Behaviorally Supported Exercise Predicts Weight Loss in Obese Adults Through Improvements in Mood, Self-Efficacy, and Self-Regulation, Rather Than by Caloric Expenditure

James J Annesi, PhD

Winter 2011 - Volume 15 Number 1

Abstract

Background: The relationship of exercise to weight loss, beyond minimal caloric expenditures possible in obese and deconditioned individuals, requires clarification.

Objective: We assessed whether changes in theory-based psychological variables associated with participation in an exercise treatment extended to psychologically based predictors of controlled eating and weight and waist-circumference reductions.

Methods: A group of 137 adults with severe obesity (mean body mass index, 42.2 kg/m2) volunteered for an exercise-support and nutrition-education treatment of 26 weeks’ duration that was based on social cognitive theory. Exercise- and eating-related measures of mood, self-regulation, and self-efficacy were obtained at baseline and at treatment end, along with weight, waist circumference, and exercise volume. Analyses were also conducted separately for women participants only (n = 102).

Results: Treatment-induced changes in total mood disturbance, self-regulatory skill usage for exercise, and exercise self-efficacy were significantly related to changes in self-efficacy to control emotional eating, self-regulatory skill usage for controlled eating, and overall self-efficacy for controlled eating, respectively (p < 0.001). Changes in the eating-related measures significantly predicted changes in weight and waist circumference with adjusted R2 values from 0.15 to 0.21 and 0.28 to 0.30, respectively (p < 0.001). Post-hoc testing indicated a strong negative correlation between exercise completed and weight change (r = –0.62); however, only 12.4% of the observed weight change was accounted for through associated caloric expenditures.

Conclusion: Exercise may support weight loss primarily through psychological rather than physiological pathways. Although the models tested were viable, additional modifiable variables may further strengthen the prediction of weight and waist-circumference change and benefit weight-loss theory and treatment outcomes.

Introduction

Exercise is a strong predictor of weight loss and maintenance of weight loss.1 However, obese and deconditioned individuals are rarely able to complete enough physical exertion to induce meaningful weight loss through associated caloric expenditures.2 It has been suggested that improvements in psychological factors associated with participation in an exercise program may extend to improvements in psychological factors associated with controlled eating and subsequent weight loss.3 For example, exercise-induced improvements in mood4 may transfer to tempered emotional eating; self-regulatory skills developed to adhere to an exercise program may transfer to self-regulation for controlled eating5; and self-efficacy for maintaining exercise may transfer to a more generalized self-efficacy for weight management and, thus, controlled eating.3 A model proposed by Baker and Brownell,3 recently adapted and tested,6,7 suggests viability of these possibilities.

An understanding of the pathways by which exercise behaviors may affect weight loss beyond caloric expenditures is needed to shape both theoretical and treatment research. Thus, relations of changes in mood, self-efficacy, and self-regulation associated with an exercise program to changes in mood, self-efficacy, and self-regulation associated with controlled eating and weight loss were tested with severely obese adults.

Methods

Study Participants

Men and women responded to local newspaper solicitations for participation in research on weight loss. Requirements were being at least age 21 years, having a body mass index (BMI) of 35 kg/m2 to 50 kg/m2, and participating in no regular exercise (< 20 minutes per week) in the previous year. Pregnancy and the use of medication for weight loss or a psychological or psychiatric condition were reasons for exclusion. We obtained a written statement of adequate physical health to participate from a physician, approval from an institutional review board, and written consent from all study participants (N = 137; mean age = 43.6 years [Standard Deviation {SD} = 9.9]; mean BMI = 42.2 kg/m2 [SD = 6.6]; racial makeup: 53% white, 45% black, and 2% other races/ethnicities; socioeconomic level: mostly lower-middle to middle class).

Measures

Total mood disturbance (TMD) is an aggregate measure of mood derived from the six subscales of the Profile of Mood States Short Form.8 Respondents rate feelings during the preceding week for 30 items (5 items for each of its subscales: tension, depression, fatigue, confusion, anger, vigor) on a scale ranging from 0 (not at all) to 4 (extremely). The internal consistency ranged from 0.84 to 0.95, and test-retest reliability at 3 weeks averaged 0.69.8

Measurement of self-regulation skills usage for both exercise (SR-Ex) and appropriate eating (SR-Eat) was adapted from a validated scale that was based on treatment content.9 Responses to the 10 items for each scale ranged from 1 (never) to 5 (often). Internal consistencies were 0.79 and 0.81, and test-retest reliabilities during a span of 2 weeks were 0.78 and 0.74, respectively.

The Exercise Self-Efficacy Scale10 (ExSE) measured perceived ability to overcome barriers to exercise. Responses range from 1 (not at all confident) to 7 (very confident). Internal consistencies ranged from 0.76 to 0.82, and test-retest reliability during a span of 2 weeks was 0.90.11
The Weight Efficacy Lifestyle Questionnaire12 measured self-efficacy for controlled eating. It is made up of 5 subscales (4 items for each of its subscales: negative emotions, availability, social pressure, physical discomfort, positive activities). Item responses range from 0 (not confident) to 9 (very confident). For this research, both the total score (WEL-Tot) and the negative emotions subscale (WEL-NegEm) were used. Internal consistencies ranged from 0.70 to 0.90 and 0.87 to 0.88, respectively.12

The Godin Leisure-Time Exercise Questionnaire13 measured exercise through study participants’ entry of weekly frequencies of strenuous, moderate, and light exercise for more than 15 minutes per session. Responses are multiplied by 9, 5, and 3 standard metabolic equivalents (METs), respectively, and then summed. For adults, test-retest reliability during a span of 2 weeks was 0.74.13 Construct validity was indicated by significant correlations with accelerometer and maximum oxygen consumption measurements.14,15

A recently calibrated digital scale was used to measure weight (kg). A tape measure was used to measure waist circumference at the umbilicus. Change scores were the difference from baseline to week 26.

Procedure

Participants were provided access to YMCA wellness centers and were enrolled in a treatment program that was based on tenets of social cognitive theory. The exercise support portion of the treatment consisted of 6 one-on-one meetings of 45 to 60 minutes each, during a span of 26 weeks.6 Instruction in an array of self-regulatory methods (eg, long- and short-term goal setting, cognitive restructuring, relapse prevention) was a primary focus. Exercise plans were based on each participant’s tolerance; however, the volume suggested for health promotion (150 minutes per week)16 was described, and it was suggested that any volume of exercise may have benefit.

The nutrition portion of the treatment consisted of six 1-hour group sessions over the initial 14 weeks.17 Components included 1) using the US Food Guide Pyramid, 2) developing a plan for snacking, and 3) using self-regulatory skills for controlled eating. Overall, attendance in treatment sessions was 72%.

Data Analyses

First, score changes in TMD, SR-Ex, ExSE, WEL-NegEm, SR-Eat, WEL-Tot, weight, waist circumference, and recalled exercise per week during the 26-week treatment were calculated. As in previous research,18,19 changes throughout treatment, rather than scores at a particular temporal point, were used to account for the dynamic nature of weight-loss treatment processes. Both actual score changes and changes controlling for baseline scores were used for analyses.

Next, linear bivariate relationships between changes in the following exercise-related and eating-related variables were calculated: 1) TMD and WEL-NegEm, 2) SR-Ex and SR-Eat, and 3) ExSE and WEL-Tot. Finally, the variance in changes in weight and waist circumference accounted for by changes in the three eating-related variables was derived using multiple regression analysis with simultaneous entry of the predictors.

Because treatments that include exercise (and hence may increase muscle density) may temper reduction in weight,20 changes in both weight and waist circumference were incorporated as outcome measures. Because WEL-NegEm was a subscale of WEL-Tot and thus had some redundancy in item responses, multiple regression analyses were also completed using only changes in WEL-Tot and SR-Eat as predictors.

For a multiple regression equation with three predictors, to detect an effect size of f2 = 0.15 at the statistical power of 0.90, a minimum of 98 study subjects was required. Because emotional eating may affect women differently than men,21 analyses were conducted with the entire sample (N = 137) and then with women only (n = 102). An intention-to-treat design was used with multiple imputation.22 Significance levels were set at α = 0.05 (two-tailed), with the Bonferroni adjustment applied where appropriate.

Results

For both the entire sample and women-only subsample, independent t-tests indicated statistically significant improvements over a span of 26 weeks in all study variables (Table 1). In all subsequent analyses, results were similar whether actual change scores or changes controlling for baseline values were incorporated. Thus, only results from actual score changes are reported. For both the entire sample and women-only subsample, significant bivariate relationships were found between changes in

  • TMD and WEL-NegEm (β = –0.30, SE = 0.05, p < 0.001, and β = –0.31, SE = 0.05, p = 0.002, respectively)
  • SR-Ex and SR-Eat (β = 0.65, SE = 0.06, p < 0.001, and β = 0.61, SE = 0.07, p < 0.001, respectively)
  • ExSE and WEL-Tot (β = 0.51, SE = 0.23, p < 0.001, and β = 0.53, SE = 0.26, p < 0.001, respectively).

For both the entire sample and the women-only subsample, changes in WEL-NegEm, SR-Eat, and WEL-Tot accounted for a significant portion of the variance in weight and waist-circumference changes (Table 2). In each of the four multiple regression equations having three predictors, changes in SR-Eat explained a significant unique portion of the variance. In the women-only subsample, change in WEL-Tot was also a significant unique predictor. For both the entire sample and the women-only subsample, changes in SR-Eat and WEL-Tot accounted for a significant portion of the variance in waist-circumference changes in each of the multiple regression equations having two predictors (Table 2). In the two-predictor equations, both predictors explained at least a marginally significant (p < 0.07) unique portion of the variance.

Post-Hoc Test

When change in exercise volume per week for both the entire sample and the women-only subsample was converted to caloric expenditure on the basis of previous research,18,23 only 12.4% and 13.1%, respectively, of weight change was explained, although the correlations between changes in exercise and weight were strong (r values = –0.62 and –0.55, respectively; p < 0.001).

Discussion

Carryover from improvements in mood, self-regulation, and self-efficacy, (associated with an exercise treatment using cognitive-behavioral methods) to improvements in corresponding variables associated with controlled eating was previously suggested,3,19 but empirical verification was largely missing. The present findings suggested that exercise’s association with weight loss was better explained through such psychological, rather than physiological (ie, caloric expenditure), pathways. This has considerable implications for weight-loss theory development and clinical applications, suggesting that attention should be given to the mood-enhancing properties and to improvements in self-regulation and self-efficacy that are possible through behaviorally based exercise treatments.

Replications should incorporate more controlled settings, direct measurement of eating behaviors and caloric consumption, and, possibly, inclusion of additional variables to extend the present prediction models. Continued testing within field settings with a variety of sample types (eg, persons who have undergone bariatric surgery, morbidly obese persons), however, may have more immediate benefits for practical application of findings.24 The directionality of the identified relationships also requires further investigation. Hopefully, behavioral interventions directed at eating behaviors can be paired with appropriately supported exercise to reliably improve lagging weight-loss treatment outcomes25 over the long term.

Disclosure Statement

The author(s) have no conflicts of interest to disclose.

Acknowledgments

The research reported herein was supported by a grant from Blue Cross Blue Shield of Georgia.

Katharine O’Moore-Klopf, ELS, of KOK Edit provided editorial assistance.

References
1.    Miller WC, Koceja DM, Hamilton EJ. A meta-analysis of the past 25 years of weight loss research using diet, exercise or diet plus exercise intervention. Int J Obes Relat Metab Disord 1997 Oct;21(10):941–7.
2.    Donnelly JE, Blair SN, Jakicic JM, Manore MM, Rankin JW, Smith BK; American College of Sports Medicine. American College of Sports Medicine Position Stand. Appropriate physical activity intervention strategies for weight loss and prevention of weight regain for adults. Med Sci Sports Exerc 2009 Feb;41(2):459–71. Erratum in: Med Sci Sports Exerc 2009 Jul;41(7):1532.
3.    Baker CW, Brownell KD. Physical activity and maintenance of weight loss: physiological and psychological mechanisms. In: Bouchard C, editor. Physical activity and obesity. Champaign, IL: Human Kinetics, 2000. p 311–28.
4.    Landers DM, Arent SM. Physical activity and mental health. In: Tennenbaum G, Eklund RC, editors. Handbook of sport psychology. 3rd ed. New York, NY: Wiley; 2007. p 469–91.
5.    Hagger MS, Wood C, Stiff C, Chatzisarantis NL. Ego depletion and the strength model of self-control: a meta-analysis. Psychol Bull 2010 Jul;136(4):495–525.
6.    Annesi JJ, Unruh JL. Relations of exercise, self-appraisal, mood changes and weight loss in obese women: testing propositions based on Baker and Brownell’s (2000) model. Am J Med Sci 2008 Mar;335(3):198–204.
7.    Mata J, Silva MN, Vieira PN, et al. Motivational “spill-over” during weight control: increased self-determination and exercise intrinsic motivation predict eating self-regulation. Health Psychol 2009 Nov;28(6):709–16.
8.    McNair DM, Heuchert JWP. Profile of Mood States (POMS), technical update. North Tonawanda, NY: Multi-Health Systems, 2009.
9.    Saelens BE, Gehrman CA, Sallis JF, Calfas KJ, Sarkin JA, Caparosa S. Use of self-management strategies in a 2-year cognitive-behavioral intervention to promote physical activity. Behav Ther 2000;31(2):365–79.
10.    Marcus BH, Selby VC, Niaura RS, Rossi JS. Self-efficacy and the stages of exercise behavior change. Res Q Exerc Sport 1992 Mar;63(1):60–6.
11.    McAuley E, Mihalko SL: Measuring exercise-related self-efficacy. In: Duda JL, editor. Advances in sport and exercise psychology measurement. Morgantown, WV: Fitness Information Technology, 1998. p. 371–90.
12.    Clark MM, Abrams DB, Niaura RS, Eaton CA, Rossi JS. Self-efficacy in weight management. J Consult Clin Psychol 1991 Oct;59(5):739–44.
13.    Godin G, Shephard RJ. A simple method to assess exercise behavior in the community. Can J Appl Sport Sci 1985 Sep;10(3):141–6.
14.    Jacobs DR Jr, Ainsworth BE, Hartman TJ, Leon AS. A simultaneous evaluation of 10 commonly used physical activity questionnaires. Med Sci Sports Exerc 1993 Jan;25(1):81–91.
15.    Miller DJ, Freedson PS, Kline GM. Comparison of activity levels using Caltrac accelerometer and five questionnaires. Med Sci Sports Exerc 1994 Mar;26(3):376–82.
16.    Haskell WL, Lee IM, Pate RR, et al. Physical activity and public health: updated recommendation from the American College of Sports Medicine and the American Heart Association. Med Sci Sports Exerc 2007 Aug;39(8):1423–34.
17.    Kaiser Permanente Health Education Services. Cultivating health weight management kit. 8th ed. Portland, OR: Kaiser Permanente, 2008.
18.    Annesi JJ, Gorjala S. Changes in theory-based psychological factors predict weight loss in women with class III obesity initiating supported exercise. J Obes 2010;2010:171957.Epub 2010 Jun 2.
19.    Jakicic JM, Wing RR, Winters-Hart C. Relationship of physical activity to eating behaviors and weight loss in women. Med Sci Sports Exerc 2002 Oct;34(10):1653–9.
20.    Després J, Lamarche B. Physical activity and the metabolic complications of obesity. In: Bouchard C, editor. Physical activity and obesity. Champaign, IL: Human Kinetics; 2000. p 331–54.
21.    Tanofsky MB, Wilfley DE, Spurrell EB, Welch R, Brownell KD. Comparison of men and women with binge eating disorder. Int J Eat Disord 1997 Jan;21(1):49–54.
22.    Kline RB. Principles and practice of structural equation modeling. 2nd ed. New York, NY: Guilford; 2005.
23.    Hall KD. What is the required energy deficit per unit weight loss? Int J Obes (Lond) 2008 Mar;32(3):573–6.
24.    Glasgow RE, Emmons KM. How can we increase translation of research into practice? Types of evidence needed. Annu Rev Public Health 2007;28:413–33.
25.    Mann T, Tomiyama AJ, Westling E, Lew AM, Samuels B, Chatman J. Medicare’s search for effective obesity treatments: diets are not the answer. Am Psychol 2007 Apr;62(3):220–33.

More from this Journal section

Nutritional Update for Physicians: Plant-Based Diets
Wednesday, 27 March 2013
Phillip J Tuso, MD; Mohamed H Ismail, MD; Benjamin P Ha, MD; Carole Bartolotto, MA, RD Perm J 2013 Spring; 17(2):61-66 http://dx.doi.org/10.7812/TPP/12-085 Abstract The objective of this article is to present to physicians an update on plant-based diets. Concerns about the rising cost of health care are being voiced nationwide, even as unhealthy lifestyles are contributing to the spread of obesity, diabetes, and cardiovascular disease. For these reasons, physicians looking for cost-effective interventions to improve health outcomes are becoming more involved in helping their patients adopt healthier lifestyles. Healthy eating may be best achieved with a plant-based diet, which we define as a regimen that encourages whole, plant-based foods and discourages meats, dairy products, and eggs as well as all refined and processed foods. We present a case study as an example of the potential health benefits of such a diet. Research shows that plant-based diets are cost-effective, low-risk interventions that may lower body mass index, blood pressure, HbA1C, and cholesterol levels. They may also reduce the number of medications needed to treat chronic diseases and lower ischemic heart disease mortality rates. Physicians should consider recommending a plant-based diet to all their patients, especially those with high blood pressure, diabetes, cardiovascular disease, or obesity. Introduction In the HBO documentary The Weight of the Nation, it was noted that if you “go with the flow” in the US, you will eventually become obese.1 In 2011, Witters reported that in some areas of the country, the rate of obesity is 39% and is increasing at a rate of 5% per year.2 Risks of obesity, diabetes, hypertension, and cardiovascular disease, along with their ensuing complications (eg, behavioral health and quality-of-life problems) often go hand-in-hand and are strongly linked to lifestyle, especially dietary choices.3 Of all the diets recommended over the last few decades to turn the tide of these chronic illnesses, the best but perhaps least common may be those that are plant based. Despite the strong body of evidence favoring plant-based diets, including studies showing a willingness of the general public to embrace them,4 many physicians are not stressing the importance of plant-based diets as a first-line treatment for chronic illnesses. This could be because of a lack of awareness of these diets or a lack of patient education resources. National dietary guidelines for active living and healthful eating are available at www.ChooseMyPlate.gov.5 A typical healthful plate of food is 1/2 plant foods (nonstarchy vegetables and fruits), 1/4 whole grains or unprocessed starchy food, and 1/4 lean protein. The goal of this article is to review the evidence supporting plant-based diets and to provide a guideline for presenting them to patients. We start with a case study and conclude with a review of the literature. Case Study A 63-year-old man with a history of hypertension presented to his primary care physician with complaints of fatigue, nausea, and muscle cramps. The result of a random blood glucose test was 524 mg/dL, and HbA1C was 11.1%. Type 2 diabetes was diagnosed. His total cholesterol was 283 mg/dL, blood pressure was 132/66 mmHg, and body mass index (BMI) was 25 kg/m2. He was taking lisinopril, 40 mg daily; hydrochlorothiazide, 50 mg daily; amlodipine, 5 mg daily; and atorvastatin, 20 mg daily. He was prescribed metformin, 1000 mg twice daily; glipizide, 5 mg daily; and 10 units of neutral protamine Hagedom insulin at bedtime. His physician also prescribed a low-sodium, plant-based diet that excluded all animal products and refined sugars and limited bread, rice, potatoes, and tortillas to a single daily serving. He was advised to consume unlimited nonstarchy vegetables, legumes, and beans, in addition to up to 2 ounces of nuts and seeds daily. He was also asked to begin exercising 15 minutes twice a day. The patient was seen monthly in his primary care clinic. Over a 16-week period, significant improvement in biometric outcome measures was observed. He was completely weaned off of amlodipine, hydrochlorothiazide, glipizide, and neutral protamine Hagedorn insulin. Follow-up blood pressure remained below 125/60 mmHg, HbA1C improved to 6.3%, and total cholesterol improved to 138 mg/dL. Lisinopril was gradually decreased to 5 mg daily and his diabetes is controlled with metformin alone, 1000 mg twice daily. Definitions of Plant-Based Diets The presented case is a dramatic example of the effect a plant-based diet can have on biometric outcomes like blood pressure, diabetes, and lipid profile. The reduction in HbA1C from 11.1% to 6.3% in 3 months is much better than would be expected with monotherapy with metformin6 or daily exercise.7 The improvement in blood pressure observed over a 4-month period with few medications is also rarely encountered in clinical practice and is likely related to a low-sodium diet and the avoidance of red meat. Because the patient was not obese and did not have significant weight loss with the diet, the dramatic improvements appear to be related to the quality of his new diet. A healthy, plant-based diet aims to maximize consumption of nutrient-dense plant foods while minimizing processed foods, oils, and animal foods (including dairy products and eggs). It encourages lots of vegetables (cooked or raw), fruits, beans, peas, lentils, soybeans, seeds, and nuts (in smaller amounts) and is generally low fat.8,9 Leading proponents in the field have varying opinions as to what comprises the optimal plant-based diet. Ornish et al recommends allowing animal products such as egg whites and skim milk in small amounts for reversal of disease.10,11 Esselstyn, who directs the cardiovascular prevention and reversal program at the Cleveland Clinic Wellness Institute, recommends completely avoiding all animal-based products as well as soybeans and nuts, particularly if severe coronary artery disease is present.12 Despite these smaller differences, there is evidence that a broadly defined plant-based diet has significant health benefits. It should be noted that the term plant-based is sometimes used interchangeably with vegetarian or vegan. Vegetarian or vegan diets adopted for ethical or religious reasons may or may not be healthy. It is thus important to know the specific definitions of related diets and to ascertain the details of a patient’s diet rather than making assumptions about how healthy it is. The following is a brief summary of typical diets that restrict animal products. A key distinction is that although most of these diets are defined by what they exclude, the plant-based diet is defined by what it includes. Vegan (or total vegetarian): Excludes all animal products, especially meat, seafood, poultry, eggs, and dairy products. Does not require consumption of whole foods or restrict fat or refined sugar. Raw food, vegan: Same exclusions as veganism as well as the exclusion of all foods cooked at temperatures greater than 118°F. Lacto-vegetarian: Excludes eggs, meat, seafood, and poultry and includes milk products. Ovo-vegetarian: Excludes meat, seafood, poultry, and dairy products and includes eggs. Lacto-ovo vegetarian: Excludes meat, seafood, and poultry and includes eggs and dairy products. Mediterranean: Similar to whole-foods, plant-based diet but allows small amounts of chicken, dairy products, eggs, and red meat once or twice per month. Fish and olive oil are encouraged. Fat is not restricted. Whole-foods, plant-based, low-fat: Encourages plant foods in their whole form, especially vegetables, fruits, legumes, and seeds and nuts (in smaller amounts). For maximal health benefits this diet limits animal products. Total fat is generally restricted. Benefits of Plant-Based Diets The goal of our diet should be to improve our health. In this section, we will review the literature for key articles that demonstrate the benefits of plant-based diets. Our review consists of existing studies that include vegan, vegetarian, and Mediterranean diets. Obesity In 2006, after reviewing data from 87 published studies, authors Berkow and Barnard13 reported in Nutrition Reviews that a vegan or vegetarian diet is highly effective for weight loss. They also found that vegetarian populations have lower rates of heart disease, high blood pressure, diabetes, and obesity. In addition, their review suggests that weight loss in vegetarians is not dependent on exercise and occurs at a rate of approximately 1 pound per week. The authors further stated that a vegan diet caused more calories to be burned after meals, in contrast to nonvegan diets which may cause fewer calories to be burned because food is being stored as fat.13 Farmer et al14 suggest that vegetarian diets may be better for weight management and may be more nutritious than diets that include meat. In their study, they showed that vegetarians were slimmer than their meat-eating counterparts. Vegetarians were also found to consume more magnesium, potassium, iron, thiamin, riboflavin, folate, and vitamins and less total fat. The authors conclude that vegetarian diets are nutrient dense and can be recommended for weight management without compromising diet quality.14 In 2009, Wang and Beysoun15 analyzed the nationally representative data collected in the 1999-2004 National Health and Nutrition Examination Survey. The aim of their study was to analyze the associations between meat consumption and obesity. Using linear and logistic regression analyses, they showed that there was a positive association between meat consumption and obesity.15 The Oxford component of the European Prospective Investigation into Cancer and Nutrition assessed changes in weight and BMI over a five-year period in meat-eating, fish-eating, vegetarian, and vegan men and women in the United Kingdom. During the five years of the study, mean annual weight gain was lowest among individuals who had changed to a diet containing fewer animal foods. The study also reported a significant difference in age-adjusted BMI, with the meat eaters having the highest BMI and vegans the lowest.16 Similar results were reported by the Adventist Health Study.17 According to Sabaté and Wien,18 “Epidemiologic studies indicate that vegetarian diets are associated with a lower BMI and a lower prevalence of obesity in adults and children. A meta-analysis of adult vegetarian diet studies estimated a reduced weight difference of 7.6 kg for men and 3.3 kg for women, which resulted in a 2-point lower BMI. Similarly, compared with nonvegetarians, vegetarian children are leaner, and their BMI difference becomes greater during adolescence. Studies exploring the risk of overweight and food groups and dietary patterns indicate that a plant-based diet seems to be a sensible approach for the prevention of obesity in children. Plant-based diets are low in energy density and high in complex carbohydrate, fiber, and water, which may increase satiety and resting energy expenditure.”18 The authors conclude that plant-based dietary patterns should be encouraged for optimal health. Diabetes Plant-based diets may offer an advantage over those that are not plant based with respect to prevention and management of diabetes. The Adventist Health Studies found that vegetarians have approximately half the risk of developing diabetes as nonvegetarians.19 In 2008, Vang et al20 reported that nonvegetarians were 74% more likely to develop diabetes over a 17-year period than vegetarians. In 2009, a study involving more than 60,000 men and women found that the prevalence of diabetes in individuals on a vegan diet was 2.9%, compared with 7.6% in the nonvegetarians.17 A low-fat, plant-based diet with no or little meat may help prevent and treat diabetes, possibly by improving insulin sensitivity and decreasing insulin resistance. Barnard et al21 reported in 2006 the results of a randomized clinical trial comparing a low-fat vegan diet with a diet based on the American Diabetes Association guidelines. People on the low-fat vegan diet reduced their HbA1C levels by 1.23 points, compared with 0.38 points for the people on the American Diabetes Association diet. In addition, 43% of people on the low-fat vegan diet were able to reduce their medication, compared with 26% of those on the American Diabetes Association diet.18 Heart Disease In the Lifestyle Heart Trial, Ornish10 found that 82% of patients with diagnosed heart disease who followed his program had some level of regression of atherosclerosis. Comprehensive lifestyle changes appear to be the catalyst that brought about this regression of even severe coronary atherosclerosis after only 1 year. In his plant-based regimen, 10% of calories came from fat, 15% to 20% from protein, and 70% to 75% from carbohydrate, and cholesterol was restricted to 5 mg per day. Interestingly, 53% of the control group had progression of atherosclerosis. After 5 years, stenosis in the experimental group decreased from 37.8% to 34.7% (a 7.9% relative improvement). The control group experienced a progression of stenosis from 46.1% to 57.9% (a 27.7% relative worsening). Low-density lipoprotein had decreased 40% at 1 year and was maintained at 20% less than baseline after 5 years. These reductions are similar to results achieved with lipid-lowering medications.10,11 In the Lyon Diet Heart Study, a prospective, randomized, secondary prevention trial, de Lorgeril found that the intervention group (at 27 months) experienced a 73% decrease in coronary events and a 70% decrease in all-cause mortality. The intervention group’s Mediterranean-style diet included more plant foods, vegetables, fruits, and fish than meat. Butter and cream were replaced with canola oil margarine. Canola oil and olive oil were the only fats recommended.22 In 1998, a collaborative analysis using original data from 5 prospective studies was reviewed and reported in the journal Public Health Nutrition. It compared ischemic heart disease-specific death rate ratios of vegetarians and nonvegetarians. The vegetarians had a 24% reduction in ischemic heart disease death rates compared with nonvegetarians.23 The lower risk of ischemic heart disease may be related to lower cholesterol levels in individuals who consume less meat.24 Although vegetarian diets are associated with lower risk of several chronic diseases, different types of vegetarians may not experience the same effects on health. The key is to focus on eating a healthy diet, not simply a vegan or vegetarian diet.25 High Blood Pressure In 2010, the Dietary Guidelines Advisory Committee performed a literature review to identify articles examining the effect of dietary patterns on blood pressure in adults. Vegetarian diets were associated with lower systolic blood pressure and lower diastolic blood pressure.25 One randomized crossover trial found that a Japanese diet (low sodium and plant based) significantly reduced systolic blood pressure.27 Mortality The Dietary Guidelines Advisory Committee also performed a 2010 literature review to determine the effect of plant-based diets on stroke, cardiovascular disease, and total mortality in adults. They found that plant-based diets were associated with a reduced risk of cardiovascular disease and mortality compared with non-plant-based diets.26 The benefit of plant-based diets on mortality may be primarily caused by decreased consumption of red meat.28 Several studies have documented the benefits of avoiding excessive consumption of red meat, which is associated with an increased risk of all-cause mortality and an increased risk of cardiovascular mortality.29 Low meat intake has been associated with longevity.30 In 2012, Huang et al31 performed a meta-analysis to investigate cardiovascular disease mortality among vegetarians and nonvegetarians. They only included studies that reported relative risks and corresponding 95% confidence intervals. Seven studies with a combined total of 124,706 participants were analyzed. Vegetarians had 29% lower ischemic heart disease mortality than nonvegetarians.31 Health Concerns About Plant-Based Diets Protein Generally, patients on a plant-based diet are not at risk for protein deficiency. Proteins are made up of amino acids, some of which, called essential amino acids, cannot be synthesized by the body and must be obtained from food. Essential amino acids are found in meat, dairy products, and eggs, as well as many plant-based foods, such as quinoa.32 Essential amino acids can also be obtained by eating certain combinations of plant-based foods. Examples include brown rice with beans, and hummus with whole wheat pita. Therefore, a well-balanced, plant-based diet will provide adequate amounts of essential amino acids and prevent protein deficiency.33 Soybeans and foods made from soybeans are good sources of protein and may help lower levels of low-density lipoprotein in the blood34 and reduce the risk of hip fractures35 and some cancers. A study in the Journal of the American Medical Association36 reported that women with breast cancer who regularly consumed soy products had a 32% lower risk of breast cancer recurrence and a 29% decreased risk of death, compared with women who consumed little or no soy.36 An analysis of 14 studies, published in the American Journal of Clinical Nutrition, showed that increased intake of soy resulted in a 26% reduction in prostate cancer risk.37 Because of concerns over the estrogenic nature of soy products, women with a history of breast cancer should discuss soy foods with their oncologists. Also, overly processed, soy-based meat substitutes are often high in isolated soy proteins and other ingredients that may not be as healthy as less processed soy products (ie, tofu, tempeh, and soy milk). Iron Plant-based diets contain iron, but the iron in plants has a lower bioavailability than the iron in meat. Plant-based foods that are rich in iron include kidney beans, black beans, soybeans, spinach, raisins, cashews, oatmeal, cabbage, and tomato juice.38 Iron stores may be lower in individuals who follow a plant-based diet and consume little or no animal products. However, the American Dietetic Association states that iron-deficiency anemia is rare even in individuals who follow a plant-based diet.39 Vitamin B12 Vitamin B12 is needed for blood formation and cell division. Vitamin B12 deficiency is a very serious problem and can lead to macrocytic anemia and irreversible nerve damage. Vitamin B12 is produced by bacteria, not plants oranimals. Individuals who follow a plant-based diet that includes no animal products may be vulnerable to B12 deficiency40 and need to supplement their diet with vitamin B12 or foods fortified with vitamin B12.41 Calcium and Vitamin D Calcium intake can be adequate in a well-balanced, carefully planned, plant-based diet. People who do not eat plants that contain high amounts of calcium may be at risk for impaired bone mineralization and fractures. However, studies have shown that fracture risk was similar for vegetarians and nonvegetarians. The key to bone health is adequate calcium intake, which appears to be irrespective of dietary preferences.42 Some significant sources of calcium include tofu, mustard and turnip greens, bok choy, and kale. Spinach and some other plants contain calcium that, although abundant, is bound to oxalate and therefore is poorly absorbed.43 Vitamin D deficiency is common in the general population. Plant-based products such as soy milk and cereal grains may be fortified to provide an adequate source of Vitamin D.44 Supplements are recommended for those who are at risk for low bone mineral density and for those found to be deficient in vitamin D. Fatty Acids Essential fatty acids are fatty acids that humans must ingest for good health because our bodies do not synthesize them. Only two such essential fatty acids are known: linoleic acid (an omega-6 fatty acid) and alpha-linolenic acid (an omega-3 fatty acid). Three other fatty acids are only conditionally essential: palmitoleic acid (a monounsaturated fatty acid), lauric acid (a saturated fatty acid), and gamma-linolenic acid (an omega-6 fatty acid). Deficiency in essential fatty acids may manifest as skin, hair, and nail abnormalities.45 The fatty acids that vegans are most likely to be deficient in are the omega-3 fats (n-3 fats). Consumptions of the plant version of omega-3 fats, alpha-linolenic acid, are also low in vegans. Adequate intake of n-3 fats is associated with a reduced incidence of heart disease and stroke. Foods that are good sources of n-3 fats should be emphasized. They include ground flax seeds, flax oil, walnuts, and canola oil.46 Conclusion A healthy, plant-based diet requires planning, reading labels, and discipline. The recommendations for patients who want to follow a plant-based diet may include eating a variety of fruits and vegetables that may include beans, legumes, seeds, nuts, and whole grains and avoiding or limiting animal products, added fats, oils, and refined, processed carbohydrates. The major benefits for patients who decide to start a plant-based diet are the possibility of reducing the number of medications they take to treat a variety of chronic conditions, lower body weight, decreased risk of cancer, and a reduction in their risk of death from ischemic heart disease. A plant-based diet is not an all-or-nothing program, but a way of life that is tailored to each individual. It may be especially beneficial for those with obesity, Type 2 diabetes, high blood pressure, lipid disorders, or cardiovascular disease. The benefits realized will be relative to the level of adherence and the amount of animal products consumed. Strict forms of plant-based diets with little or no animal products may be needed for individuals with inoperable or severe coronary artery disease. Low-sodium, plant-based diets may be prescribed for individuals with high blood pressure or a family history of coronary artery disease or stroke. A patient with obesity and diabetes will benefit from a plant-based diet that includes a moderate amount of fruits and vegetables and minimal low-fat animal products. Severe obesity may require counseling and initial management with a low-calorie diet or very-low-calorie diet and the supervision of a physician’s team. Patients with kidney disease may need a plant-based diet with special restrictions, for example fruits and vegetables that are high in potassium and phosphorus. Finally, patients with thyroid disease will need to be careful when consuming plants that are mild goitrogens, like soy, raw cruciferous vegetables, sweet potatoes, and corn. These patients should be informed that cooking these vegetables inactivates the goitrogens. Physicians should advocate that it is time to get away from terms like vegan and vegetarian and start talking about eating healthy, whole, plant-based foods (primarily fruits and vegetables) and minimizing consumption of meat, eggs, and dairy products. Physicians should be informed about these concepts so they can teach them to staff and patients. A registered dietitian should be part of the health care team that designs a plant-based diet for patients with chronic disease, especially if multiple medications are involved. Depending on the underlying conditions, patients with chronic disease who take multiple medications need close monitoring of low blood sugar levels, low blood pressure, or rapid weight loss. If these occur, the physician may need to adjust medications. In some cases, such as the one presented here, the need for certain medications can be eliminated altogether. Although the risk of deficiencies may be low, health care teams need to be aware that a motivated patient on a strict plant-based diet may need monitoring for deficiencies of certain nutrients, as outlined above. The purpose of this article is to help physicians understand the potential benefits of a plant-based diet, to the end of working together to create a societal shift toward plant-based nutrition. There is at least moderate-quality evidence from the literature that plant-based diets are associated with significant weight loss and a reduced risk of cardiovascular disease and mortality compared with diets that are not plant based. These data suggest that plant-based diets may be a practical solution to prevent and treat chronic diseases. Further research is needed to find ways to make plant-based diets the new normal for our patients and employees. We cannot cure chronic diseases, but we may be able to prevent and control them by changing how we eat. With education and monitoring for adherence, we can improve health outcomes. Patterns of families and other colleagues who may be reluctant to support the efforts of individuals who are trying to change are a challenge to be overcome. We should invite our colleagues, patients, and their families to a shared decision-making process with the goal of adopting a plant-based diet and a regular exercise program. We should invite health care teams to complete a course on healthy eating and active living. We should encourage staff to be knowledgeable about plant-based nutrition. Finally, we should encourage performance-driven measurable outcomes, which may include: the percentage of physicians who have completed a course on nutrition that includes a discussion of the benefits of a plant-based diet and exercise; the percentage of our hospitals, cafeterias, and physicians’ meeting facilities that serve meals that are consistent with a plant-based diet; the percentage of patients on a physician panel who are obese and who have completed a course on weight management and nutrition that emphasizes a plant-based diet; and the percentage of patients in a physician panel with high blood pressure, diabetes, high cholesterol, or cardiovascular disease who completed a course on nutrition that emphasizes a plant-based diet. Too often, physicians ignore the potential benefits of good nutrition and quickly prescribe medications instead of giving patients a chance to correct their disease through healthy eating and active living. If we are to slow down the obesity epidemic and reduce the complications of chronic disease, we must consider changing our culture’s mind-set from “live to eat” to “eat to live.” The future of health care will involve an evolution toward a paradigm where the prevention and treatment of disease is centered, not on a pill or surgical procedure, but on another serving of fruits and vegetables. Disclosure statement The author(s) have no conflicts of interest to disclose. Acknowledgment Kathleen Louden, ELS, of Louden Health Communications provided editorial assistance. References     1.    HBO Documentary Films; Institute of Medicine of the National Academies; Centers for Disease Control and Prevention; National Institutes of Health; Michael and Susan Dell Foundation; Kaiser Permanente. The weight of the nation [documentary]. New York, NY: Home Box Office, Inc; 2012. Available from: http://theweightofthenation.hbo.com/?cmpid=ABC1213.     2.    Witters D. More than 15% obese in nearly all US metro areas [monograph on the Internet]. Washington, DC: Gallup Wellbeing; 2012 Mar 7 [cited 2012 Oct 6]. Available from: www.gallup.com/poll/153143/Obese-Nearly-Metro-Areas.aspx.    3.    US Department of Health and Human Services. The surgeon general’s call to action to prevent and decrease overweight and obesity [monograph on the Internet]. Rockville, MD: US Department of Health and Human Services, Public Health Service, Office of the Surgeon General; 2001 [cited 22 Jan 2013]. Available from: www.surgeongeneral.gov/library/calls/obesity/index.html    4.    Lea EJ, Crawford D, Worsley A. Public views of the benefits and barriers to the consumption of a plant-based diet. Eur J Clin Nutr 2006 Jul;60(7):828-37. DOI: http://dx.doi.org/10.1038/sj.ejcn.1602387    5.    ChooseMyPlate.gov [homepage on the Internet]. Alexandria, VA: US Department of Agriculture, Center for Nutrition Policy and Promotion; [cited 2013 Jan 31]. Available from: www.choosemyplate.gov/.    6.    Ito H, Ishida H, Takeuchi Y, et al. Long-term effects of metformin on blood glucose control in non-obese patients with type 2 diabetes mellitus. Nutr Metab (Lond) 2010 Nov 12;7:83. DOI: http://dx.doi.org/10.1186/1743-7075-7-83    7.    Sigal RJ, Kenny GP, Boulé NG, et al. Effects of aerobic training, resistance training, or both on glycemic control in type 2 diabetes: a randomized trial. Ann Intern Med 2007 Sep 18;147(6):357-69.    8.    Blaney D, Diehl H. The optimal diet: the official CHIP cookbook. Hagerstown, MD: Autumn House Publishing; 2009 Jan 1.    9.    McDougall, JA, McDougall M. (1997). The new McDougall cookbook: 300 delicious ultra-low-fat recipes. New York, NY: Plume; 1997 Jan 1.    10.    Ornish D, Brown SE, Scherwitz LW, et al. Can lifestyle changes reverse coronary heart disease? The Lifestyle Heart Trial. Lancet 1990 Jul 21;336(8708):129-33. DOI: http://dx.doi.org/10.1016/0140-6736(90)91656-U    11.    Ornish D, Scherwitz LW, Billings JH, et al. Intensive lifestyle changes for reversal of coronary heart disease. JAMA 1998 Dec 16;280(23):2001-7. DOI: http://dx.doi.org/10.1001/jama.280.23.2001    12.    Esselstyn CB Jr. Prevent and reverse heart disease: q & a with Caldwell B Esselstyn, Jr, MD [monograph on the Internet]. Lyndhurst, OH: Prevent and Reverse Heart Disease; [cited 2012 Oct 6]. Available from: www.heartattackproof.com/qanda.htm.    13.    Berkow SE, Barnard N. Vegetarian  diets and weight status. Nutr Rev 2006 Apr;64(4):175-88. DOI: http://dx.doi.org/10.1111/j.1753-4887.2006.tb00200.x    14.    Farmer B, Larson BT, Fulgoni VL 3rd, Rainville AJ, Liepa GU. A vegetarian dietary pattern as a nutrient-dense approach to weight management: an analysis of the national health and nutrition examination survey 1999-2004. J Am Diet Assoc 2011 Jun;111(6):819-27. DOI: http://dx.doi.org/10.1016/j.jada.2011.03.012    15.    Wang Y, Beydoun MA. Meat consumption is associated with obesity and central obesity among US adults. Int J Obes (Lond) 2009 Jun;33(6):621-8. DOI: http://dx.doi.org/10.1038/ijo.2009.45    16.    Rosell M, Appleby P, Spencer E, Key T. Weight gain over 5 years in 21,966 meat-eating, fish-eating, vegetarian, and vegan men and women in EPIC-Oxford. Int J Obes (Lond) 2006 Sep;30(9):1389-96. DOI: http://dx.doi.org/10.1038/sj.ijo.0803305    17.    Tonstad S, Butler T, Yan R, Fraser GE. Type of vegetarian diet, body weight, and prevalence of type 2 diabetes. Diabetes Care 2009 May;32(5):791-6. DOI: http://dx.doi.org/10.2337/dc08-1886    18.    Sabaté J, Wien M. Vegetarian diets and childhood obesity prevention. Am J Clin Nutr 2010 May;91(5):1525S-1529S. DOI: http://dx.doi.org/10.3945/ajcn.2010.28701F    19.    Snowdon DA, Phillips RL. Does a vegetarian diet reduce the occurrence of diabetes? Am J Public Health 1985 May;75(5):507-12. DOI: http://dx.doi.org/10.2105/AJPH.75.5.507    20.    Vang A, Singh PN, Lee JW, Haddad EH, Brinegar CH. Meats, processed meats, obesity, weight gain and occurrence of diabetes among adults: findings from Adventist Health Studies. Ann Nutr Metab 2008;52(2):96-104. DOI: http://dx.doi.org/10.1159/000121365    21.    Barnard ND, Cohen J, Jenkins DJ, et al. A low-fat vegan diet improves glycemic control and cardiovascular risk factors in a randomized clinical trial in individuals with type 2 diabetes. Diabetes Care 2006 Aug;29(8):1777-83. DOI: http://dx.doi.org/10.2337/dc06-0606    22.    de Lorgeril M, Salen P, Martin JL, Monjaud I, Delaye J, Mamelle N. Mediterranean diet, traditional risk factors, and the rate of cardiovascular complications after myocardial infarction: final report of the Lyon Diet Heart Study. Circulation 1999 Feb;99(6):779-85. DOI: http://dx.doi.org/10.1161/01.CIR.99.6.779    23.    Key TJ, Fraser GE, Thorogood M, et al. Mortality in vegetarians and non-vegetarians: a collaborative analysis of 8300 deaths among 76,000 men and women in five prospective studies. Public Health Nutr 1998 Mar;1(1):33-41. DOI: http://dx.doi.org/10.1079/PHN19980006    24.    Appleby PN, Thorogood M, McPherson K, Mann JI. Associations between plasma lipid concentrations and dietary, lifestyle and physical factors in the Oxford Vegetarian Study. J Hum Nutr Diet 1995 Oct;8(5):305-14. DOI: http://dx.doi.org/10.1111/j.1365-277X.1995.tb00324.x     25.    Fraser GE. Vegetarian diets: what do we know of their effects on common chronic diseases? Am J Clin Nutr 2009;89(5):1607S-1612S. DOI: http://dx.doi.org/10.3945/ajcn.2009.26736KErratum in: Am J Clin Nutr 2009 Jul;90(1):248. DOI: http://dx.doi.org/10.3945/​ajcn.2009.27933    26.    Report of the Dietary Guidelines Advisory Committee on the dietary guidelines for Americans, 2010: to the Secretary of Agriculture and the Secretary of Health and Human Services. Washington, DC: Agriculture Research Service, US Department of Agriculture, US Department of Health and Human Services; 2010 May.     27.    Takahashi Y, Sasaki S, Okubo S, Hayashi M, Tsugane S. Blood pressure change in a free-living population-based dietary modification study in Japan. J Hypertens. 2006 Mar;24(3):451-8. DOI: http://dx.doi.org/10.1097/01.hjh.0000209980.36359.16    28.    Singh PN, Sabaté J, Fraser GE. Does low meat consumption increase life expectancy in humans? Am J Clin Nutr 2003 Sep;78(3 Suppl):526S-532S.    29.    Campbell TC, Campbell TM II. The China study: the most comprehensive study of nutrition ever conducted and the startling implications for diet, weight loss and long-term health. Dallas, TX: BenBella Books; 2006 May 11.    30.    Sinha R, Cross AJ, Graubard BI, Leitzmann MF, Schatzkin A. Meat intake and mortality: a prospective study of over half a million people. Arch Intern Med 2009 Mar 23;169(6):562‑71. DOI: http://dx.doi.org/10.1001/archinternmed.2009.6    31.    Huang T, Yang B, Zheng J, Li G, Wahlqvist ML, Li D. Cardiovascular disease mortality and cancer incidence in vegetarians: a meta-analysis and systematic review. Ann Nutr Metab 2012;60(4):233-40. DOI: http://dx.doi.org/10.1159/000337301    32.    Nutritiondata.self.com [web page on the Internet]. Soybeans, mature seeds, raw. New York, NY: Condé Nast; 2012 [cited 2012 Oct 6]. Available from: http://nutritiondata.self.com/facts/legumes-and-legume-products/4375/2.    33.    Young VR, Pellett PL. Plant proteins in relation to human protein and amino acid nutrition. Am J Clin Nutr 1994 May;59(5 Suppl):1203S-1212S.    34.    Pipe EA, Gobert CP, Capes SE, Darlington GA, Lampe JW, Duncan AM. Soy protein reduces serum LDL cholesterol and the LDL cholesterol: HDL cholesterol and apolipoprotein B: apolipoprotein A-I ratios in adults with type 2 diabetes. J Nutr 2009 Sep;139(9):1700-6. DOI: http://dx.doi.org/10.3945/jn.109.109595    35.    Koh WP, Wu AH, Wang R, et al. Gender-specific associations between soy and risk of hip fracture in the Singapore Chinese Health Study. Am J Epidemiol 2009 Oct 1;170(7):901-9. DOI: http://dx.doi.org/10.1093/aje/kwp220    36.    Shu XO, Zheng Y, Cai H, et al. Soy food intake and breast cancer survival. JAMA 2009 Dec 9;302(22):2437-43. DOI: http://dx.doi.org/10.1001/jama.2009.1783    37.    Yan L, Spitznagel EL. Soy consumption and prostate cancer risk in men: a revisit of a meta-analysis. Am J Clin Nutr 2009 Apr;89(4):1155-63. DOI: http://dx.doi.org/10.3945/ajcn.2008.27029    38.    Waldmann A, Koschizke JW, Leitzmann C, Hahn A. Dietary iron intake and iron status of German female vegans: results of the German vegan study. Ann Nutr Metab 2004;48(2):103-8. DOI: http://dx.doi.org/10.1159/000077045    39.    Craig WJ, Mangels AR; American Dietetic Association. Position of the American Dietetic Association: vegetarian diets. J Am Diet Assoc 2009 Jul;109(7):1266-82. DOI: http://dx.doi.org/10.1016/j.jada.2009.05.027    40.    Donaldson MS. Metabolic vitamin B12 status 1on a mostly raw vegan diet with follow-up using tablets, nutritional yeast, or probiotic supplements. Ann Nutr Metab 2000;44 (5-6):229-34. DOI: http://dx.doi.org/10.1159/000046689    41.    Dietary supplement fact sheet: vitamin B12 [monograph on the Internet]. Bethesda, MD: National Institutes of Health, Office of Dietary Supplements; 2011 Jun 24 [cited 2013 Jan 31. Available from: http://ods.od.nih.gov/factsheets/VitaminB12-HealthProfessional/.    42.    Appleby P, Roddam A, Allen N, Key T. Comparative fracture risk in vegetarians and non-vegetarians in EPIC-Oxford. Eur J Clin Nutr 2007 Dec;61(12):1400-6. DOI: http://dx.doi.org/10.1038/sj.ejcn.1602659    43.    Weaver CM, Plawecki KL. Dietary calcium: adequacy of a vegetarian diet. Am J Clin Nutr 1994 May;59(5 Suppl):1238S-1241S.    44.    Dietary supplement fact sheet: vitamin D [monograph on the Internet]. Bethesda, MD: National Institutes of Health, Office of Dietary Supplements; 2011 Jun 24 [cited 2013 Jan 31. Available from: http://ods.od.nih.gov/factsheets/VitaminD-HealthProfessional/.    45.    Rosell MS, Lloyd-Wright Z, Appleby PN, Sanders TA, Allen NE, Key TJ. Long-chain n-3 polyunsaturated fatty acids in plasma in British meat-eating, vegetarian, and vegan men. Am J Clin Nutr 2005 Aug;82(2):327-34.    46.    Davis BC, Kris-Etherton PM. Achieving optimal essential fatty acid status in vegetarians: current knowledge and practical implications. Am J Clin Nutr 2003 Sep;78(3 Suppl):640S-646S.
Supported Exercise Improves Controlled Eating and Weight through Its Effects on Psychosocial Factors: Extending a Systematic Research Program Toward Treatment Development
Wednesday, 14 March 2012
James J Annesi, PhD Winter 2012 - Volume 16 Number 1 http://dx.doi.org/10.7812/TPP/11-136 Abstract Background: Behavioral weight-loss treatments have been overwhelmingly unsuccessful. Many inadequately address both behavioral theory and extant research—especially in regard to the lack of viability of simply educating individuals on improved eating and exercise behaviors.Objective: The aim was to synthesize research on associations of changes in exercise behaviors, psychosocial factors, eating behaviors, and weight; and then conduct further direct testing to inform the development of an improved treatment approach.Methods: A systematic program of health behavior-change research based on social cognitive theory, and extensions of that theory applied to exercise and weight loss, was first reviewed. Then, to extend this research toward treatment development and application, a field-based study of obese adults was conducted. Treatments incorporated a consistent component of cognitive-behaviorally supported exercise during 26 weeks that was paired with either standard nutrition education (n = 183) or cognitive-behavioral methods for controlled eating that emphasized self-regulatory methods such as goal setting and caloric tracking, cognitive restructuring, and eating cue awareness (n = 247).Results: Both treatment conditions were associated with improved self-efficacy, self-regulation, mood, exercise, fruit and vegetable consumption, weight, and waist circumference; with improvements in self-regulation for eating, fruit and vegetable consumption, weight, and waist circumference significantly greater in the cognitive-behavioral nutrition condition. Changes in exercise- and eating-related self-efficacy and self-regulation were associated with changes in exercise and eating (R2 = 0.40 and 0.17, respectively), with mood change increasing the explanatory power to R2 = 0.43 and 0.20. Improved self-efficacy and self-regulation for exercise carried over to self-efficacy and self-regulation for controlled eating (β = 0.53 and 0.68, respectively).Conclusions: Development and longitudinal testing of a new and different approach to behavioral treatment for sustained weight loss that emphasizes exercise program-induced psychosocial changes preceding the facilitation of improved eating and weight loss should be guided by our present research. Introduction The most current data from the US government indicates that 34% of adults (77 million) are obese (body mass index [BMI] ≥ 30 kg/m2),1 causing increased propensities for Type 2 diabetes, hypertension, heart disease, and stroke as degree of overweight increases.2,3 The rate of obesity has steadily risen over the last several decades,4 with the more severe levels of obesity (BMI 40 and above) rising 3 times that of class I obesity (BMI 30 to 35 kg/m2).5 At any given time, approximately 70% of adults report trying to manage their weight.6 Weight loss of even less than 5% can result in clinically important improvements in health risks.7 Although a reduction in caloric intake and an increase in physical activity will reliably reduce excess weight, results of behavioral weight-loss treatments have, overwhelmingly, been poor.8 When significant weight is lost, with very few exceptions, it is regained in short order.8,9 A pattern of repeated weight loss and regain is associated with increased health risks,1 and makes weight loss even more difficult in the future.11, 12 Findings suggest that even the most current behavioral methods focused on reduction in caloric intake are largely inadequate,13 and innovative techniques, possibly through the use of exercise as the central component,8 should be investigated.9 On the basis of this present state-of-affairs, this article has 3 aims: 1. To review limitations in the extant research on behavioral weight-loss treatment and describe a systematic program of research that was intended to address some of those limitations2. To design and carry out a field study based on a new model suggesting a relationship between supported exercise and weight loss through psychosocial channels3. To inform construction of a treatment, based on present findings, that may be appraised for effect over the long term. Limitations of Previous Research One problem with existing treatments is that they typically fail to address methods to sustain weight loss beyond the initial weeks or months. Although research indicates that exercise is the strongest predictor of long-term success with weight loss,14-16 adherence is usually not sufficiently considered, as attrition from programs is high.17,18 In many cases, the inclusion of physical activity is either deferred or minimized because it is feared that participants’ self-regulation for maintaining an exercise program may dilute their self-regulatory resources for managing their eating.19This is understandable because research has suggested self-regulation to be a limited resource that is subject to depletion.20 Minimal caloric expenditures possible from deconditioned and obese participants21,22 may also lessen the perceived importance of exercise because of its minimal direct impact on weight. Although a “clustering” of improvements in exercise and eating behaviors has been suggested, explanatory mechanisms that may lead to intervention development has been lacking, and cited as a limitation.23-25Integration of accepted behavioral theory into weight-loss treatment has been sporadic.26 Treatments often are based on the assumption that providing education in desired behaviors and their beneficial outcomes will alone be sufficient to induce a reduction in caloric consumption and, possibly, an increase in physical activity. This is inconsistent with most theories of behavioral change as well as the realization that, although most adults absolutely know the value of exercise, healthy eating, and an appropriate weight,27,28 less than 4% of adults in North America complete recommended minimum amounts of physical activity,29-31 most consume well in excess of their caloric needs,32and approximately two-thirds are now at an unhealthy weight.1 Interventions that claim a theoretical basis generally have been influenced by established behavioral models in only broad and general terms.33 Relations of specific psychological variables associated with changes in exercise, eating, and weight loss have not been sufficiently tested in a manner that could easily be translated into practical treatments. Possibly, this is because researchers typically test a proposed set of relationships emanating from a nuanced adaptation of theory that is of interest to them, report on its strengths, weakness, and needs for replication and extension, and move on.34 Further compromising matters is that specific treatment techniques used have not typically been annotated through a standard taxonomy that could facilitate comparative evaluation of efficacy—especially through their relationship with theory.35 Thus, conclusions do not often go beyond whether a set of findings might hold promise for predicting or explaining exercise and weight-loss phenomena in future research. There has been minimal concern for systematically evolving their line of inquiry in a manner where treatment, as well as theory, may simultaneously benefit. Albert Bandura referred to this as a paradigm’s, “… operative power to guide psychosocial change.”36p248 This is problematic because practitioners are bound by practical constraints when attempting to translate abstract findings into day-to-day use, whereas researchers may have little concern for advancing treatments in real-life settings. What remains is a preponderance of intuitively based treatments, and concerns from the academicians that such treatments are not sufficiently guided by theory and rigorous research.37 Systematically Progressing Since 2000, I, along with a team from varied disciplines from the YMCA of Metropolitan Atlanta, have attempted to address some of the above-stated limitations. Within our research program, the relations of exercise with psychosocial changes and changes in eating behaviors and weight have been evaluated in a systematic manner while maintaining a focus on the practical application of findings. Out of heuristic necessity, issues such as adherence to exercise, exercise and mood change, and effects of exercise on weight loss through psychosocial channels were sequentially addressed. Incorporating recent suggestions,38,39 much of the research was, accordingly, completed in practical settings. Our research produced a structured exercise support protocol entitled The Coach Approach,16,40-42 incorporating an array of self-regulatory methods (eg, self-talk, relapse prevention) where manipulation of variables based on social cognitive theory (a theory viewing individuals as directing their own behaviors through self-reflection and self-organization43-44) and self-efficacy theory (a theory viewing behaviors as being directed by individuals’ feelings of ability45) (eg, physical self-concept, barriers self-efficacy46) were used to reliably and meaningfully increase adherence to exercise in obese and formerly sedentary adults by an average of 52% over 53 trials.47 Consistent with previous research,48 mood also improved and was, additionally, found to be associated with adherence.47,49,50 Because the research clearly and strongly relates exercise to success with sustained weight loss,51 we judged this adherence component to be an essential initial step in a progression toward development of effective weight-management treatment. Nutrition components, which were also included in much of the research, incorporated traditional educationally based approaches. This allowed us to probe for and identify salient relationships among psychosocial variables, associated with behaviorally supported exercise, which might ultimately lead to an effective and reliable intervention. Thus, through the use of an overarching framework of social cognitive and self-efficacy theory,43,44 our program of research progressively built upon findings, suggesting the following: 1. There is empirical strength in the basic social cognitive model proposed in 2000 by Baker and Brownell (Figure 1),52 particularly as in the contribution of exercise program-induced changes in mood, body image, self-efficacy, and coping leading to increased physical activity, improved eating, and weight loss.47,50,53-582. Self-efficacy and self-regulation for both exercise and controlled (well-managed) eating are distinct59 and essential constructs in the prediction of physical activity and eating changes, and weight loss.60-643. There are significant effects of exercise-induced mood change on weight loss and psychosocial predictors of weight loss55,64-69—especially in the effect that mood change has in enhancing and/or undermining self-efficacy and self-regulation (such as with emotional eating [emotion-triggered eating]).62,704. There is a carry-over effect from improvements in self-efficacy and self-regulation for exercise to self-efficacy and self-regulation for controlled eating,60,64,70 which is consistent with recent research on women from Portugal,71,72 Finland,73 and Baker and Brownell’s model.52 The strong positive relationship between changes in self-regulation for exercise and self-regulation for eating60,64,70-72 was especially noteworthy because laboratory research suggested, quite definitively, that self-regulation for exercise would deplete self-regulation for eating when these behaviors are attempted in close temporal proximity (viewing self-regulation as a limited resource that is readily depleted).19,74 Rather, consistent with the “training hypothesis” of self-regulation (viewing self-regulation as potentially improving with practice),75,76 it was recently indicated that when self-regulatory skills were taught in first exercise, then eating, contexts (rather than drawn from participants’ innate abilities as had been the case in most of the previous research), a strengthening of the skills for controlled eating occurred.60,64 As previously suggested, improvements in self-efficacy for exercise appeared to carry over to improvements in controlled eating because of a generalization of feelings of ability to manage an array of behaviors consistent with weight control.52 Findings also suggested that increased satisfaction with the physical self (which was associated with persistence with exercise more than actual physiological changes77-81) and self-regulatory skill usage82 are associated with maintained weight loss. These findings are consistent with studies suggesting the positive effects of self-regulation on improved eating (ie, fruit and vegetable consumption) and on weight loss sustained at two-year follow-ups,83,84 and hypothesized that feelings of accomplishment (ie, self-efficacy) fostered persistence. Additionally, findings indicated that a significant improvement in mood requires a minimum of only about 2 sessions of moderate exercise per week,85,86 with no dose-response effect (ie, more exercise was not associated with greater change in mood),87,88 rather than the “public health dose” of at least 5 sessions per week (ie, 17.5 kcal/kg/week, or approximately 150 minutes per week) previously suggested.89 Moreover, it was determined that exercise durations and intensities could be purposefully adjusted to induce acute improvements in post-exercise feeling states (eg, increased revitalization; decreased physical exhaustion) that are consistent with both long-term mood improvements46,90,91 and, of key importance, adherence to exercise through their reinforcement effects.47,92-94 Although the indirect relationship between exercise program participation and weight loss was strong,50,58,62 less than 15% of the weight loss, across studies, was attributable to caloric expenditures associated with exercise. This further supported the contention that the association of exercise program participation with weight loss in obese and deconditioned individuals is associated more with changes in psychosocial variables than direct caloric expenditure. Through this research program, important proposed relationships were suggested and are presented graphically in Figure 2. Assessing Propositions Within a New Model Intervention researchers have long been underinformed about the specific function that exercise plays in weight loss and, more specifically, how exercise-related changes in mood, self-efficacy, and self-regulation may affect controlled eating. After review and consolidation of our stream of findings, specific relationships emerged as important for treatment-based testing. Thus, for the present study, we incorporated conditions of: 1) The Coach Approach exercise adherence protocol coupled with nutrition education, and 2) The Coach Approach protocol coupled with a cognitive-behavioral approach to reducing caloric intake that complemented the behavioral methods already being employed within the exercise context.a This facilitated a contrast of treatment effects and allowed testing of proposed relationships among variables. Severely obese adults were selected for testing to allow investigation with a difficult population, but one in great need. Hypothesized Findings Consistent with both theory and the synthesis of previous findings, pairing The Coach Approach with the proposed cognitive-behavioral approach to reducing calories was expected to demonstrate significantly greater improvements in self-regulation and self-efficacy for controlled eating, food consumption, and weight, than The Coach Approach paired with traditional nutrition education. In terms of relationships of variables identified for testing, improvements in domain-specific feelings of ability to overcome perceived barriers (ie, self-efficacy) and use of behavioral skills to overcome barriers (ie, self-regulatory skill usage) were expected to significantly predict improvements in both exercise and eating behaviors. Changes in mood were expected to strengthen these relationships (eg, mood changes would increase the explanatory power of self-efficacy and self-regulation). Improvements in both self-efficacy and self-regulatory skill use for exercise were expected to predict improved self-efficacy and self-regulation for controlled eating. It also was expected that improvements in mood would be associated with a minimum of 2 exercise sessions per week, and a greater frequency would not be associated with greater improvement. Additionally, it was anticipated that change in mood would be more strongly associated with change in self-efficacy to control emotional eating than with other dimensions of self-efficacy for controlled eating, and that a very small portion of the observed weight loss (<15%) would be directly attributable to caloric expenditure associated with exercise. Study Methods Participants    Men and women responded to advertisements in local newspapers soliciting volunteers for research incorporating physical activity and nutrition instruction for weight loss. Inclusion criteria were: 1) minimum age of 21 years, 2) BMI ≥ 35 kg/m2, 3) no regular exercise within the previous year (less than 20 minutes per week on average), and 4) a goal of weight loss. Exclusion criteria were current or soon-planned pregnancy and/or taking medications prescribed for weight loss or a psychological or psychiatric condition. A wellness specialist assessed BMI in a private office before participants were accepted into the study. A written statement of adequate physical health to participate was required from a physician. Appropriate institutional review board approval and written consent from all participants was obtained. There was no significant difference in proportion of women (overall 82.6%), age (overall mean = 42.5 years, standard deviation [SD] = 10.0), BMI (overall mean = 41.7 kg/m2, SD = 6.5), and racial make-up (overall 45% White, 51% African American, and 4% of other racial/ethnic groups) between participants randomly assigned to a treatment of The Coach Approach plus standard nutrition education (Nutrition Education group; n = 183) and The Coach Approach plus a version of cognitive-behavioral methods applied to caloric reduction (Cognitive-Behavioral Nutrition group; n = 247). The socioeconomic strata of most participants (90%) were classified as middle class. Within the Nutrition Education condition, some individuals might have been exposed to unplanned nutritional lectures and support within 1 of the 6 study facilities. Thus, their data were omitted, which explains the difference in group sample sizes. Exploratory analyses indicated that the omitted individuals did not significantly differ from the overall pool of participants on any personal characteristic or baseline measure. Measures Self-efficacy Self-efficacy for exercise (perceived ability to overcome barriers to completing exercise) was measured by the Exercise Self-Efficacy Scale.95 It requires responses to 5 items that begin with the stem, “I am confident I can participate in regular exercise when:” (eg, “I am tired,” “I have more enjoyable things to do”), ranging from 1 (not at all confident) to 7 (very confident). Internal consistencies were reported to range from 0.76 to 0.82, and test-retest reliability over 2 weeks was 0.90.96 Self-efficacy for controlled eating (perceived ability to overcome barriers to managing one’s eating) was measured by the Weight Efficacy Lifestyle Questionnaire.97 It is made up of 5 subscales of 4 items each, derived from factor analysis, that are Negative Emotions (eg, “I can resist eating when I am depressed [or down”), Social Pressure (eg, “I can resist eating even when others are pressuring me to eat”), Availability (eg, “I can resist eating even when high-calorie foods are available”), Physical Discomfort (eg, “I can resist eating when I feel uncomfortable”), and Positive Activities (eg, “I can resist eating when I am watching TV”). Responses range from 0 (not at all confident) to 9 (very confident). Individual subscale responses are summed for a total score. Internal consistencies were reported to range from 0.70 to 0.90.97 The predictive validity of the Weight Efficacy Lifestyle Questionnaire for weight loss has been supported in multiple studies.98 Self-regulation Self-regulation for exercise and self-regulation for eating were separately measured by modified versions of a scale where items are based on intervention content.99 An example of a self-regulation for exercise item for the present study was, “I set physical activity goals.” An example of a self-regulation for eating item was, “I say positive things to myself about eating well.” Following the taxonomy by Abraham and Michie,35 items measured self-regulatory skills related to intention formation, barrier identification, specific goal setting, review of behavioral goals, self-monitoring of behavior, feedback on performance, self-talk, relapse prevention, and time management. Each scale required responses to 10 items ranging from 1 (never) to 5 (often). In a previous version, internal consistency (0.75), test-retest reliability over 2 weeks (0.77), and predictive validity were supported.100 Construct validity was indicated because the measure partially mediated the relationship between self-efficacy and physical activity.100 In separate testing of the present versions, the internal consistency of the self-regulation for physical activity scale was 0.79, and the test-retest reliability over 2 weeks was 0.78.64 For self-regulation for eating, the internal consistency was 0.81, and test-retest reliability was 0.74.64 Mood Mood was measured by Total Mood Disturbance—an aggregate measure of the Profile of Mood States Short Form scales of Tension (eg, anxious), Depression (eg, sad), Fatigue (eg, weary), Confusion (eg, bewildered), Anger (eg, annoyed), and Vigor (eg, energetic) (5 items for each of the 6 subscales).101 Respondents rate feelings over the past week ranging from 0 (not at all) to 4 (extremely). Internal consistency for the subscales was reported to range from 0.84 to 0.95, and test-retest reliability at 3 weeks averaged 0.69.101 Concurrent validity was suggested through contrasts with accepted measures such as the Beck Depression Inventory, Manifest Anxiety Scale, and Minnesota Multiphasic Personality Inventory.101 Exercise Volume of exercise was measured by the Godin Leisure-Time Exercise Questionnaire.102 It required entry of weekly frequencies of strenuous (“heart beats rapidly”) (eg, running, basketball, vigorous swimming), moderate (“not exhausting”) (eg, fast walking, easy bicycling), and light (“minimal effort”) (eg, easy walking, yoga) exercise for “more than 15 minutes” per session. These responses are multiplied by 9, 5, and 3 standard metabolic equivalents (METs), respectively, and then summed. For adults, test-retest reliability over 2 weeks was reported to be 0.74.102 Construct validity was supported by significant correlations of scores with accelerometer and VO2max measurements of exercise volume.103,104 Using this measure for an individual of 115 kg, a score of 10 and 20 would indicate an approximate weekly expenditure from exercise of 450 and 900 calories, respectively. Food Consumption A survey recalling the number of servings of fruits and the number of servings of vegetables consumed “in a typical day” (“looking back over the last month”), based on the US Food Guide Pyramid and its descriptions of foods and portion sizes, was used. The quantity of fruit and vegetable servings reported consumed was summed. Research suggests the adequacy of this measure for both its responsiveness in the context of the present nutrition treatments and to minimize participant burden.105 Test-retest reliability over 2 weeks averaged 0.82, and concurrent validity was suggested through significant correlations with longer, more invasive, food frequency questionnaires.106 Pilot research suggested that the participant burden with administration of a full food frequency questionnaire (sometimes requiring approximately 60 minutes to complete), along with the aforementioned surveys within this investigation, would compromise respondents’ attention and degrade the validity of responses. Thus, because research suggests that fruit and vegetable consumption, alone, is a good predictor of overall caloric consumption,107,108 the present measure was selected. Weight and Waist Circumference A recently calibrated digital scale was used to measure weight (kg), and a tape measure was used to measure waist circumference (cm) at the umbilicus. Although used less frequently than weight, recent research suggests waist circumference to be a superior measure for the prediction of health risks.109,110 Procedure Each participant reported to a YMCA, received an orientation to study processes associated with his or her group, and was provided full access to the facility for the duration of the investigation. Exercise Support Component The exercise adherence support component was identical in both the Nutrition Education and Cognitive-Behavioral Nutrition groups. It consisted of a standard protocol (ie, The Coach Approach) of 6 one-hour meetings with a trained wellness specialist, spaced across 26 weeks and supported by a computer program.17,47 These one-on-one sessions included an orientation to exercise apparatus and facilities, but most time was spent within an office setting on an array of cognitive-behavioral methods intended to foster adherence. Following recent suggestions,111,112 long-term goals were identified, documented, and broken down into process-oriented short-term goals where ongoing progress was tracked graphically. Instruction in additional self-regulatory skills such as restructuring unproductive thoughts, addressing cues to exercise, and preparedness for occurrences of barriers to exercise and “slips” in one’s exercise routine (ie, relapse prevention113) was given during the sessions. A summary of each self-regulatory skill also was provided for participants’ ongoing reference. In order that behavioral treatments may be accurately contrasted with others, Abraham and Michie35 recommended a standardized description of their components. According to their taxonomy of behavior change techniques,35 the following methods were included within The Coach Approach sessions according to a clearly defined protocol: 1) provision of information on consequences, 2) prompting intention formation, 3) prompting barrier identification, 4) provision of encouragement, 5) setting graded tasks, 6) provision of instruction in desired behaviors, 7) prompting specific goal setting, 8) prompting review of behavioral goals, 9) prompting self-monitoring of behavior, 10) provision of feedback on performance, 11) teaching the use of prompts or cues, 12) establishment of a behavioral contract, 13) facilitating social supports, 14) prompting self-talk, 15) teaching relapse prevention, 16) addressing stress management, and 17) facilitating time management methods. Specific modalities used in exercise plans (eg, walking or stationary cycling) were based on each participant’s preference. Cardiovascular exercise progressed from a minimum of 20 minutes at a moderately light to moderately hard intensity according to the Rate of Perceived Exertion scale,114 which was explained to participants. Exercise sessions could be completed inside or outside of the YMCA facilities. Widely used recommendations for volume of weekly exercise (ie, 150 minutes of moderate aerobic physical activity115) were described, but it was also suggested that any volume of exercise may be beneficial. Nutrition Components The nutrition component of the treatments varied by group. In the Nutrition Education group, a standardized nutrition education protocol116 of 6 one-hour sessions was administered over 3 months. These sessions, however, began between 4 and 6 weeks after initiating The Coach Approach exercise support protocol. They were led by a certified wellness specialist in a group format. Examples of program components were: understanding carbohydrates, protein, fats, and calories; using the US Food Guide Pyramid; menu planning; and developing a plan for snacking. An emphasis was placed on participants understanding healthy eating. Treatment techniques, based on Abraham and Michie’s taxonomy,35 included: 1) provision of information on consequences, and 2) general encouragement. The Cognitive-Behavioral Nutrition group had the identical format for meeting times and length as the Nutrition Education group, but components substantially differed. They also followed a standardized protocol. It included: establishing caloric goals and logging daily food and calorie intake, regular self-weighing, cognitive restructuring, relapse prevention training, understanding cues to overeating, and relaxation strategies. An emphasis was placed on increasing participants’ self-regulatory skills that could be used to manage their eating. Following Abraham and Michie’s taxonomy,35 with the exception of establishment of a behavioral contract (which was not used), the same array of behavior change techniques used in The Coach Approach exercise support component was incorporated here. In both treatment conditions, increasing intake of fruits and vegetables was emphasized. No participant was in both treatment groups. Wellness specialists were trained in the protocols (with no overlap between those instructing the educational or cognitive-behavioral nutrition components), and were blind to the purposes of the investigation. Fidelity of treatment protocols was assessed by trained staff and, if deviations occurred, corrective measures were immediately taken by YMCA supervisors in cooperation with study administrators. Assessments were administered in a private area at baseline, week 13, and week 26 by Master’s level health educators. Data Analyses An intention-to-treat design was incorporated. Thus, data from all participants initiating treatment were retained, regardless of their compliance. To account for missing data, multiple imputation117 was used. This method is favorable because it effectively represents uncertainty in missing values.118 Results were, however, nearly identical to the more straightforward method of last-observation-carried forward, often used in research on weight loss.72,119 Data from week 13 were used to improve imputation, where applicable. Consistent with related research24 and recent suggestions,120 change scores were the unadjusted difference between scores from baseline and scores from week 26. Statistical significance was set at α = 0.05 (2-tailed). Initially, a series of mixed-model repeated measures analysis of variances (ANOVAs) were conducted. This statistical method simultaneously assesses both within- and between-group differences. Thus, the statistical significance of within-group changes in Exercise Self-Efficacy, self-regulation for exercise, Weight Efficacy Lifestyle (self-efficacy for controlled eating), self-regulation for controlled eating, Total Mood Disturbance, exercise, fruit and vegetable consumption, weight, and waist circumference scores occurring over the 26 weeks was assessed; while also determining whether there were significant differences in those changes between the Nutrition Education and Cognitive-Behavioral Nutrition groups. Next, to assess the viability of proposed relationships among study variables, data from both treatment conditions were aggregated (because the relationships proposed were not specific to a particular treatment condition). Two hierarchical multiple regression analyses were conducted that assessed the ability of changes in self-regulation, self-efficacy, and mood to predict exercise and eating changes. In the first regression equation, the first block of analyses assessed the variance in change in volume of exercise accounted for through simultaneous entry of Exercise Self-Efficacy and self-regulation for exercise changes. In the second regression equation, the first block assessed the variance in change in fruit and vegetable consumption accounted for through simultaneous entry of Weight Efficacy Lifestyle and self-regulation for controlled eating changes. Change in Total Mood Disturbance was subsequently entered as an additional predictor in both of the regression equations. Bivariate regression analyses then assessed the ability of change in Exercise Self-Efficacy to predict Weight Efficacy Lifestyle change, and the ability of change in self-regulation for exercise to predict self-regulation for controlled eating change. Finally, the amount of the variance in weight and waist circumference change explained by exercise and fruit and vegetable consumption change was assessed through multiple regression. Consistent with previous research,17,86 a one-way ANOVA was used to test whether there was a significant difference in Total Mood Disturbance change whether a mean of 0 to 1.9, 2.0 to 3.9, or 4.0 to 7.0 days of moderate exercise per week was completed. These time frames were derived from aforementioned research assessing minimal exercise volumes required for significant mood changes to occur.17,86,89 Also, correlational analysis was used to test whether Total Mood Disturbance change was related to change in the Negative Emotions subscale of the Weight Efficacy Lifestyle Questionnaire (ie, self-efficacy to control emotional eating) scores more strongly than scores on the other 4 subscales of that survey. Consistent with previous research,63 METs, derived from the Godin measure of exercise,102 were converted to energy expenditures to estimate the percentage of weight loss associated with exercise over the course of the investigation using a recently validated formula.121 All analyses were conducted using SPSS software, version 15.0 (SPSS, Chicago, IL). Results Attendance in exercise support (overall mean = 4.2, SD = 0.9 [70%]) and nutrition treatment (overall mean = 4.1, SD = 1.0 [68%]) sessions did not significantly differ by group. There also was no significant difference in any baseline score between participants in the Nutrition Education and Cognitive-Behavioral Nutrition groups. There was no group difference in participants completing the 26-week investigation (overall 76%). Significant overall changes were found during 26 weeks in all measures (p < 0.001). Descriptive statistics and within-group changes derived from follow-up dependent t-tests are reported in Table 1. Improvements were significantly greater for the Cognitive-Behavioral Nutrition group in self-regulation for controlled eating, F(1, 428) = 5.83,p = 0.02, η2p = 0.013; fruit and vegetable consumption, F(1, 428) = 8.80, p = 0.003, η2p = 0.020; weight, F(1, 428) = 5.15, p = 0.02, η2p = 0.012; and waist circumference, F(1, 428) = 7.47, p = 0.007, η2p = 0.017 (Table 1, with significant differences annotated by different superscripts between groups on the same measure). In the Nutrition Education group, 40 (21.9%) participants lost at least 5% of their original body weight, and 9 (4.9%) lost at least 10%. In the Cognitive-Behavioral Nutrition group, 83 (33.6%) participants lost at least 5% of their original weight and 21 (8.5%) lost at least 10%. Changes in Exercise Self-Efficacy and self-regulation for exercise significantly predicted change in exercise volume (Table 2). Changes in Weight Efficacy Lifestyle and self-regulation for eating significantly predicted change in fruit and vegetable consumption (Table 2). Entry of Total Mood Disturbance change significantly improved the explained variances in both equations (Table 2). Change in Exercise Self-Efficacy significantly predicted Weight Efficacy Lifestyle change, β = 0.53, SE = 0.13, p < 0.001, and change in self-regulation for exercise significantly predicted self-regulation for controlled eating change, β = 0.68, SE = 0.03, p < 0.001. Changes in volume of exercise and fruit and vegetable consumption explained a significant portion of the variance in changes in weight, R2 = 0.28, F(2, 427) = 81.56, p < 0.001, and waist circumference, R2 = 0.28, F(2, 427) = 83.66, p < 0.001, with changes in both predictors significantly contributing, uniquely, to the variances explained, βs = -0.43 (SE = 0.01) and -0.19 (SE = 0.14), and -0.45 (SE = 0.02) and -0.17 (SE = 0.17), respectively, all p values <0.001. Change in Total Mood Disturbance significantly differed at exercise frequencies of 0 to 1.9 days (n = 194; mean = -2.62, SD = 9.97), 2.0 to 3.9 days (n = 129; mean = -14.47, SD = 17.16), and 4.0 to 7.0 days (n = 107; mean = -16.48, SD = 14.45) per week, F(2, 427) = 47.50, p < 0.001, η2 = 0.182. A Bonferroni follow-up test indicated that the participants completing 2.0 to 3.9 and 4.0 to 7.0 days per week of exercise demonstrated significantly greater reduction in Total Mood Disturbance than those completing 0 to 1.9 days, but they did not significantly differ from one another. The correlation between Total Mood Disturbance change and change in the Negative Emotion subscale was significant, r = -0.31, p < 0.001, and stronger than those of the other 4 subscales of the Weight Efficacy Lifestyle Questionnaire. Only 12.9% of the observed weight loss was accounted for through exercise completed over the course of the investigation. Discussion Consolidation of Findings Initially, a description of the problem of treating obesity with standard methods, and a review of a research program suggesting an alternate treatment route was given. An experimental research design was then established on the basis of a review of theory and our previous findings of interrelations of exercise, psychosocial changes, improved eating, and weight loss. After addressing exercise adherence concerns through the use of The Coach Approach protocol in both treatment conditions, findings indicated that an exercise and nutrition treatment focused on self-regulatory skills was associated with significantly more weight loss and reduction in waist circumference during 26 weeks than a treatment where the nutrition component was educationally based (as is the typical practice). Also consistent with expectations, changes in self-regulatory skill usage and self-efficacy were significantly related to both increased exercise and improved eating, with exercise-induced mood change significantly adding to the explained variances in improvements. It was confirmed that only 2 sessions per week of moderate exercise was sufficient to improve overall mood, with a higher volume unrelated to greater improvement. Also as expected, increased use of self-regulatory skills for exercise predicted greater use of self-regulation for controlled eating, and improvements in self-efficacy for exercise predicted greater changes in self-efficacy to control one’s eating. Although the average loss in weight in the Cognitive-Behavioral Nutrition group was a modest 3.6 kg (just over 3% of initial weight), it should be noted that the conservative intention-to-treat design used in this study included data from all individuals initiating treatment—including early drop-outs and those with very poor treatment attendance. Thus, its improvement over the Nutrition Education group (a group still receiving considerable treatment) of 30% is noteworthy. That being said, because of the improved understanding of salient psychosocial predictors of weight change, important treatment components should be carefully scrutinized for improved effect in the future. For example, findings indicated that improvement in self-efficacy for controlled eating was not significantly different between treatment conditions. Because of the present findings on the association of self-efficacy and exercise and eating improvement, more attention to this is warranted in the future. It is also not known if the considerable mood changes associated with even minimal volumes of exercise may be specifically channeled to address emotion-triggered overeating; and, if so, how this may further improve effects. Thus, it is likely that a considerably longer time frame for the nutrition component will be required to attend to these issues. Results overwhelmingly supported relationships depicted in the proposed model (Figure 2), and extended previous research on the positive effects of self-regulation on exercise and eating,122-124 and carry-over effects from self-regulating for exercise to self-regulating for controlled eating.23,71,76 Although the positive effects of increased self-efficacy on exercise and appropriate eating behaviors were previously indicated,125,126 their interrelationship was only recently suggested,72,73 as was the effect of improved mood on, “… a healthier psychological climate in which individuals have more cognitive and emotional resources, as well as motivation and energy, to sustain a long-term commitment to a weight-loss program.”52p320 Our own research program50,53-56,58,60,62-66,69,70,81,82 was also extended in a manner that may now guide the development of an original intervention that is substantially different from those previously tested; one in which physical exercise supported by methods emphasizing self-regulation, self-efficacy, and mood change is central to reliably improving eating behavior through a psychosocial pathway. A Look Forward A key to meaningfully improving lagging weight-loss treatment outcomes is by reviewing past research failures and successes, better understanding relationships among psychosocial predictors of weight loss, and implementing a plan for extension of research toward applied ends. Only then might the consideration of previous theories, models, and results have true practical value. The experimental literature is abundantly clear that failures in the behavioral treatment of obesity predominate,8 and suggest that nutrition education, severe reductions in calories (“diets”), and cognitive-behavioral techniques primarily targeting reduced intake of food, are insufficient, and will, overwhelmingly, result in rapid regain of any short-term weight loss. Even the arguably most “state-of-the-art” behavioral treatment failed to sustain weight loss when its concentration was fundamentally on extreme caloric intake change.13,19 What remains is knowledge of what, apparently, will not work, enhanced data concerning relationships among psychosocial variables within a context of exercise supported by cognitive-behavioral means, and a need for innovation related to the development of a successful intervention based on this knowledge.9 Thus, rather than acquiesce to recent pessimistic suggestions (precipitated by the routine failures in treatments) that, “… psychosocial research should perhaps shift away from work on treatment [of obesity] …,”9p710 it is proposed that sufficiently different methods with new and different emphases grounded in the emerging findings require development and sufficient testing. Because there is considerable research suggesting that participation in regular exercise is a robust predictor of maintained weight loss (but not directly reconciled through associated caloric expenditure) and, on the basis of the present results indicating that exercise affects weight loss through associations with psychosocial predictors of controlled eating, cognitive-behaviorally supported exercise as possibly the central component of the architecture of an effective weight-loss treatment is indicated. Specifically, a treatment emphasizing: 1) attention to adherence to an exercise program, 2) participants’ assimilation of new and enhanced self-regulatory skills through exercise both before and throughout their application to managed eating, 3) feelings of competence around progressive health behavior changes, and 4) an enhanced psychological profile exemplified by exercise-induced improvements in overall mood is suggested. Thus, self-regulatory abilities, self-efficacy, and improved mood, nurtured through a focused exercise-support component paired with a similar component for support of controlled eating, may help attain improvements well beyond that of the array of treatment approaches presently available. For example: 1) self-efficacy may be advanced through simultaneous emphases on short-term goal attainment in both the exercise (eg, increase walking for exercise from 60 to 90 minutes per week within 1 month) and eating (eg, increase fruit and vegetable consumption from 3 to 6 servings daily within 6 weeks) domains, 2) self-regulatory skills may be nurtured by presenting them in a similar manner in both the context of supporting regular exercise and controlling one’s eating (eg, practice in cognitive restructuring to overcome a desire to lapse in exercise when increased stress is present may serve to support modifying unproductive thoughts when preparing to use food to manage anxiety), and 3) in efforts to keep exercise manageable to maximize adherence, the minimum volume identified as consistent with mood improvements (ie, 2 sessions per week of moderate intensity) may be suggested rather than much higher dosages (that are most commonly prescribed to expedite weight loss, but few individuals are able to maintain). Although considerable testing will be required—especially with follow-ups of at least several years—methods applied to such a newly focused intervention would exemplify innovation, use of the most current evidence, and address suggestions that, “… future research focus on exercise as a treatment for obesity.”8p230 Limitations Although substantial progress was made within this research on consolidating theory-based psychosocial relationships concerning exercise, managed eating, and weight loss, there were limitations that should be addressed. Additional variables within social cognitive theory (eg, observational learning and social support) may be useful for furthering the prediction of weight loss. Although partially justified through preliminary propositions (Figure 1),52 earlier research,62,64 and the present experimental design in which self-regulation skills were first developed within an exercise context (ie, 4 to 6 weeks before the onset of the respective nutritional component), the directionality of the relationships (eg, between exercise- and eating-related self-regulation and self-efficacy) requires additional investigation. Additionally, field studies, as described here, have limited experimental controls such as through perceived instructor expectations and external social supports. Although field settings benefit the ability to readily apply findings to practice,39 replication is required before it is appropriate to generalize results to specific groups such as nonvolunteers (eg, individuals whose physicians have insisted on their immediate participation in a weight-management treatment), individuals affected by certain physical (eg, diabetes, cancer) or psychiatric/psychological (eg, depression) pathologies, and those with a lower degree of overweight. Confirmatory analyses should carefully assess the validity of the proposed model across such disparate groups. Conclusion The present review of theory and previous findings, including summarization of a systematic research program on the relationship of supported exercise with psychosocial correlates of controlled eating and weight loss, was extended here to include direct testing of differing nutrition treatment components and a refined set of behavioral predictors. As a result, it now appears prudent to construct and test an original weight-loss protocol emphasizing maintained exercise and development of self-regulation and self-efficacy for both exercise and controlled eating. Additionally, findings suggest that effects of mood change associated with even minimal volumes of exercise can further improve behaviors—especially emotional eating. It is hoped that this review, field experiment, consolidation of findings, and suggestions for future research and practice provides an enhanced understanding of the role that cognitive-behaviorally supported exercise plays in controlled eating and, ultimately, facilitates greatly improved treatment results that may be widely disseminated. It is incumbent on the fields of behavioral and medical science to collaborate in a quest for more effective methods to successfully intervene with the growing epidemic of obesity through continued extension of the existing knowledge base. a     A cognitive-behavioral treatment approach relates to a family of methods in which the purposeful changing of thoughts and perceptions are used to shape behaviors useful to the individual being cared for. Disclosure Statement The author(s) have no conflicts of interest to disclose. Acknowledgments The author acknowledges the interdisciplinary team at the YMCA of Metropolitan Atlanta that facilitated much of the research synthesized in this article, including: Ed Munster, Dan Pile, Scott Doll, Betsy Lenahan, Kristin McEwen, Robyn Furness-Fallin, Alice Smith, Jennifer Unruh Rewkowski, Linda Vaughn, and Elizabeth Kelly, as well as the funding agencies that made the work possible. References 1.    Flegal KM, Carroll MD, Ogden CL, Curtin LR. Prevalence and trends in obesity among US adults, 1999-2008. JAMA 2010 Jan 20;303(3):235-41.2.    Arkin JM, Alsdorf R, Bigornia S, et al. Relations of cumulative weight burden to vascular endothelial dysfunction in obesity. Am J Cardiol 2008 Jan 1;101(1):98-101.3.    Aronne LJ. Classification of obesity and assessment of obesity-related health risks. Obes Res 2002 Dec;10 Suppl 2:105S-15S.4.    National Center for Health Statistics. Health, United States, 2006, with chartbook on trends in the health of Americans. Hyattsville, MD: National Center for Health Statistics; 20065.    Sturm R. Increases in morbid obesity in the USA: 2000-2005. Public Health 2007 Jul;121(7):492-6.6.    Serdula MK, Mokdad AH, Williamson DF, Galuska DA, Mendlein JM, Heath GW. Prevalence of attempting weight loss and strategies for controlling weight. JAMA 1999 Oct;282(14):1353-8.7.    Flechtner-Mors M, Ditschuneit HH, Johnson TD, Suchard MA, Adler G. Metabolic and weight loss effects of long-term dietary intervention in obese patients: four-year results. Obes Res 2000 Aug;8(5):399-402.8.    Mann T, Tomiyama AJ, Westling E, Lew AM, Samuels B, Chatman J. Medicare’s search for effective obesity treatments: diets are not the answer. Am Psychol 2007 Apr;62(3):220-33.9.    Jeffery RW, Drewnowski A, Epstein LH, et al. Long-term maintenance of weight loss: current status. Health Psychol 2000 Jan;19(1 Suppl):5-16.10.    Amigo I, Fernández C. Effects of diets and their role in weight control. Psychol Health Med 2007 May;12(3):321-7.11.    Brownell KD, Rodin J. The dieting maelstrom. Is it possible and advisable to lose weight? Am Psychol 1994 Sep;49(9):781-91.12.    Kroke A, Liese AD, Schulz M, et al. Recent weight changes and weight cycling as predictors of subsequent two year weight change in a middle-aged cohort. Int J Obes Relat Metab Disord 2002 Mar;26(3):403-6.13.    Cooper Z, Doll HA, Hawker DM, et al. Testing a new cognitive behavioural treatment for obesity: a randomized controlled trial with three-year follow-up. Behav Res Ther 2010 Aug;48(8):706-13.14.    Fogelholm M, Kukkomen-Harjula, K. Does physical activity prevent weight gain—a systematic review. Obes Rev 2000 Oct;1(2):95-111.15.    Clinical guidelines on the identification, evaluation, and treatment of overweight and obesity in adults—the evidence report. National Institutes of Health. Obes Res 1998 Sep;6 Suppl 2:51S-209S. Erratum in: Obes Res 1998 Nov;6(6):464.16.    Svetkey LP, Stevens VJ, Brantley PJ, et al; Weight Loss Maintenance Collaborative Research Group. Comparison of strategies for sustaining weight loss: the weight loss maintenance randomized controlled trial. JAMA 2008 Mar;299(10):1139-48.17.    Annesi JJ. Effects of a cognitive behavioral treatment package on exercise attendance and drop out in fitness centers. European Journal of Sport Science 2003;3(2):1-12.18.    Buckworth J, Dishman RK. Exercise psychology. Champaign, IL: Human Kinetics; 2002.19.    Cooper Z, Fairburn CG, Hawker DM. Cognitive-behavioral treatment of obesity: a clinician’s guide. New York: Guilford; 2003.20.    Hagger MS, Wood C, Stiff C, Chatzisarantis NL. Ego depletion and the strength model of self-control: a meta-analysis. Psychol Bull 2010 Jul;136(4):495-525.21.    American College of Sports Medicine Position Stand. Appropriate physical activity intervention strategies for weight loss and prevention of weight regain for adults. Med Sci Sports Exerc 2009 Feb;41(2):459-71. Erratum in: Med Sci Sports Exerc 2009 Jul;41(7):1532.22.    Garrow JS, Summerbell CD. Meta-analysis: effect of exercise, with or without dieting, on the body composition of overweight subjects. Eur J Clin Nutr 1995 Jan;49(1):1-10.23.    Andrade AM, Coutinho SR, Silva MN, et al. The effect of physical activity on weight loss is mediated by eating self-regulation. Patient Educ Couns 2010 Jun;79(3):320-6.24.    Jakicic JM, Wing RR, Winters-Hart C. Relationship of physical activity to eating behaviors and weight loss in women. Med Sci Sports Exerc 2002 Oct;34(10):1653-9.25.    Kremers SPJ, De Bruijn GJ, Schaalma H, Brug J. Clustering of energy balance-related behaviours and their interpersonal determinants. Psychol Health 2004 Jun;19(5):595-606.26.    Rothman AJ. “Is there nothing more practical than a good theory?”: why innovations and advances in health behavior change will arise if interventions are used to test and refine theory. Int J Behav Nutr Phys Act 2004 Jul;1(1):11.27.    Kearney JM, de Graaf C, Damkjaer S, Engstrom LM. Stages of change towards physical activity in a nationally representative sample in the European Union. Public Health Nutr 1999 Mar;2(1A):115-24.28.    Povey R, Conner M, Sparks P, James R, Shepherd R. Interpretations of healthy and unhealthy eating, and implications for dietary change. Health Educ Res 1998 Jun;13(2):171-83.29.    Colley RC, Garriguet D, Janssen I, Craig CL, Clarke J, Tremblay MS. Physical activity of Canadian adults: accelerometer results from 2007 to 2009 Canadian Health Measures Survey. Health Rep 2011 Mar;22(1):1-8.30.    Tudor-Locke C, Brashear MM, Johnson WD, Katzmarzyk PT. Accelerometer profiles of physical activity and inactivity in normal weight, overweight, and obese US men and women. Int J Behav Nutr Phys Act 2010 Aug 3;7:60.31.    Troiano RP, Berrigan D, Dodd KW, Mâsse LC, Tilert T, McDowell M. Physical activity in the United States measured by accelerometer. Med Sci Sports Exerc 2008 Jan;40(1):181-8.32.    Caballero B. The global epidemic of obesity: an overview. Epidemiol Rev 2007;29(1):1-5.33.    Suls J, Rothman A. Evolution of the biopsychosocial model: prospects and challenges for health psychology. Health Psychol 2004 Mar;23(2):119-25.34.    Baranowski T. Advances in basic behavioral research will make the most contributions to effective dietary change programs at this time. J Am Diet Assoc 2006 Jun;106(6):808-11.35.    Abraham C, Michie S. A taxonomy of behavior change techniques used in interventions. Health Psychol 2008 May;27(3):379-87.36.    Bandura A. The primacy of self-regulation in health promotion. Applied Psychology: An International Review 2005;54(2):245-54.37.    Baranowski T, Lin LS, Wetter DW, Resnicow K, Hearn MD. Theory as mediating variables: why aren’t community interventions working as desired? Ann Epidemiol 1997 Oct;7(7 Suppl):S89-S95.38.    Glasgow RE. What types of evidence are most needed to advance behavioral medicine? Ann Behav Med 2008 Feb;35(1):19-25.39.    Glasgow RE, Emmons KM. How can we increase translation of research into practice? Types of evidence needed. Annu Rev Public Health 2007;28:413-33.40.    Annesi JJ. Effects of a computer feedback treatment and behavioral support protocol on drop out from a newly initiated exercise program. Percept Mot Skills 2007 Aug;105(1):55-66.41.    Annesi JJ, Unruh JL. Effects of a cognitive behavioral treatment protocol on the drop-out rates of exercise participants in 17 YMCA facilities of six cities. Psychol Rep 2004 Aug;95(1):250-6.42.    Annesi JJ, Unruh JL. Effects of the Coach Approach intervention on drop-out rates among adults initiating exercise programs at nine YMCAs over three years. Percept Mot Skills 2007 Apr;104(2):459-66.43.    Bandura A. Social foundations of thought and action: a social cognitive theory. Englewood Cliffs, NJ: Prentice Hall; 1986.44.    Bandura A. Health promotion by social cognitive means. Health Educ Behav 2004 Apr;31(2):143-64.45.    Bandura A. Self-efficacy: the exercise of control. New York, NY: Freeman; 1997.46.    Annesi JJ. Relationship of social cognitive theory factors to exercise maintenance in adults. Percept Mot Skills 2004 Aug;99(1):142-8.47.    Annesi JJ, Unruh JL, Marti CN, Gorjala, S, Tennant, G. Effects of the Coach Approach intervention on adherence to exercise in obese women: assessing mediation of social cognitive theory factors. Res Q Exerc Sport 2011 Mar;82(1):99-108.48.    Landers DM, Arent SM. Physical activity and mental health. In: Singer RN, Hausenblas HA, Janelle CM, editors. Handbook of research on sport psychology. 2nd ed. New York: John Wiley & Sons; 2001. p 740-65.49.    Annesi JJ, Unruh JL. Correlates of mood changes in obese women initiating a moderate exercise and nutrition information program. Psychol Rep 2006 Aug;99(1):225-9.50.    Annesi JJ, Unruh JL. Relations of exercise, self-appraisal, mood changes and weight loss in obese women: testing propositions based on Baker and Brownell’s (2000) model. Am J Med Sci 2008 Mar;335(3):198-204.51.    Wing RR, Phelan S. Long-term weight loss maintenance. Am J Clin Nutr 2005 Jul;82(1 Suppl):222S-5S.52.    Baker CW, Brownell KD. Physical activity and maintenance of weight loss: physiological and psychological mechanisms. In: Bouchard C, editor. Physical activity and obesity. Champaign, IL: Human Kinetics; 2000. p 311-28.53.    Annesi JJ. Relations of changes in exercise self-efficacy, physical self-concept, and body satisfaction with weight changes in obese white and African American women initiating a physical activity program. Ethn Dis 2007 Winter;17(1):19-22.54.    Annesi JJ. Relations of changes in physical self-appraisal and perceived energy with weight change in obese women beginning a supported exercise and nutrition information program. Soc Behav Pers 2007;35(1):1295-1300.55.    Annesi JJ. Effects of improved self-appraisal and mood factors on weight loss in obese women initiating supported exercise. J Complement Integr Med 2011;8(1):article 11.56.    Annesi JJ, Gorjala S. Changes in theory-based psychological factors predict weight loss in women with class III obesity initiating supported exercise. J Obes 2010;2010. pii: 171957. Epub 2010 Jun 2.57.    Annesi JJ, Whitaker AC. Relations of mood and exercise with weight loss in formerly sedentary obese women. Am J Health Behav 2008 Nov-Dec;32(6):676-83.58.    Annesi JJ, Whitaker AC. Weight loss and psychologic gain in obese women—participants in a supported exercise intervention. Perm J 2008 Summer;12(3):36-45.59.    Hagger MS. Self-regulation: an important construct in health psychology research and practice. Health Psychol Rev 2010;4(2):57-65.60.    Annesi JJ. Behaviorally supported exercise predicts weight loss in obese adults through improvements in mood, self-efficacy, and self-regulation, rather than by caloric expenditure. Perm J 2011 Winter;15(1):23-7.61.    Annesi JJ. Self-regulatory skills usage strengthens the relations of self-efficacy for improved eating, exercise, and weight in the severely obese: toward an explanatory model. Behav Med 2011 Jul;37(3):71-6.62.    Annesi JJ, Gorjala S. Relations of self-regulation and self-efficacy for exercise and eating and BMI change: a field investigation. Biopsychosoc Med 2010 Sep 3;4:10.63.    Annesi JJ, Gorjala S. Relationship of exercise program participation with weight loss in adults with severe obesity: assessing psychologically based mediators. South Med J 2010 Nov;103(11):1119-23.64.    Annesi JJ, Marti CN. Path analysis of exercise treatment-induced changes in psychological factors leading to weight loss. Psychol Health 2011 Aug;26(8):1081-98.65.    Annesi JJ. Relations of mood with body mass index changes in severely obese women enrolled in a supported physical activity treatment. Obes Facts 2008;1(2):88-92.66.    Annesi JJ. Relationship of physical activity and weight loss in women with class II and class III obesity: mediation of exercise-induced changes in tension and depression. Int J Clin Health Psychol 2010 Sep;10(3):435-44.67.    Annesi JJ. Moderation of fatigue and stress in the carry-over of self-regulation and self-efficacy for exercise to self-regulation and self-efficacy for managed eating. Psychology 2011 Oct;2(7):694-9.68.    Annesi JJ. Relationship of initial self-regulatory ability with changes in self-regulation and associated fruit and vegetable consumption in severely obese women initiating an exercise and nutrition treatment: moderation of mood and self-efficacy. J Sports Sci Med2011 Dec;10:643-8.69.    Annesi JJ, Gorjala S. Association of reduction in waist circumference with normalization of mood in obese women initiating exercise supported by the Coach Approach protocol. South Med J 2010 Jun;103(6):517-21.70.    Annesi JJ. Relationships between self-regulation skills and physical activity and fruit and vegetable consumption in obese adults: mediation of mood and self-efficacy. Psychol Rep 2011 Feb;108(1):95-103.71.    Mata J, Silva MN, Vieira PN, et al. Motivational “spill-over” during weight control: increased self-determination and exercise intrinsic motivation predict eating self-regulation. Health Psychol 2009 Nov;28(6):709-16.72.    Teixeira PJ, Silva MN, Coutinho SR, et al. Mediators of weight loss and weight loss maintenance in middle-aged women. Obesity (Silver Spring) 2010 Apr:18(4);725-35.73.    Hankonen N, Absetz P, Haukkala A, Uutela A. Socioeconomic status and psychosocial mechanisms of lifestyle change in a type 2 diabetes prevention trial. Ann Behav Med 2009 Oct;38(2):160-5.74.    Muraven M, Baumeister RF. Self-regulation and depletion of limited resources: does self-control resemble a muscle? Psychol Bull 2000 Mar;126(2):247-59.75.    Baumeister RF, Gailliot M, DeWall CN, Oaten M. Self-regulation and personality: how interventions increase regulatory success, and how depletion moderates the effects of traits on behavior. J Pers 2006 Dec;74(6):1773-802.76.    Oaten M, Cheng K. Longitudinal gains in self-regulation from regular physical exercise. Br J Health Psychol 2006 Nov;11(Pt 4):717-33.77.    Annesi JJ. Effects of minimal exercise and cognitive behavior modification on adherence, emotion change, self-image, and physical change in obese women. Percept Mot Skills 2000 Aug;91(1):322-36.78.    Annesi JJ. Relation of perceived fitness with health changes and physiological changes in women exercisers. Percept Mot Skills 2002 Aug;95(1):226.79.    Annesi JJ. Relations of perceived bodily changes with actual changes and changes in mood in obese women initiating an exercise and weight-loss program. Percept Mot Skills 2006 Aug;103(1):238-40.80.    Annesi JJ. Correlations of changes in weight and body satisfaction for obese women initiating exercise: assessing effects of ethnicity. Psychol Rep 2009 Dec;105(3 Pt 2):1072-6.81.    Annesi JJ. Relations of changes in self-regulatory efficacy and physical self-concept with improvements in body satisfaction in obese women initiating exercise with cognitive-behavioral support. Body Image 2010 Sep;7(4):356-9.82.    Annesi JJ, Whitaker AC. Psychological factors discriminating between successful and unsuccessful weight loss in a behavioral exercise and nutrition education treatment. Int J Behav Med 2010 Sep;17(3):168-75.83.    Jackson C, Lawton R, Knapp P, et al. Beyond intention: do specific plans increase health behaviours in patients in primary care? A study of fruit and vegetable consumption. Soc Sci Med 2005 May;60(10):2383-91.84.    Stadler G, Oettingen G, Gollwitzer PM. Intervention effects of information and self-regulation on eating fruits and vegetables over two years. Health Psychol 2010 May;29(3):274-83.85.    Annesi JJ. Effects of cardiovascular exercise frequency and duration on depression and tension changes over 10 weeks. European Journal of Sport Science 2003 Aug;3(4):1-12.86.    Annesi JJ, Vaughn LL. Relationship of exercise volume with change in depression and its association with self-efficacy to control emotional eating in severely obese women. Adv Prev Med 2011;2011:514271.87.    Annesi JJ. Predictors of exercise-induced mood change during a 6-month exercise and nutrition education program with obese women. Percept Mot Skills 2009 Dec;109(3):931-40.88.    Annesi JJ. Dose-response and self-efficacy effects of an exercise program on vigor change in obese women. Am J Med Sci 2010 Feb;339(2):127-32.89.    Dunn AL, Trivedi MH, Kampert JB, Clark CG, Chambliss HO. Exercise treatment for depression: efficacy and dose response. Am J Prev Med 2005 Jan;28(1):1-8.90.    Annesi JJ. Relation of rated fatigue and changes in energy after exercise and over 14 weeks in previously sedentary women exercisers. Percept Mot Skills 2002 Dec;95(3 Pt 1):719-27.91.    Annesi JJ, Westcott WL. Relationship of feeling states after exercise and Total Mood Disturbance over 10 weeks in formerly sedentary women. Percept Mot Skills 2004 Aug;99(1):107-15.92.    Annesi JJ. Relationship between changes in acute exercise-induced feeling states, self-motivation, and adults’ adherence to moderate aerobic exercise. Percept Mot Skills 2002 Apr;94(2):25-39.93.    Annesi JJ. Relationship between before-to-after-exercise feeling state changes and exercise session attendance over 14 weeks: testing principles of operant conditioning. European Journal of Sport Science 2005 Dec;5(4):159-63.94.    Annesi JJ. Preliminary testing of a brief inventory for assessing changes in exercise-induced feeling states. Percept Mot Skills 2006 Jun;102:776-80.95.    Marcus BH, Selby VC, Niaura RS, Rossi JS. Self-efficacy and the stages of exercise behavior change. Res Q Exerc Sport 1992 Mar;63(1):60-6.96.    McAuley E, Mihalko SL. Measuring exercise-related self-efficacy. In: Duda JL, editor. Advances in sport and exercise psychology measurement. Morgantown, WV: Fitness Information Technology; 1998. p 371-90.97.    Clark MM, Abrams DB, Niaura RS, Eaton CA, Rossi JS. Self-efficacy in weight management. J Consult Clin Psychol 1991 Oct;59(5):739-44.98.    Warziski MT, Sereika SM, Styn MA, Music E, Burke LE. Changes in self-efficacy and dietary adherence: the impact on weight loss in the PREFER study. J Behav Med 2008 Feb;31(1):81-92.99.    Saelens BE, Gehrman CA, Sallis JF, Calfas KJ, Sarkin JA, Caparosa S. Use of self-management strategies in a 2-year cognitive-behavioral intervention to promote physical activity. Behav Ther 2000;31(2):365-79.100.    Dishman RK, Motl RW, Sallis JF, et al. Self-management strategies mediate self-efficacy and physical activity. Am J Prev Med 2005 Jul;29(1):10-8.101.    McNair DM, Heuchert JWP. Profile of Mood States (POMS) technical update. North Tonawanda, NY: Multi-Health Systems; 2005.102.    Godin G, Shephard RJ. A simple method to assess exercise behavior in the community. Can J Appl Sport Sci 1985 Sep;10(3):141-6.103.    Jacobs DR Jr, Ainsworth BE, Hartman TJ, Leon AS. A simultaneous evaluation of 10 commonly used physical activity questionnaires. Med Sci Sports Exerc 1993 Jan;25(1):81-91.104.    Miller DJ, Freedson PS, Kline GM. Comparison of activity levels using Caltrac accelerometer and five questionnaires. Med Sci Sport Exerc 1994 Mar;26(3):376-82.105.    Kristal AR, Beresford SAA, Lazovich D. Assessing change in diet-intervention research. Am J Clinical Nutr 1994 Jan;59(1 Suppl):185S-9S.106.    Sharma S, Murphy SP, Wilkens LR, et al. Adherence to the food guide pyramid recommendations among African Americans and Latinos: results from the Multiethnic Cohort. J Am Diet Assoc 2004 Dec;104(12):1873-7.107.    Epstein LH, Gordy CC, Raynor HA, Beddome M, Kilanowski CK, Paluch R. Increasing fruit and vegetable intake and decreasing fat and sugar intake in families at risk for childhood obesity. Obes Res 2001 Mar;9(3):171-8.108.    Rolls BJ, Ello-Martin JA, Tohill BC. What can intervention studies tell us about the relationship between fruit and vegetable consumption and weight management? Nutr Rev 2004 Jan;62(1):1-17.109.    Janssen I, Katzmarzyk PT, Ross R. Waist circumference and not body mass index explains obesity-related health risk. Am J Clin Nutr 2004 Mar;79(3):379-84.110.    Shen W, Punyanita M, Chen J, et al. Waist circumference correlates with metabolic syndrome indicators better than percentage fat. Obesity (Silver Spring) 2006 Apr;14(4):727-36.111.    Locke EA, Latham GP. The application of goal setting to sports. Journal of Sport Psychology 1985;7:205-22.112.    Locke EA, Latham GP. Building a practically useful theory of goal setting and task motivation. A 35-year odyssey. Am Psychol 2002 Sep;57(9):705-17.113.    Marlatt GA, George WH. Relapse prevention: introduction and overview of the model. Br J Addict 1984 Sep;79(3):261-73.114.    Robertson RJ, Noble BJ. Perceptions of physical exertion: methods, mediators, and applications. In: Holloszy JO, editor. Exercise and sport sciences reviews. Vol 25. Philadelphia: Williams & Wilkins; 1997. p 407-52.115.    Garber CE, Blissmer B, Deschenes MR, et al; American College of Sports Medicine. American College of Sports Medicine position stand. Quantity and quality of exercise for developing and maintaining cardiorespiratory, musculoskeletal, and neuromotor fitness in apparently healthy adults: guidance for prescribing exercise. Med Sci Sport Exerc 2011 Jul;43(7):1334-59.116.    Kaiser Permanente Health Education Services. Cultivating Health weight management kit. 8th ed. Portland, OR: Kaiser Permanente; 2008.117.    Schafer JL. Analysis of incomplete multivariate data. London: Chapman Hall; 1997.118.    Schafer JL, Graham JW. Missing data: our view of the state of the art. Psychol Methods 2002 Jun;7(2):147–77.119.    Nackers LM, Ross KM, Perri MG. The association between rate of initial weight loss and long-term success in obesity treatment: does slow and steady win the race? Int J Behav Med 2010 Sep;17(3):161-7.120.    Glymour MM, Weuve J, Berkman LF, Kawachi I, Robins JM. When is baseline adjustment useful in analyses of change? An example with education and cognitive change. Am J Epidemiol 2005 Aug 1;162(3):267-78.121.    Hall KD. What is the required energy deficit per unit weight loss? Int J Obes (Lond) 2008 Mar;32(3):573-6.122.    Umstattd RM, Wilcox S, Saunders R, Watkins K, Dowda M. Self-regulation and physical activity: the relationship in older adults. Am J Health Behav 2008 Mar-Apr;32(2):115-24.123.    Tate DF, Wing RR, Winnett RA. Using Internet technology to deliver a behavioral weight loss program. JAMA 2001 Mar 7;285(9):1172-7.124.    Wing RR, Tate DF, Gorin AA, Raynor HA, Fava JL. A self-regulation program for maintenance of weight loss. N Engl J Med 2006 Oct 12;355(15):1563-71.125.    Linde JA, Rothman AJ, Baldwin AS, Jeffery RW. The impact of self-efficacy on behavior change and weight change among overweight participants in a weight loss trial. Health Psychol 2006 May;25(3):282-91.126.    Roach JB, Yadrick MK, Johnson JT, Boudreaux LJ, Forsythe WA 3rd, Billon W. Using self-efficacy to predict weight loss among young adults. J Am Diet Assoc 2003 Oct;103(10):1357-9.
Proactive Office Encounter: A Systematic Approach to Preventive and Chronic Care at Every Patient Encounter
Thursday, 30 September 2010
2009 James A Vohs Award for Quality Michael Kanter, MD; Osvaldo Martinez, MPH; Gail Lindsay, RN; Kristen Andrews; Cristine Denver, SM Fall 2010 - Volume 14 Number 3 Abstract In 2007, Kaiser Permanente’s (KP) Southern California Region designed and implemented a systematic in-reach program, the Proactive Office Encounter (POE), to address the growing needs of its three million patients for preventive care and management of chronic disease. The program sought staff from both primary and specialty care departments to proactively identify gaps in care and to assist physicians in closing those gaps. The POE engaged the entire health team in a proactive patient-care experience, creating standard work flows and using information technology to identify gaps in patient care. The goals were to improve consistency of preventive care and improve quality of care for chronic conditions and to improve reliability of staff support for physicians. The POE has been implemented in all outpatient settings in KP’s Southern California Region’s 13 medical centers and 148 medical office buildings. The program has contributed to significant improvements in key clinical quality metrics, including cancer screenings, blood pressure control, and tobacco cessation. It is now being extended into the inpatient setting and is being shared with other KP Regions. Introduction “The necessity of living with a limited supply of physicians in the face of increasing demand forces us to focus on the need for a medical care delivery system that utilizes scarce and costly medical manpower properly.”1 Sidney Garfield, MD, the co-founder of Kaiser Permanente (KP), wrote those words in 1970 for an article that appeared in Scientific American (reprinted in the Summer 2006 issue of The Permanente Journal), but they could well have been written today to describe the growing demands on primary care, particularly for preventive care and management of chronic disease. The medical literature reports that for a primary care physician to ensure that all patients on a hypothetical panel of 2000 receive the preventive screenings and treatment of chronic diseases that they need, the primary care physician would need to devote an estimated 18 hours per day.2,3 That being the case, it is hardly surprising that only 54.9% of adult patients receive the preventive care recommended by medical evidence.4 (SCPMG) now serves more than three million KP patients, generating 12 million visits to outpatient offices with 60% of these visits occurring outside of primary care. The concept of the Proactive Office Encounter (POE) began as a question: How can we turn each of these encounters, in either primary or specialty care, into preventive screenings and care for chronic conditions? This is a simple idea to describe, but implementing it meant a cultural shift. The POE, a regionwide in-reach program, gave ancillary staff and specialty departments more responsibility for preventive screenings and management of chronic care. To succeed, the team had to convince administrators, physicians, and staff of its potential value. Other key elements included: Electronic tools to identify gaps in any patient’s care, regardless of which department they visited New work flows and training modules to proactively identify gaps in care to draw them to a physician’s attention Reports to monitor improvement in closing gaps and to identify areas needing more support. Team members are noted in Table 1. Staff now play a more active role in patient care and the culture has changed so that specialty departments are also responsible for identifying and addressing preventive screenings and chronic care needs. Since its inception, POE has contributed to sharp improvement in the Southern California Region’s clinical quality performance, including double-digit improvements in colorectal cancer screening, advice to quit smoking, and blood pressure control. Electronic Tools: Step 1 in the Proactive Office Encounter Early attempts made to systematically identify and address preventive care needs were less comprehensive than the POE; for example, a few years ago, identifying needs required a manual search through a patient’s chart and use of a paper checklist (the Care Management Summary Sheet) to identify preventive screenings and gaps in chronic care. The Pharmacy Analytic Services group converted the paper to an electronic checklist on its Permanente Online Interactive Network Tools (POINT) database, though it was not used consistently in all medical offices until integrated into KP HealthConnect, the electronic medical record (EMR). The electronic POE tools provide physicians and staff with adult primary care, specialty care, and pediatric care checklists (Figure 1), which identify gaps to be addressed and recommended actions. For example, a patient due for a bone-density test or mammogram had a pending order set up and an appointment made for the required examination. Additionally, the POE team created shortcuts known as SmartTools within KP HealthConnect to improve efficiency in the medical office. By scrolling through a list of common preventive care needs, a nurse or medical assistant can set up pending orders for screening examinations or supplies, immunizations, or laboratory tests and can select and print appropriate patient information on topics ranging from body mass index to tobacco cessation. Using “SmartPhrases,” staff can document preventive or chronic care actions taken. Early Technical Challenges Initially, patient information in POINT and KP HealthConnect was not integrated, creating confusion and mistrust early in the implementation of the POE tool, because alerts were sometimes inaccurate or redundant. The project team worked with Pharmacy Analytics Services and the KP HealthConnect team to integrate the POINT database and the EMR. The team added functionality to document or to set up pending orders, streamlining these processes to make the POE tool more efficient and user-friendly. Methods Developing and Implementing New Work Flows: Step 2 in the Proactive Office Encounter Information technology alone is not sufficient to transform the approach to preventive and chronic care. A standardized structure of work flows and processes was built to address individual care gaps in every outpatient setting (Table 2), to increase efficiency and to improve the reliability and consistency of staff support for physicians. The POE includes three main components, detailed in the next section (Figure 2). Before an Encounter (Pre Encounter) Before a patient comes in, a medical assistant or nurse reviews the patient’s record to identify needed laboratory tests and health screenings, and to determine whether the patient is registered with KP.org, which gives the patient online access to most laboratory results, prescription and immunization status, and the opportunity to e-mail the physician’s office. During an Encounter (Office Encounter) In the office, the nurse or medical assistant follows a standard workflow (Figure 3) that includes reviewing and updating documentation of the patient’s chief complaint, vital signs, physical activity levels, medications, allergies, and preferred pharmacy. The nurse or medical assistant then: identifies gaps in care using decision-support tools sets up any necessary pending orders and/or exclusion codes for the clinician flags needed screenings and/or uncontrolled conditions for the clinician to discuss during the visit prepares the patient and examination room for procedures (eg, Papanicolaou test, diabetic foot examination, etc), and assists the clinician through the process. After an Encounter (Post Encounter) Immediately after the visit, the medical assistant or nurse ensures that the patient receives information to obtain preventive screenings or to address health issues, including providing an after-visit summary, after-care instructions, health education materials, information on accessing KP.org, and follow-up appointments or referrals. In addition, the patient may be contacted after the visit at the clinician’s direction. Managing the Change Because the POE represented a cultural shift, it therefore required a comprehensive change in management approach. In 2007, the POE team widely presented the concept to internal audiences, including Medical Directors, Chiefs, nonphysician administrative leaders, and department managers. One challenge was ensuring that tasks remained within the scope of practice for medical assistants and nurses. They identified physicians and administrators who could serve as POE team leads at the local level. The team also developed extensive training materials for both preventive screenings and management of chronic conditions. Participants learned to use the tools and to perform new tasks, for example, communication tips about sensitive patient issues, such as weight. It also provided instructions on how to prepare the patient and the examination room for specific procedures, such as a diabetic foot examination. Persuading people to work in a new way meant engaging them emotionally. To demonstrate the difference that nonphysician staff can make identifying care gaps, the POE team worked with California’s Multimedia Department to produce videos of patients telling how an early screening made a difference in their lives. The videos, which have since been shown in internal meetings and are available on KP’s Intranet, included patients’ physicians and key staff (including receptionists, medical assistants, and nurses). By the end of 2007, all primary care offices trained for the POE. The following year, specialty care staff trained on a streamlined version of the program. In 2009, staff in Urgent Care and Emergency Departments (ED) used work flows for the POE. Those concepts now extend to inpatient settings, with four pilot studies underway. Results Measuring Improvement: Step 3 in the Proactive Office Encounter SCPMG measured the program’s success by tracking Healthcare Effectiveness Data and Information Set results on a bimonthly basis. In addition, SCPMG developed a new set of reports (dubbed “Successful Opportunities”) to measure improvements specific to the POE (Table 3). These reports monitor the frequency of care gaps closure within 30 days of an appointment, including lead, chlamydia, and osteoporosis screening (dual energy x-ray absorptiometry, or DEXA); pneumococcal immunizations; documentation of height and weight to capture body mass index; asthma questionnaire completion; and health education class attendance. These reports are e-mailed to regional leaders, medical center leaders, and local POE leads for identification of strengths and areas for improvement. Specialists in SCPMG have some of their at-risk moneys contingent on their performance on the Successful Opportunities Report. This has been an important step in getting the specialists involved in the POE. The conclusions drawn from the analysis of these data reveal increased success in closing care gaps at every opportunity resulting in a 2% to 18.5% range of improvement in clinical quality for the conditions of diabetes, cancer, immunization, blood pressure, and smoking (Table 4). Future Potential for the Proactive Office Encounter In the outpatient setting, the POE allowed a shift from a reactive care-delivery model to one that is consistently proactive in addressing preventive and chronic care needs. Because SCPMG is part of an integrated system that includes Kaiser Foundation Health Plan and Hospitals, there are more opportunities to expand and embed this approach throughout the organization where patients may seek care, from appointment call centers to hospital discharge. In the near future, SCPMG intends to implement the POE in pharmacy and inpatient settings. Deployment in EDs and urgent-care settings is already in progress. Pre-encounter automated telephone calls were also piloted in 2008 and were deployed throughout SCPMG by year end. Automated pre-encounter calls target patients with HbA1c, lipid, and/or microalbumin laboratory care gaps and ask that they complete the necessary tests before their office visit to maximize their encounter with their clinician. Implementing a proactive approach to care also involves continual improvement to the work flows already developed and requires refining the outpatient encounter with specialty-specific work flows, which are in development, for obstetrics, oncology, and nephrology. With modification of the work flow training materials for SCPMG, other KP Regions could adopt a similar proactive approach, because other Regions have access to the same KP HealthConnect functionality and SmartTools required to support proactive care. Fully implementing this would require processes and structures for staff and physicians to use those electronic tools to close care gaps. That will require a comprehensive change in management approach, including a communication strategy and an extensive training program. More information and educational videos, job aides, and reference sheets are available from: http://proactivecare.kp.org. KP’s Hawaii Region is now adopting a proactive care approach, embracing principles of the POE. In KP’s Mid-Atlantic Region, an ophthalmologist who saw an 82-year-old patient ordered a DEXA scan, which showed osteoporosis (Janice M Beaverson, MD, personal communication, March 2010).a There is much external interest, including in community clinics in Southern California and professional and national health organizations. Conclusion The project’s impact has been widespread and positive, changing the organization’s culture and providing a powerful tool for physician’s, staff, and patients. Proactive care is now an expectation of care delivery. Barriers encountered by the team were overcome through a collaborative approach, which involved labor partners, physicians, and leaders in the implementation from the early stages. Correlation data show a positive impact on the delivery of quality care. a    Janice Beaverson, MD, Associate Medical Director, Quality and Health Management for the Mid-Atlantic Permanente Medical Group, Rockville, MA. Disclosure Statement The author(s) have no conflicts of interest to disclose. Acknowledgment Katharine O’Moore-Klopf, ELS, of KOK Edit provided editorial assistance. References   1.    Garfield SR. The delivery of medical care. Sci Am 1970 Apr;222(4):15–23. (Reprinted in Perm J 2006 Summer;10[2]:46–55.) 2.    Østbye T, Yarnall KS, Krause KM, Pollak KI, Gradison M, Michener JL. Is there time for management of patients with chronic diseases in primary care? Ann Fam Med 2005 May–Jun;3(3):209–14. 3.    Yarnall KS, Pollak KI, Østbye T, Krause KM, Michener JL. Primary care: is there enough time for prevention? Am J Public Health 2003 Apr;93(4):635–41. 4.    McGlynn EA, Asch SM, Adams J, et al. The quality of health care delivered to adults in the United States. N Engl J Med 2003 Jun 26;348(26):2635–45  
Primary Care DirectConnect: How the Marriage of Call Center Technology and the EMR Brought Dramatic Results—A Service Quality Improvement Study
Thursday, 27 May 2010
Brent Bowman, MBA; 
Scott Smith, MD Summer 2010 - Volume 14 Number 2 Abstract Of the key Health Plan patient satisfaction measures used in Kaiser Permanente Colorado, ease of contacting the physician’s office with a medical question was consistently rated as the lowest quarterly patient satisfaction measure. Furthermore, medical office staff had become dissatisfied with their inability to contact patients who had previously left messages. In addition to the shear volume of messages, the return calls were often unanswered, leading to subsequent attempts to reach patients, creating additional work for medical office staff. DirectConnect—the project name for a system and set of processes focused on improving patient satisfaction with the ability to contact Primary Care delivery teams by telephone—focuses on isolating medical advice calls from the other types of calls handled by the centralized Call Center. The system identifies the patient using his/her unique electronic medical record number, then automatically routes medical advice calls directly to the appropriate Primary Care Physician (PCP) or staff. The clinician may then evaluate and respond to the patient’s need quickly, thus managing more of their panel’s requests in real time. How is DirectConnect different from simply having the patient contact their PCP’s office directly? The primary difference is “one-number” convenience that allows all patients to dial one number to access their PCP’s team. In addition, calls are routed to various staff as available to reduce long telephone queues and wait times. The DirectConnect system has resulted in statistically significant improvement in key service quality measures. Patient satisfaction improved from a pre-implementation nine quarter mean of 55.9% to a post-implementation 12 quarter mean of 70.2%. Fourteen percent to 17% of all Primary Care calls are now handled by the patient’s home medical office team, creating a 54% improvement in the centralized Call Center’s speed of answering calls in the first quarter post implementation—making no additions to medical office staffing levels. The efficiencies gained by directly connecting medical advice-seeking patients with their Primary Care team resulted in an estimated savings of 198 and 247 cumulative hours per week in unnecessary telephone work for Call Center and medical office staff regionwide. Introduction Problem Definition For the nine quarters prior to DirectConnect’s implementation, on average only 55% of Kaiser Permanente Colorado (KPCO) patients rated the ability to contact their physician as “extremely easy” or “easy” with a range between 44% and 59% (Figure 1). This served as evidence of KPCO’s “big system” feel when compared to its care delivery competitors. Patients routinely expressed their frustration with the process of leaving a message with someone they didn’t know (Call Center agent) and awaiting a call back at some unpredictable time in the future. The following patient comments on the system of leaving telephone messages were documented in KPCO’s QIII 2005 and QIV 2005 patient satisfaction study:. “It makes it more difficult to wait for them to call back. It might be sometime later in the day, so it’s not convenient because you don’t know when they could call you back.” “It is just hard to give them a call back number if you don’t know where you are going to be and they can’t tell you exactly when [they will] call.” “I would tell [KPCO] that they need to have a different way to actually contact a physician or triage nurse when needed, a lot easier than it is now.” Before DirectConnect, patients with a medical question would call the regional Primary Care Call Center with the hope of speaking with someone from their home medical office. Instead, centralized Call Center agents, located away from all primary care medical office buildings were forced to use an electronic message to route questions to the appropriate medical office building. Patients then awaited a return call from their trusted Primary Care team. Although patients ultimately received the appropriate level of care, the process rarely met preferred service expectations. Beyond the well-documented issues of poor patient satisfaction, the internal system of managing telephone messages was fraught with waste and rework—although the full extent of this waste and rework had not been formally quantified. From the centralized Call Center perspective, inbound call volumes were projected to increase at a rate of 3% to 10% per year and the ability to increase staffing was not available. These challenges resulted in 64% of calls answered within 60 seconds for the year prior to implementation of DirectConnect with an average speed to answer calls of 101 seconds during that period. These statistics are evidence of less than desired telephone service for any need related to Primary Care, be it for appointments or medical questions. Current State Measurement and Analysis Process improvement expert W Edwards Deming, one of the fathers of Lean Manufacturing concepts noted: “Workers are responsible for only 15% of the problems, the system for the other 85%. The system is the responsibility of management.”1p94 In keeping with this philosophy, a small team of management, frontline employee representatives, internal consultants, and analysts were identified to focus on improving the system of telephone message management and to develop the methods by which ongoing measurement of that workflow could be realized (Table 1). Figure 2 depicts the high-level process flow yielded by the analysis of the telephone messaging system. Four to seven process steps were needed to highlight the vast majority of scenarios related to the telephone message system. Weekly volumes were tabulated to capture the average number of electronic messages routed to each medical office building from the Call Center, the average number of documented attempts made by the medical office staff to call the patient back, and any subsequent return calls into the Call Center for transfer to the medical office building because the patient was not available to receive the first call back. For every 100 electronic messages routed from Call Center to medical office, an average of 130 call attempts were made from medical office staff back to the patient and another 21 calls were made from the patient back to the Call Center—ultimately receiving a call transfer to the Primary Care team in the medical office. Scope The scope of the improvement effort focused on medical advice telephone messages that were routed electronically from the centralized Call Center to each of 17 Primary Care medical offices. These messages required a nonclinically trained Call Center agent to answer the call and document the chief complaint and symptoms. The Call Center agent then routed the message to the appropriate medical office where clinical staff and physicians would sort through the messages and return those calls at some future point. These calls represented 20% of the Call Center’s two million annual calls received. The remaining calls handled by the Call Center included appointment requests for Primary Care and other medical specialties, pharmacy requests and general information requests. These calls were considered outside the scope of the improvement effort. Methods Using Lean Manufacturing and Six Sigma concepts coupled with Call Center industry technology, a new program was developed to transform the way telephone-based medical questions from a Primary Care Physician’s (PCP’s) panel would be handled. The Six Sigma DMAIC (Define, Measure, Analyze, Improve, and Control) method was heavily leveraged in the development of the solution. During the analysis phase, Lean Manufacturing methods, in particular value stream mapping, flow,2 and root cause analysis were used. Lean’s concepts of reducing work in process to decrease completion time3 and removing wastes, most notably those related to overproduction and defects, governed many of the decision points of the effort. Measuring and Analyzing the Current State To measure the overproduction and delays associated with the medical advice telephone messaging process, 1) time and motion studies were performed, 2) data was retrieved from Call Center reports, 3) reports were developed to specifically measure the responsiveness of medical offices staff to telephone messages as captured by the electronic medical record, and 4) a third party administered a satisfaction survey sent quarterly to patients. 1. Time and motion studies found that, on average, Call Center agents spent 124 seconds per medical advice telephone message and medical office staff spent, on average, 44 seconds calling back the caller, waiting for the phone to ring, and leaving a message when unable to reach the originator of the request. All of this time was non-value-added4 in the system. From a patient satisfaction perspective, value is primarily added to these types of calls only when speaking to their PCP or a clinical team member of that PCP in their home medical office. 2. Standard Call Center reports were used to assess the impact process and system change would have in the Call Center. Key metrics included the average speed of answer for all inbound calls and the percentage of calls answered within 60 seconds. The number of Call Center agent full-time employee resources needed to provide improved service was also tracked. 3. The electronic medical record (EMR) documentation yielded more evidence of waste in the system. For every 100 telephone messages routed to the medical office by the Call Center on average, EMR documentation revealed that 130 return call attempts were made by that medical office. This highlights the frequency of occurrence that the medical office staff or clinician received no answer or was forced to leave a voice message to have the patient call back. Furthermore, the analysis showed that on average 21% of patients were required to place a second call back to the Call Center before being manually transferred to the medical office after having previously left a message. This loop of wasteful overproduction in the system was referred to as the ratio of telephone tag in the system. 4. Patient satisfaction with the ability to contact physicians or care delivery teams with a medical question was tabulated on a quarterly basis by a third party survey administrator. Before DirectConnect, this measure maintained a nine quarter mean of 54.6% satisfaction with ease of contacting clinician with a range from 44.0% to 59.0%, an upper control limit of 68.9%, and a lower control limit of 40.3%. Intervention DirectConnect seeks to provide a way to more efficiently and effectively handle increases in Primary Care-related call volume that comes with growing patient demand and with increasing use of the telephone as a key channel of communication between patient and physician. By streamlining this channel of communication, DirectConnect aims to increase the level of trust between patients and physicians by increasing the frequency that medical advice is delivered to the patient by a caregiver known and trusted by the patient—typically by their personal PCP or their physician’s team. Increasing the frequency of real-time response to a patient’s medical question by a known, trusted caregiver became the hallmark of the DirectConnect process of telephone request management for PCPs and their care delivery teams. Pilot With the data made available as a result of the analysis phase, a manual system was designed to pilot the removal of the telephone tag associated with the medical advice telephone messaging. Three medical offices—one housing general Internal Medicine physicians, one with Pediatricians, and the third with a mixed Primary Care model of general Internal Medicine, Family Medicine, and Pediatrics—were selected. These medical offices began a pilot in which, when a call was received, the Call Center agent would remain on the line and would transfer the call directly to the patient’s home medical office, instead of creating an electronic message. Although this pilot required that the Call Center absorb the cost of spending more time on the line with patients while waiting for the medical office staff to answer—the return call volume declined dramatically. This decline was as a result of handling a greater percentage of would-be electronic messages in real time—a Lean Manufacturing concept known as single-piece flow, versus the prior method of electronic messaging, which was more akin to the Lean Manufacturing concept of batch-and-queue. Technological Intervention Once the initial pilot was successfully completed, a technological intervention pilot was funded and implemented that allowed the system to automatically identify the PCP, capture the nature of the call—whether a medical question or appointment request—match these attributes, and direct the call to the appropriate staff member. Additional attributes were included in the design that allowed the system to evaluate and to predict the next available staff member and that ensured calls would not be queued for longer than an agreed-upon threshold. Further system revisions were made throughout the implementation to present any waiting callers with the option to remain holding or be immediately transferred to a Call Center agent to leave an electronic message. This put the decision to remain on hold in the hands of the patient. If the caller selected the option to leave a message instead of remaining on hold, the call would be seamlessly routed to the next available Call Center agent where an electronic message would be sent to the medical office in traditional fashion (Figure 3). Models and Options During the first two months of deployment, several call routing models and medical office workflow options were tested. Best practices were shared and adopted. The result has been sustained improvement in all 12 quarters following implementation. Weekly reports indicating medical office performance are posted and accountabilities are in place to ensure results are sustained. Since full deployment in July 2007, DirectConnect calls consistently represent between 15% to 20% of overall Primary Care telephone volume, with one outlier of 22% in November 2008 (Figure 4). This suggests that patients who learn the system are not inclined to abuse the service beyond what is required on the basis of their request. Although medical office staff answers 98% to 100% of all DirectConnect calls to the medical office, some physicians have chosen to log into the system as part of their daily routine when returning calls to patients. This capability allows physicians who wish to deliver a significantly higher level of service to their patients the opportunity to do so. Results With the system and associated processes implemented, dramatic gains have been achieved without adding any resources in the medical offices and while reducing the resource requirements of the Call Center. Today, 14% to 17% of total annual inbound call volume is answered by the home medical office. For each of these calls, the Call Center need not answer them, create telephone messages for them, or route them to the medical office where the patient must await a return call later in the day. Furthermore, the Call Center’s speed of answering calls improved by 54% in the first quarter after implementation compared to the same quarter from the year before. Now, for every 100 documented inbound telephone advice encounters that fall within the scope of DirectConnect on average, 79 requests are handled on the first call by the patient’s home medical office physician or team. Although the remaining 21 requests require additional research or a higher skill set to be satisfied, the return calls required to reach the patient are lower when the telephone encounter originates in the home medical office—presumably because the medical office team can provide a more targeted call back time than the centralized Call Center. This increases the odds of reaching the patient when the return call is made. Thus, the system has experienced a documented 26.9% reduction in required return calls because of DirectConnect. This reduces the number of non-value-added steps associated with the medical advice request process from 193 (Figure 2) to 45 (Figure 5). The removal of these non-value-added process steps yields a weekly time savings of between 198 and 247 hours per week in unnecessary telephone work for Call Center and medical office staff. Patient satisfaction with the ability to contact their PCP or Primary Care delivery team with a medical question, the key driver of improvement, has improved a statistically significant 14% and maintained a nine quarter mean of 70.2% satisfied with a range from 65% to 79% and an upper control limit of 77.9% and a lower control limit of 62.6% since implementation. Discussion Key Successes DirectConnect enabled significant improvements for the patients of KPCO while eliminating system barriers that hampered PCPs and staff from providing the high level of service they desired (Table 2). By systematically driving 14% to 17% of KPCO’s inbound telephone volume directly to the home medical office of the patient, Call Center service levels have improved beyond the internal target of 80% answered within 60 seconds (Figure 6) while maintaining an average speed of answering inbound calls below the 60 second mark in each month following the DirectConnect deployment. These Call Center improvements occurred without adding Call Center staff. In fact, the DirectConnect system’s financial breakeven point occurred ten months after full deployment as a result of savings generated by Call Center agent attrition—while maintaining these improved levels of service. Removing call volume from the centralized Call Center and routing those calls directly to the home medical office of the patient will, on the surface, appear to necessitate a need to shift resources to those medical office buildings to handle the volume; however, because of the single-piece flow nature of the new system, this process is far more efficient for the medical office staff than the previous batch-and-queue process associated with electronic messages. Medical office staff and PCPs make 26.9% fewer return calls; this equates to a time savings 198 to 247 hours per week across the system. Most importantly, these measurable improvements in both Call Center and medical office areas have led to statistically significant improvements in patient satisfaction—the ultimate objective of the DirectConnect implementation. From the pre-DirectConnect mean of 55.9% satisfaction with the patient’s ability to contact their physician, this measure increased to a mean of 70.2%—14.3% higher than the mean of the previous process, and 3.3% higher than the eight quarter upper control limit of the previous process (Figure 7). DirectConnect has brought KPCO patients closer to their physicians and the Primary Care delivery teams that know them. The barriers that once existed as a result of the desire to gain economies of scale through a large, centralized Call Center have been mitigated. This system has pleased physicians, medical office staff, and those seeking care (Table 3). As health care seeks to better meet the needs of the population, systems like DirectConnect lend credence to the concept that large health plans and provider groups can foster better communication with members and patients without sacrificing affordability of care. Future The future implications of this marriage between Call Center technology and the electronic medical record are exciting. Once a technical interface is created between the caller’s EMR and the Personal Physician—as in the DirectConnect system—new opportunities to creatively connect patient and physician exist. For example, on the basis of diagnosis, stratification of patients may occur to automatically route them to the nurse who is most equipped to handle questions related to their condition. Additionally, physicians may be able to establish one-time clinical rules that permit the patient to be directly routed to the physician’s mobile phone upon their next call if important information exchange is needed. Within the context of the telephone system, a mobile phone could be considered part of the greater call routing system, thereby falling under the umbrella of load balancing and call handling redundancy to ensure that calls are not left unanswered. This system creates a foundation on which the relationship between the patient and their personal physician can be further enhanced. Disclosure Statement The author(s) have no conflicts of interest to disclose. References     1.    Walton M. The Deming management method. New York: Penguin Putnam; 1986.     2.    Womack JP, Jones DT. Lean thinking: banish waste and create wealth in your corporation. New York: Simon & Schuster; 2003.     3.    Gerst R. The little known law. Six Sigma Forum Magazine 2004 Feb;3(2):18-23.     4.    George ML. Lean six sigma for service: How to use lean speed and six sigma quality to improve services and transactions. New York: McGraw-Hill; 2003.
Obesity: Problem, Solution, or Both?
Wednesday, 30 June 2010
Vincent J Felitti, MD, FACP; Kathy Jakstis; Victoria Pepper, MS; Albert Ray, MD Spring 2010 - Volume 14 Number 1 Since 1982, the Southern California Permanente Medical Group’s Positive Choice Weight Loss Program in San Diego has treated more than 30,000 adults, predominantly middle-aged, for obesity—some successfully, some not. This has been an extraordinary experience and provided us with numerous counterintuitive observations. We now are convinced that obesity is widely misunderstood, and we realize that the unusual program we have operated safely and effectively for more than a quarter century is often misunderstood as well. There is growing interest in our program and in using our approach as a model for other Kaiser Permanente (KP) Regions. We therefore share an overview here of our experience with this specific program. Consequently, most referenced works in this report are publications emanating from our program, sometimes contrasting those findings with conventional views on the subject. The Positive Choice Weight Loss Program has two integrated components: • Prolonged absolute fasting, with the use of a supplement to support health and to prevent death from such fasting. • A lengthy and complex group program to explore the basis of each participant’s unconscious compulsive use of food, as well as to explore the hidden benefits of obesity for that individual. Given that the average weight loss of someone completing our 20-week program is 62 lb (28 kg) and that approximately 5000 patients each have lost more than 100 lb (45 kg), we realize we have challenged the belief systems of some who assume either that such weight loss cannot commonly be achieved or that the process of supplemented absolute fasting must be dangerous. In fact, the process has been notably safe, and major improvements in biomedical outcomes have been the norm. This article addresses four basic issues: 1. The safety of properly supplemented prolonged absolute fasting in obesity 2. The observed origins of obesity, and their implications 3. The components of a relevant treatment program 4. Outcomes of the Program. Overview of Unsupplemented Starvation The Irish hunger strikers of the early 1980s illustrated the outcome of unsupplemented, prolonged, absolute fasting. They only drank water, and it was clear after six weeks that all involved had sustained significant weight loss and were mortally ill. By seven weeks, all were dead. They died because of profound potassium and magnesium deficiency, with consequent lethal cardiac arrhythmia. Had they received electrolyte supplementation and had the hunger strikers been obese, they could have lived for several months longer before dying because of major protein deficiency. Supplementing two essential fatty acids and the essential amino acids needed for anabolic protein turnover would have prevented such a death. Had this been done, the hunger strikers would have died toward the end of a year because of beriberi, pellagra, and scurvy. Preventing these diseases by vitamin supplementation would be straightforward. To simplify the example, we have left out the problem of calorie deficiency in these nonobese individuals. In obese individuals, body fat stores of course resolve this problem; the metabolism of these fat stores is obviously the basis for weight loss. Details of unsupplemented starvation can be found in the famous work of Ancel Keys, described in his two-volume Biology of Human Starvation.1 Safety of Supplemented Fasting The nutritional supplement Optifast 70 was created by Sandoz Pharmaceuticals to supply electrolytes, amino acids, two essential fatty acids, and vitamins. At 420 cal/d in five feedings, this superbly designed product allows a sufficiently morbidly obese individual to cease eating all food and caloric beverages for at least a full year. In our entire experience, no death or biomedical harm has occurred in any of these individuals. During a year of supplemented absolute fasting, a weight loss of approximately 300 lb (136 kg) will occur (Figure 1). To the degree that this does not occur, it means that the patient is consuming food, regardless of denial. Surprisingly, hunger is not a problem. However, the desire to eat is variable, ranging from minor to uncontrollable. Interestingly, this desire to eat is an issue separate from hunger. Indeed, it attests to the profound psychoactive benefits of food, as illustrated by a commonplace observation that is even built into our language: “Sit down and have something to eat; you’ll feel better.” There is truth for many in the phrase “comfort food.” Origins of Obesity In the early years of the Weight Program, we naively were taking morbidly obese individuals down 300 lb (136 kg) at a time, a rate of loss distinctly exceeding that of bariatric surgery. The striking results perhaps understandably led us to believe that we understood what we were doing. Counterintuitively, some of our most successful patients forced us to realize we were merely in possession of a powerful technology and had no idea what we were doing in other regards. They did this by demonstrating that massive weight loss could precipitate divorce, severe anxiety, and sometimes suicidality. Some patients, sensing these outcomes early, fled their own success in the Program. Surprisingly, our high dropout rate was mainly limited to patients who were successfully losing weight. By contrast, we had other patients who were eating during the Program, routinely denying it, and losing no weight while paying a fairly significant fee, seemingly to accomplish nothing. With these patients, it took some time for us to realize that we were supplying an important support system with our group approach. It turned out that many of our obese patients had no functional support systems at home. The striking and frankly annoying conflict between our ability quickly and safely to reduce a person’s weight and what patients appeared capable of tolerating emotionally led us to detailed exploration of the life histories of 286 of our patients. Here, we unexpectedly discovered that histories of childhood sexual abuse were common, as were histories of growing up in markedly dysfunctional households. It became evident that traumatic life experiences during childhood and adolescence were far more common in an obese population than was comfortably recognized.2 We slowly discovered that major weight loss is often sexually or physically threatening and that obesity, whatever its health risks, is protective emotionally. Ultimately, we saw that certain of our more intractable public health problems such as obesity are often also unconsciously attempted solutions to problems dating back to the earliest years but hidden by time, by shame, by secrecy, and by social taboos against exploring certain areas of life experience. The antecedent life experiences of the obese are quite different from those of the always-slender.3 Eventually, these Program findings led to the 17,000-member Adverse Childhood Experiences (ACE) Study, in which we established that the developmental damage initially discovered in our obese patients was broadly applicable to many aspects of everyday medical practice.4,5 Ultimately, we learned from our patients that in obesity, we are dealing with two core problems: • The unconscious, compulsive use of food for its psychoactive benefits • The unrecognized and unspoken benefits of obesity. These two core problems are markedly at variance with conventional thinking about obesity, starting with the government’s food pyramid. Worse yet, these two basic problems are uncomfortable to deal with. In reviewing the medical literature, one quickly notes that most articles purporting to discuss the causes of obesity quickly switch to describing the unhealthy consequences of obesity and never pursue their stated goal. One also notes the tendency to confuse intermediary mechanism with basic cause. For instance, several years ago, leptin deficiency was proposed as the cause of human obesity. Although that idea has now been discarded, someday the “real leptin” will be discovered, but it will no more be causal than increased levels of epinephrine are the cause of anxiety. Each is a necessary intermediary mechanism, not a basic cause. Understanding the difference is as essential to progress in treatment as it is to primary prevention. Any physician choosing to validate in his patients the points being made here will be in the position of asking about topics that we have all learned are not discussed by polite people. Incest, rape, family suicides, and parental brutality are not readily brought up. That being the case, we physicians typically have no basis for opinions on the frequency or rarity of such life experiences. We documented these experiences as surprisingly common among our patients, but we did not know that before we began routinely inquiring about them. Counterintuitively, we learned that discussion of these experiences is usually not uncomfortable to those who have had them, if they are supported by someone comfortable with their discussion. Patients often find a great sense of relief in discussing their life experiences. As one patient wrote, “The shame, guilt, and pain for the abuse and molestations of childhood, and being raped, was so great that I had to come forward or die. If your questionnaire had been put in front of me, it would have shown me that people existed in the medical profession who knew about the sad things that happen to some people.” This poignant statement imposes a huge responsibility on us that we can of course avoid by falling back on lack of time or lack of training as being the factor that precludes our inquiry. The now internationally recognized ACE Study was initiated to determine the prevalence and outcomes of ten categories of such life experiences in more than 17,000 consecutive adults from KP’s San Diego population.6 These experiences are common, and their consequences are devastating in terms of emotional damage, biomedical disease, and the costs of health care. Like a child’s footprints in wet cement, the consequences are lifelong. Putting it plainly in regard to obesity, we have seen that obesity is not the core problem. Obesity is the marker for the problem and sometimes is a solution. This is a profoundly important realization because none of us expects to cure a problem by treating its symptom. Treatment Given the nature of our observations about the causes of obesity, repeatedly documented in thousands of responses to our preprogram questionnaire (See http://www.thepermanentejournal.org/files/Obesity/PreprogramQuestionnaire.pdf to view the questionnaire) and in more than 50 videotaped interviews, it was inevitable by the early 1990s that we revise our program to fuse two separate goals: weight loss by supplemented fasting, and helping patients identify and resolve the life experiences underlying obesity. By far the easier of the two goals is the medical management of supplemented absolute fasting. Weekly checks of potassium levels, blood pressure measurements in patients taking antihypertensive medications, and blood sugar levels in patients with diabetes are our most common tracking measures other than weight itself. Other details of biomedical management are equally straightforward but are not the point of this article. Chronic disease is not a reason for exclusion from the Program; most such patients should actually be sought for Program inclusion if obese. Our only absolute exclusions are pregnancy and recent myocardial infarction or stroke. Optifast 70, drunk five times daily for a total daily intake of 420 cal, is a remarkable material that makes biologically safe the otherwise unthinkable. The remainder of the day’s caloric needs come from body fat stores as long as those fat stores exist. It is important to understand that Optifast 70 has one function only: the prevention of death from prolonged absolute fasting. It does not take weight off people; not eating does that. And it has nothing to do with whether lost weight is regained or kept off; that outcome is solely a function of what is accomplished or not accomplished by the group work of the Program. By contrast with the simplicity of fasting, the weekly two-hour group meetings of the Program are a complex endeavor that is difficult for some patients to engage in and is difficult to train staff to pursue vigorously. By the mid-1980s, we had learned that our initial goal of teaching people to “eat right” was totally irrelevant to obesity, although it seemed a reasonable thing to do when we did not know what to do. In retrospect, we should have known better because most of us knew that overweight, middle-aged women commonly know enough about calorie content to give a dietitian a run for his or her money any day of the week. Nutrition is an interesting and important subject that has no more relationship to obesity than it does to anorexia. The role of the Program is to help people recognize and find an acceptable alternate solution or resolution to the underlying problems being treated with food. We are at an early stage of success; the work is difficult because it is resisted by some patients and can awaken personal ghosts in staff, but we have clearly established a beachhead on the right beach and slowly are moving inland. In the course of detailed interviewing of about 2000 obese patients over the past 20 years, in-depth and often repetitively over time, we have noted several recurrent findings: • It is rare for anyone to be born obese. In 2000 adult obese patients, only one individual was born overweight, at 14 lb (6 kg), to a 550-lb (250-kg) mother, and she was slender throughout childhood and adolescence until age 20, when she married an alcoholic and suddenly began massive weight gains, ultimately matching her mother’s weight. “Born fat” is a defensive concept. • A significant minority of our Program participants are born at subnormal weight because of prematurity. • Obesity indeed runs in families, as does speaking the same language. It is the distribution pattern of body fat deposition that is genetically determined, not its presence. • Major weight gain is typically abrupt, episodic, and life-event related. • The forces underlying extreme morbid obesity are relatively easy to discern for those seeking them. They are qualitatively similar to those underlying mild overweight, though they are much harder to discern in the latter. • The age at which weight gain first began is critically important because it allows one to inquire why it began then. Some patients will know and others will not want to know, but this is an essential point not to be dropped because of patient avoidance. • Obesity commonly is beneficially protective: sexually, physically, and socially. This is an uncomfortably difficult point for many nonobese individuals to accept. • Major weight loss may present a significant threat, usually to the person involved, but sometimes to others. • Emotional support from others for major weight loss is uncertain. With adequate medical monitoring, there is no biologic risk to supplemented absolute fasting. Supplemented fasting has two treatment advantages: • When large amounts of weight are to be lost, it reduces weight quickly enough to provide positive and supportive feedback. • By removing eating as a major coping device, we expose the underlying issues that are being treated by the psychoactive properties of food. The main work of the Program enters personal territory that is comfortably off-limits to polite people. It is therefore difficult and demanding, though conceptually simple. Doing the work in groups is essential because of the implicit support of the group and because participants quickly learn from each other’s self-observations. To the degree that counselors pose meaningful questions to their groups, and insist on answers to the questions asked and not to some enfeebled version of their questions, they are successful. To the degree that they teach by lecturing, they fail. In actual fact, our task is to help the participants discover what they already know at some level, and then to use that discovery for their own benefit. To illustrate the process, some seemingly simple questions may be offered for our readers to try, understanding that this works best in small groups and initially will be stressful for the group leader: 1. Why (not how) do you think people get fat? 2. How old were you when you first began putting on weight? Why do you think it was then and not a few years earlier or later? 3. Sometimes people who lose a lot of weight regain it all, if not more. When that happens, why do you think it happens? 4. What are the advantages of being overweight? Patients’ answers to these questions are staggeringly counterintuitive to conventional thinking about obesity. Moreover, their answers have been consistent over the many years we have posed these questions in group sessions. For instance, answers to question 1 routinely are: “stress, depression, people leave you alone, men won’t bother you.” There are of course occasional escapist responses like “I just like food.” In that case, the following response to the answer given for question 2 is helpful: “Really? Can you tell us why you suddenly liked food more at 22 when you first began putting on weight?” Responses to question 3 always are versions of “If you don’t deal with the underlying issues, the weight will come back.” About 60% of the time, someone in a group will also propose that regain occurs because major weight loss is threatening. Answers to question 4 repeatedly fall into three categories: obesity is sexually protective; it is physically protective (eg, “throwing your weight around”); and it is socially protective—people expect less from you. Ultimately, we were forced to recognize that patients in a supportive setting speak of things that we ourselves may find it easier not to know. This embarrassing recognition exposes the tempting opportunity that a physician or group leader has to become part of the problem by authenticating as biomedical disease that which is actually the somatic inscription of life experience onto the human body and brain. The frequent reference to “the disease of obesity” is grossly in error, diagnostically destitute, and apparently made by those with little understanding of the antecedent lives of their patients. Obesity, like tachycardia or jaundice, is a physical sign, not a disease. What we have learned about obesity has been more widely applicable in everyday medical practice than we would ever have contemplated. The general principles underlying the unconscious, compulsive use of food as a psychoactive agent are common to any of the addictions. We unwittingly recognized this at some level in the early years of the Program by giving as gifts, coffee mugs bearing the inscription, “It’s hard to get enough of something that almost works.” The psychoactive benefits of food are profound though not curative: “Sit down and have something to eat; you’ll feel better.” Hunger is not at issue in that saying. Whether we are talking about the next mouthful, the next drink, the next cigarette, the next sexual partner, or the next dose of whatever psychoactive chemical we might buy on the street, the concept is equally applicable: It’s hard to get enough of something that almost works. Slowly, we have come to recognize that overeating is not the basic problem. It is an attempted solution, and people are not eager to give up their solutions, particularly at the behest of those who have no idea of what is going on. Nor is obesity the problem. Obesity is the consequence, the marker for the problem, much in the way that smoke is the marker for a house fire. Often enough, obesity is even the solution—to problems that are buried in time and further protected by shame, by secrecy, and by social taboos against exploring certain areas of human experience. A memorable response comes to mind from 1985 when a patient, going with us through a timeline of her life in which weight, age, and events were matched, told us that at age 23 she was raped and that in the subsequent year she gained 105 lb (48 kg). Looking down at the carpet, she then muttered to herself, “Overweight is overlooked, and that’s the way I need to be.” Not knowing how to respond at the time, we said nothing. A few weeks later when she had lost 35 lb (16 kg), enough to be noticeable, she abruptly disappeared for 2.5 years, quickly regaining the weight. When she attempted to rejoin the Program after that hiatus, we discovered that she had no recollection of this conversation. Prompted by this to look into the issue of amnesia, we found in a sample of 300 consecutive obesity program patients that 12% acknowledged a history of focal amnesia, typically for the few years antecedent to the onset of weight gain. Amnesia is a high-grade marker for dissociation, which is a high-grade marker for abuse.7 Just as no one becomes amnesic because of good experiences, no one becomes fat out of joy. Depression is common in the Program and is a major stumbling block to weight loss. Not surprisingly, until the recent advent of pharmacologic blockers of fat absorption, every single “diet pill” save one has had potent antidepressant activity. The exception was fenfluramine, whose potent antianxiety activity was linked with the antidepressant phentermine as the first component of fen-phen. These medications can play a useful supportive role, but it should be understood that what is being treated is depression or anxiety, the consequences of antecedent life experiences, and not obesity per se. Overall, we have found and documented that the antecedent life experiences of the obese are quite different from those of the always-slender.3 Subsequent to the 20-week weight-loss phase of the Program, we have a 12-month Maintenance Phase. Initially thinking that this was necessary to teach people how to eat right, we slowly came to see that Maintenance indeed is essential, but for other reasons: to provide group support when major weight loss is threatening, usually to the person involved but sometimes to those who are close. Some of our patients regain all their weight, and others do not. The question we posed was: What are the differences between those who regain and those who do not? We have identified two major predictors of regain: a history of childhood sexual abuse and currently being married to an alcoholic.8 The latter can probably be generalized into having a significantly dysfunctional marriage, but that concept was too nebulous to study as an outcome. Today the prevalence of obesity is rapidly increasing in children. Although our experience with obese children is quite limited, we are impressed by the number of adults who date the onset of their initial weight gain to coincide with parental loss in childhood, usually by divorce. Our most obese female patient, weighing 840 lb (381 kg) at age 29, was born weighing slightly less than 2 lb (0.9 kg) and was thin until her parents divorced when she was 11 years old and she never again saw her father. By age 17, she weighed 500 lb (227 kg). This correlation with parental divorce has escaped general attention, although a search in Google Scholar using the phrase childhood obesity divorce quickly indicates its presence in the literature. Given the high prevalence of divorce in the US, we suspect that “McDonald’s” may be a more comfortable explanation for childhood obesity, although it obviously misrepresents mechanism as cause. Bariatric surgery has been increasing in popularity since its initiation in 1967 by Edward Mason, the remarkable Iowa surgeon who introduced gastric bypass surgery to the US.9 Our own experience in the Program with bariatric surgery is biased because we see a disproportionate number of cases where “the surgery failed” and patients consequently enter the Weight Loss Program. We have found alternate explanations that are not usually considered. An unexpectedly clear insight was provided by a recent patient comment: “The antidote [sic] to bariatric surgery is Karo Syrup.” The psychological implication is blatant; the physiologic insight is ingenious. One may not be able to chew one’s way through a lot after bariatric surgery, but the ability to ingest highly caloric liquids is unlimited. The question, of course, is: Why would a patient do that? A different take on bariatric surgery is depicted in a brief video clip of an interview with a patient available at: http://www.thepermanentejournal.org/files/Obesity/EllaHNoBariatricSurgery.avi. These comments from patients are, once again, counterintuitive to conventional views about obesity. We have slowly learned that our average patient on the one hand wants very much to lose weight but on the other hand often has significant unconscious fear of the changes that major weight loss will bring about. In keeping with this unexpressed conflict, it is worth remembering that opposing forces are routinely present in biologic systems. Outcomes We have measured our Program outcomes in three categories: • Weight loss • Maintenance of weight lost • Benefits of weight loss. The average weight loss in one 20-week cycle of our program has been 62 lb (28 kg). The most anyone has ever lost in our former 26-week cycle was 157 lb (71 kg). This was a highly motivated man with a large underlying muscle mass. Eighteen months after completion of the Program, half of our patients are keeping off 60% or more of the weight lost. These are old data and have probably improved with the revised Program, but we have not restudied the point. Instead, we have studied the differences between those who regain and those who do not.8 Our ability to predict regain offers the possibility for preventive treatment in advance. The biomedical benefits of such major weight loss have been dramatic. Of 400 consecutive patients taking medication for hypertension who completed the Program, 62% were able to discontinue all medication and no longer had hypertension. Of 400 consecutive patients with hypercholesterolemia, the average starting cholesterol level was 285 mg/dL; the average cholesterol level for those completing the Program was 204 mg/dL. Most impressively, of 320 patients with Type 2 diabetes who completed the Program, 71% were able to discontinue medication and had normal fasting blood sugars. In terms of health care economics, there is a 25% reduction in physician office visits while patients are in the Program and a 40% reduction in such visits in the subsequent year. Certainly, some of this is due to a reduced disease burden, but we suspect that a significant portion is due to reduced emotional distress in patients who have been helped in supportive settings to speak of the worst secrets of their lives and have been enabled to emerge feeling still accepted as human beings. Summary We have had an unusual opportunity to become deeply involved in the treatment of major obesity since 1985. What we have counterintuitively learned from that experience is that obesity, though an obvious physical sign and easily measured, is not the core problem to be treated, any more than smoke is the core problem to be treated in house fires. Supplemented absolute fasting is a highly effective treatment for obesity, but only if it is combined with a meaningful program that is designed to help patients explore the psychodynamic issues that underlie overeating as a coping device, as well as exploring the possible protective benefits of obesity itself. The work is difficult because it threatens social conventions and beliefs and often awakens personal ghosts in staff. This can lead to nonalignment of purpose and reminds us of Michael Balint’s famous comment, “Patients see doctors because of anxiety, while doctors see patients because of disease. Therein lies the problem between the two.”10 Although our work with obesity is difficult to carry out, we have nevertheless found that the work we have described can be done and that the benefits are major. v Disclosure Statement The author(s) have no conflicts of interest to disclose. Acknowledgment Katharine O’Moore-Klopf, ELS, of KOK Edit provided editorial assistance. References 1. Keys A. Biology of human starvation. Minneapolis: University of Minnesota Press; 1950. 2. Felitti VJ. Long-term medical consequences of incest, rape, and molestation. South Med J 1991 Mar;84(3):328–31. 3. Felitti VJ. Childhood sexual abuse, depression, and family dysfunction in adult obese patients: a case control study. South Med J 1993 Jul;86(7):732–6. 4. Felitti VJ, Anda R, Nordenberg D, et al. Relationship of childhood abuse and household dysfunction to many of the leading causes of death in adults. The Adverse Childhood Experiences (ACE) Study. Am J Prev Med 1998 May;14(4):245–58. 5. Felitti VJ. The relation between adverse childhood experiences and adult health: turning gold into lead. Perm J 2002 Winter;6(1):44–7. 6. Felitti VJ, Anda RF. The relationship of adverse childhood experiences to adult health, well-being, social function, and healthcare. In: Lanius R, Vermetten E, Pain C, editors. The impact of early life trauma on health and disease: the hidden epidemic. Cambridge, UK: Cambridge University Press; in press 2010. Chapter 8. 7. Edwards V, Fivush R, Anda RF, Felitti VJ, Nordenberg DF. Autobiographical memory disturbances in childhood abuse survivors. In: Freyd JJ, DePrince AP, editors. Trauma and cognitive science: a meeting of minds, science, and human experience. New York: Haworth Maltreatment and Trauma Press; 2001. p 247–64. 8. Felitti VJ, Williams SA. Long-term follow-up and analysis of more than 100 patients who each lost more than 100 pounds. Perm J 1998;2(3):17–21. 9. Mason EE, Ito C. Gastric bypass in obesity. Surg Clin North Am 1967 Dec;47(6):1345–51. 10. Balint M. The doctor, his patient, and the illness. Rev ed. New York: International Universities Press; 1972.
An Alternate Model for Medical Education: Longitudinal Medical Education Within an Integrated Health Care Organization— A Vision of a Model for the Future?
Monday, 30 August 2010
Innovation Quentin Eichbaum, MD, PhD, MPH, MFA, FCAP; Tim Grennan, MD, FACP; Howard Young, MD; Myra Hurt, PhD Fall 2010 - Volume 14 Number 3 Editor’s note: This article was developed as a hypothetical model from the June 2009 session of the Harvard Macy Institute—Program for Leading Innovations in Healthcare and Education on innovations in medical curriculum. As the health care debate in the US rages on, we need also to examine whether our medical education system is keeping pace with the changing landscape of medicine and how well it will cope with the proposed changes in health care delivery. Are we graduating sufficient numbers of physicians in the correct specialties and in a timely manner? Are medical trainees being adequately trained for the molecular and digital revolutions in science and technology? Are there other models of medical education outside of the universities that we might explore for training outstanding physicians in America in the 21st century? We propose situating a medical school program within one of the larger progressive, nonprofit, integrated, managed care organizations in the US. At first, this may appear an audacious suggestion. The recent health care reform legislation and current policy discussions suggest that these integrated delivery systems may become the model for future care delivery. It seems legitimate to try to use their strengths in seeking solutions to the country’s health care dilemmas. From this perspective, we suggest that situating modular and longitudinal medical education within a progressive integrated health care system such as a large, multispecialty group model, nonprofit health maintenance organization might provide a valid alternate stream of education and training for physicians (and other health care workers). It could draw its trainees from a broader but ultimately not less deserving pool of applicants and potentially also help alleviate certain health care worker shortages. We conceive of this alternate medical education course operating alongside the traditional university-based medical schools rather than replacing them. We suggest the hypothetical name Kaiser Permanente School of Medicine (KPSOM) to exemplify the alternative model we describe. Kaiser Permanente (KP) is a large, integrated, prepaid Health Plan with 8.6 million members and more than 14,000 physicians in eight Regions.1 The organization has established for itself a solid reputation as a progressive health care delivery organization with a focus on preventive, patient-centered care and patient satisfaction. The KPSOM for the training of health care workers would be one that 1) uses the existing structures of a progressive health care management organization (with existing graduate physician-training programs) and does not require the construction of new medical schools; 2) co-trains physicians, physician’s assistants, nurses, nurse practitioners, and potentially even health care administrators; 3) has a streamlined and less costly admissions process and functions alongside traditional university-based medical schools; 4) acknowledges the student-centric learning style and computer proficiency of the incoming Millennial Generation (or Generation Y) students; 5) maximizes human potential by taking into account differences in learning styles and accommodating self-paced modular learning; 6) increases the number of physicians (as well as other health care workers) by drawing on a pool of applicants, some of whom may conventionally be considered underqualified for admission but will prove to be equally qualified after training; and 7) enhances opportunities for medical careers to students from economically disadvantaged backgrounds. Applicants to the Kaiser Permanente School of Medicine A central component of the school would be the admission and training of what we call the pluripotential health care worker. The baseline 1 to 3 years of learning in this school (depending on how the students pace their learning) would involve the training of a generic or pluripotential student apprentice who would be well versed in both basic science and basic medical skills at a level of competence necessary for medical students, physician’s assistants, and nurses or nurse practitioners. Because baseline training before specialist training would be pluripotential, applicants could also be selected from a broader background of applicants. In particular, applicants from underprivileged and underserved areas might be accepted into the program because learning in the program is self-paced and modular in nature, with backup mentoring and academic support (as described in the following section). The school would be attractive to a diverse range of students, including those from resource-poor settings; students interested in a career in health care but undecided about the specific direction; students who prefer the option of self-paced learning; and students attracted by the option of remaining within a large organization for residency, fellowship, and subsequent employment opportunities. An advantage of this hypothetical model would be that it could function without some of the current constraints that render the current admissions process to university medical schools cumbersome, expensive, and drawn out. Students applying to the KPSOM would not need to apply to and interview at numerous medical schools. The current highly competitive system is draining and costly and entails students crossing the country for multiple interviews and schools investing substantial time and money into screening applications and interviewing students—overall, an exhausting, time-consuming, and costly process. This new hypothetical institution might not require the MCAT (Medical College Admission Test) for admission, because it would conduct its own in-house assessment of candidates. It would not directly compete with university medical schools because it would accept trainees from a wider pool of applicants and nurture them within the organization to the required level of competence. The school would conduct its own in-house evaluations, monitored by the Liaison Committee on Medical Education (LCME), of students it admits. These could take the form of an initial basic competency test, followed by formative and summative testing as students progressed through the modular self-paced learning system (see the next section). This progressive admissions policy would allow applicants from a broader range of educational backgrounds, not only from elite schools but also from underserved areas. This would make for a healthy diversity among trainees. It has been recently noted that about 75% of US medical students come from the upper wage-earning quintile of the population. According to a report on the Web site of the Association of American Medical Colleges (AAMC), the Matriculating Student Questionnaire, All Schools Summary Report for the years 2006, 2007, and 2008, 69% to 71% of students reported that their parents’ gross income was $75,000 or more, and the average was between $149,779 (2006) and $164,483 (2008). In these same years, 15% or less reported that their parents’ gross income was less than $40,000.2 In keeping with the community mission of KP, this new training model could help redress this imbalance by accepting minority and less-privileged students. Recruitment from a wider pool of applicants would likely also increase numbers of medical, nursing, and physician’s assistant graduates and might have the added consequence of increasing the supply of qualified health care workers to underserved areas. Modular Self-Paced Learning Education and training at this new school would be modular and self-paced but would be buttressed with sophisticated academic support and mentoring. An organization the size of KP has ample resources to provide such academic support. Students would not study in lockstep with the entire class being at the same point in the curriculum at any one point, as in most current medical school curricula, but would instead pace their own learning. Coursework would be completed in modules, and trainees could be tested for competency at critical steps in their learning before being permitted to move on to the next learning module. Modular learning in the basic sciences would be largely Web based. Because it would not be a classic university, this new alternative medical school would not employ basic science faculty for lecture-style teaching. The school might partner with universities for parts of the basic science teaching. Students would be assigned (as apprentices) to KP clinical faculty members, many of whom are already clinical faculty members at local universities and are engaged in the teaching of graduate physicians. The students would shadow the faculty in clinics and hospitals while they also engaged in completing modules in clinical skills. Students would not be permitted to proceed to the next level of learning in the basic sciences or clinical skills until they had demonstrated adequate competency at each prior level of learning. Although the program would be self-paced, there would nonetheless be a limited time frame for completion of specific tracks (possibly five to seven years). We envisage students learning the basic sciences concurrently with clinical skills so that concepts from these two spheres of knowledge would reinforce each other. The specifics of the school’s curriculum model would remain to be deliberated but would be based on recommendations of the AAMC for small interdisciplinary group teaching that would incorporate aspects of problem-based and team-based learning as well the more recent recommendations of the Carnegie Foundation’s 2010 report for supportive learning environments that encourage curiosity, encourage feedback improvement, and promote learners’ ability to work collaboratively in health care teams.3 As recommended in the Carnegie Foundation report, the KPSOM would also, through its apprenticeship model, incorporate more clinical experiences earlier in the curriculum. Examples of current curricula that may provide guidance are Harvard Medical School’s New Pathway MD Program (http://hms.harvard.edu/admissions/default.asp?page=pathway); the symptom-based curriculum of Calgary Medical School in Canada (www.medicine.ucalgary.ca/) and the new Paul L Foster Medical School in El Paso, Texas (www.ttuhsc.edu/elpaso/); and the “longitudinal integrated” clerkship curriculum of the Cambridge Health Alliance and Harvard Medical School (www.cha.harvard.edu/academics/integrated_clerkship.shtml) in Boston. It is anticipated that the students would learn better and more quickly because the program would be embedded in an integrated health care system. While proceeding with their modules in the basic sciences, students would work at KP as clinician apprentices. Initially, they would do very basic clinical work while shadowing experienced physicians in clinics and hospitals, and only after demonstrated basic clinical competencies would they proceed to more self-reliant clinical work. Millennial Generation or Generation Y: Self-Based Style of Learning A curriculum of self-paced modular learning has a number of advantages. First, it would accommodate differences in students’ learning styles and would be advantageous to students from challenged backgrounds by allowing them to proceed through the program at their own learning pace (within certain time limits). Second, it would accommodate the self-based learning style of the “Millennial” or “Generation Y” students who are generally adept at computers and are swift at information retrieval from the Internet, who ostensibly have shorter attention spans than students in past generations, and who prefer to take charge and be at the center of their own learning.4 Third, it would take account of the exponential increase in medical knowledge by presenting it in modular form and allowing students to pace their learning. The Pluripotential Baseline Trainee The first benchmark phase of the KPSOM would be the training of a pluripotential health care worker who would subsequently proceed with more specific training along designated tracks toward becoming a physician, physician’s assistant, nurse, nurse practitioner, or health care administrator. Each track would have graduated levels of competency in training, and trainees would have to demonstrate adequate competency at each level before being admitted to the next. Many students might know from the start which graduation track they wish to pursue, but all would initially go through the gatekeeping pluripotential track, during which they would also be tested for their natural learning styles, aptitude, and acquired competencies before being admitted to the graduation track of their choice. Such monitoring would maximize human potential because there would presumably be a closer fit between candidates’ aspirations and their true capabilities. A trainee who did not qualify for the physician track might still be offered the choice of the less demanding physician’s assistant track. After completion of the basic gatekeeping pluripotential track, the different tracks would, however, not be melded but would be separate and have strict competency attainment requirements. This hypothetical new school could afford having different tracks of health care professional training because unlike a university medical school, it would ultimately offer employment to most graduates in the different tracks. Regarding administrative regulation of the school, the LCME—which currently appears to be interested in innovative projects in medical education—would maintain its standard accrediting and regulatory role at all stages of the school’s development, as it does for all other US medical schools. Students would be required to pass the standardized National Board of Medical Examiners subject examinations as well as the US Medical Licensing Examination steps 1, 2, and 3 for licensure. In any case, in 2010, the centennial year of its groundbreaking Flexner Report, the Carnegie Foundation released another call for reform, Educating Physicians: A Call for Reform of Medical School and Residency,3 in which it drew attention to the need for reform with regard to admissions, accrediting, certifying, and licensing in medical education in a manner that resolves conflicts but ensures diversity of medical schools. The first two of the report’s seven recommendations read as follows3: AAMC and medical schools work together to revise premedical course requirements and admission processes, ensuring the diversity of those in medical schools. Accrediting, certifying, and licensing bodies together develop a coherent framework for the continuum of medical education and establish effective mechanisms to coordinate standards and resolve jurisdictional conflicts. Students as Reduced-Tuition Employees of the Organization Tuition would be reduced because students would be admitted as part-time employees and would perform, in their roles as clinical apprentices, basic clinical service functions for the organization’s clinics and hospitals. Conceivably, as employees they might also receive a reasonable stipend to cover living expenses. Analogous education models exist within engineering schools in which students may spend half the year within the university and the other half employed by an engineering firm (Richard K Miller, personal communication, May 2009).a,5 The organization would ensure that appropriate supervision is provided at all times to quarantee that patient safety and quality of care is maintained.Students of the new school would graduate with less financial debt than students of university medical schools and would therefore not be unduly influenced by considerations of the size of tuition loans in their choice of medical specialty training, as is happening with current medical school graduates applying for residency. Moreover, a less costly system may be enticing to students from disadvantaged educational backgrounds as well as to more accomplished students from better endowed institutions. This would enhance the diversity of the school’s student population and may ultimately also increase the numbers of physicians choosing to return to work in resource-poor settings. The financing of the school itself, which may require some additional infrastructure but little physical construction, may come from KP itself, particularly if it viewed the venture as a good investment. Because the school would attract students from resource-poor settings, additional financing might be obtained via the federal government, such as through new health care legislation,6 or through state support, or from large philanthropic organizations with an interest in education such as the Carnegie or Rockefeller Foundations. The Lifelong Medical School: Residency, Fellowship, Cross-Training, and Continuing Medical Education The KPSOM would continue and expand its own in-house residency and fellowship programs that encompass a number of medical specialties and subspecialties. Medical student trainees would apply from within the organization for specialty training at any one of its many hospitals. Because the medical school and residency programs would be housed within the same organization, applications for residency would also be greatly facilitated. The drawn-out and costly process of the current residency application and cross-country interview process, which consumes the better part of the fourth year of medical school, would be obviated. This time saving could eliminate a year of medical training for the motivated, quicker-paced student or else provide the additional time required for the slower-working, self-paced student. During their ‘medical school’ training, students would be carefully monitored, evaluated, and assessed for their aptitudes and learning styles in deciding about residency. The processing of applications from within the organization would not only streamline the process but also might improve quality control and standardization of applications. Residency programs would also be largely modular in structure and self-paced for the learning of clinical competencies. Although there might be some loss of diversity among residents who all derive from the same organization, compared with residents entering from a variety of different medical schools, the gain to the residency program would be in having a more carefully monitored, standardized, and appropriately matched (by aptitude, learning style, and intellectual capability) program of residents. Students would not be required, however, to complete all their clerkships and rotations within the school but would be encouraged to do rotations outside of KP, which already has formal affiliations with medical schools such as those with the University of California, San Francisco; Stanford University; the University of California, Los Angeles; the University of California, Davis; the University of Southern California; and the University of California, Berkeley (public health). Depending on their examination grades, performance, and recommendations, students from KPSOM applying for rotations, residencies, and fellowships outside of the organization should be readily competitive with students from other medical schools. Applications to outside programs should not present a compatibility problem, as KP already interfaces with several such residency programs. The program might also admit a limited number of residents from other US medical schools as well as graduates of foreign medical schools, who would also be carefully assessed and then slotted into the appropriate phase of the training program. Currently, international medical applicants to US residency programs are required to repeat their entire residency training regardless of their prior training and competency. In this proposed alternative medical school, foreign residency applicants would nonetheless still have to pass US medical board examinations and satisfy all LCME accrediting requirements. Applications to fellowship programs, which would also be in-house, would be similarly handled. The proposed KPSOM would also readily accommodate cross-training of its employed physicians into different associated subspecialties, a trend that is occurring increasingly as medical knowledge expands. For instance, the increasing role of invasive radiologic techniques and laparoscopic surgical techniques has changed management in a variety of surgical disciplines. Finally, continuing medical education programs would be easier to implement and monitor from within the organization, whereas the current system of accumulating continuing education credits is often seemingly haphazard and fragmented. Continuity of Care, Preventive Care, and Patient Satisfaction in the Lifelong/Longitudinal Medical School Because most trainees would continue their training within the organization initially as medical students, then as residents, fellows, and finally as fully employed physicians, they could provide better continuity of care for patients over this extended period of participation in the organization. This would lead to both enhanced patient care and, as a consequence, overall higher levels of patient satisfaction. Instead of experiencing continual disruptions in their care with frequent changes in physicians and hospitals, patients would continue to see the same physicians they initially encountered when these physicians were medical students or residents and who would therefore have a more substantial grasp of their ongoing health care needs over time. In addition, with enhanced continuity of care, the organization could implement highly effective longitudinal preventive-care programs, which would lead to improved health outcomes and patient satisfaction. The integrated modular nature of this course would allow for flexibility in learning styles to be matched with the flexibility that would be needed of the future workforce. It would promote the concept of teamwork at an early stage, improve communication between trainees and teachers, and redefine the apprentice model in the 21st century. Summ ary In brief, the hypothetical KPSOM could be envisaged as a model of a lifetime medical school that would initially draw candidates from a diverse socioeconomic pool of applicants and guide them through a series of carefully monitored, modular, self-paced basic science and clinical skills learning programs, up to a phase where they would branch out into specialty programs leading to graduation as physician, physician’s assistant, nurse, nurse practitioner, or health care administrator. Tuition would be less costly because students would also be employees of the organization and would likely remain in the organization throughout their extensive training careers, from medical school and into subspecialty certification—and possibly as full-fledged physician employees. This system would be satisfying to patients as well as students because it would provide more effective longitudinal and preventive care. The model is offered as an alternate stream of medical education that would not supplant university medical schools but would operate alongside them. This alternate model might serve to increase the number of qualified physicians without the need to build more costly medical schools, and it would train a broader range of health care professionals from diverse backgrounds within the same organization. a    President, Franklin W Olin College of Engineering Disclosure Statement The author(s) have no conflicts of interest to disclose. Acknowledgments We gratefully acknowledge Elizabeth Armstrong, PhD, Director of the June 2009 session of the Harvard Macy Institute—Program for Leading Innovations in Health Care and Education and our seminar group for the ideas generated in the group on innovations in the medical curriculum. Katharine O’Moore-Klopf, ELS, of KOK Edit provided editorial assistance. References 1.    Fast facts about Kaiser Permanente [monograph on the Internet]. Kaiser Permanente News Center. Oakland, CA: Kaiser Permanente; © 2010 [cited 2010 Jul 5]. Available from: http://xnet.kp.org./newscenter/aboutkp/fastfacts.html.2.    Matriculating Student Questionnaire, All Schools Summary Report [Web page on the Internet]. Washington, DC: Association of American Medical Colleges. © 1995–2010 [cited 2010 Jul 5]. Available from: www.aamc.org/data/msq/start.htm.3.    Cooke M, Irby DM, O’Brien BC. Educating physicians: a call for reform of medical school and residency. San Francisco: Jossey-Bass; 2010.4.    Baron RA. Why it’s important to export our field—and how we can do it effectively. In: Saville BK, Zinn TE, Meyers SA, Stowell JR, editors. Essays from e-xcellence in teaching, 2006. Washington, DC: Society for the Teaching of Psychology; 2006 [cited 2010 Jul 7]. Available from: http://teachpsych.org/resources/e-books/eit2006/eit06-05.pdf.5.    Miller RK. President’s message [monograph on the Internet]. Needham, MA: Franklin W Olin College of Engineering; 2010 [cited 2010 Jul 7]. Available from: www.olin.edu/about_olin/presidents_message.asp.6.    Patient Protection and Affordable Care Act of 2010, Pub L. No. 111-148, 124 Stat 119. Title V. Health Care Workforce; Subtitle B: Innovations in Health Care Workforce; Section 5101: National health care workforce commission; Section 5102: State health care workforce development grants. Available from: http://www.gpo.gov/fdsys/pkg/PLAW-111publ148/pdf/PLAW-111publ148.pdf.
A Colorectal “Care Bundle” to Reduce Surgical Site Infections in Colorectal Surgeries: A Single-Center Experience
Monday, 06 August 2012
Waleed Lutfiyya, MD, FASCRS; David Parsons, MD, FASCRS; Juliann Breen, RN, CPHQ Summer 2012 - Volume 16 Number 3 Abstract Background: Kaiser Sunnyside Medical Center has participated in the American College of Surgeons National Surgical Quality Improvement Program (NSQIP) since January 2006. Data on general and colorectal surgical site infections (SSIs) demonstrated a need for improvement in SSI rates.Objective: To evaluate application of a “care bundle” for patients undergoing colorectal operations, with the goal of reducing overall SSI rates.Methods: We prospectively implemented multiple interventions, with retrospective analysis of data using the NSQIP database. The overall, superficial, deep, and organ/space SSI rates were compared before and after implementation of this colorectal care bundle.Results: Between January 2006 and December 2009, there were 430 colorectal cases in our NSQIP report with 91 infections, an overall rate of 21.16%. Between January 2010, when the colorectal care bundle was implemented, and June 2011, there were 195 cases and 13 infections, a 6.67% overall rate. The absolute decrease of 14.49% is significant (p < 0.0001). The rate of superficial SSI decreased from 15.12% to 3.59% (p < 0.0001). The rates for deep and organ/space SSI also showed a decrease; however, this was not statistically significant. The NSQIP observed-to-expected ratio for colorectal SSI decreased from a range of 1.27 to 1.83 before implementation to 0.54 after implementation (fiscal year 2010). Conclusions: Our institution was a NSQIP high outlier in general surgery SSIs and had a high proportion of these cases represented in colorectal cases. By instituting a care bundle composed of core and adjunct strategies, we significantly decreased our rate of colorectal SSIs. Introduction In the US, an individual who undergoes a major operation carries a 2% risk of surgical site infection (SSI). This rate is substantially higher if the patient undergoes colorectal surgery, with reported rates of 5% to 30%.1,2 In a recent claims study by Wick et al3 with more than 10,000 colorectal surgery patients, the 30-day readmission rate was 11.4%, the 90-day readmission rate was 23.3%, and the 30-day SSI rate was 18.8%. The mean readmission length of stay was 8 days, and the median cost for an SSI readmission was $12,835. These reports support the concept that interventions that reduce SSIs are likely to reduce length of stay and costs. SSIs represent an important target for surgical quality. Interest in improving surgical outcomes led to the National Veterans Administration Surgical Risk Study in the late 1980s,4 and from that, the National Surgical Quality Improvement Program (NSQIP) was developed in the mid-1990s.5 The American College of Surgeons NSQIP collects data on 135 variables from more than 300 different institutions around the country. NSQIP is the first nationally validated, risk-adjusted, outcomes-based program to measure and improve quality of surgical care. It provides participating hospitals risk-adjusted outcomes on a biannual basis and expresses them as an “observed-to-expected” (O/E) ratio. An O/E ratio below 1 indicates that the hospital is performing better than expected, and an O/E ratio greater than 1 indicates that a hospital is performing worse than expected. These reports are blinded, allowing participating centers to compare their risk profiles and outcomes with those of peer medical centers and with national averages. As a result, NSQIP has become a catalyst for the development of quality-improvement programs designed to advance surgical care. Several studies have demonstrated that institutions can improve outcomes by directing quality initiatives in areas where they seem to be outliers.6 Schilling et al7 examined 36 different procedure groups in the NSQIP and their relative contribution to morbidity and mortality, and they found that 10 procedure groups accounted for 62% of all complications. Colectomy, which composed 9.9% of all procedures, accounted for the greatest share of these adverse events. At the Kaiser Sunnyside Medical Center (KSMC) in Clackamas, OR, colorectal procedures composed 13.4% of all general surgery operations but made up 33% of all the SSIs. We hypothesized that colorectal operations should be targeted to decrease SSIs in general surgery. The purpose of this study is to evaluate the application of a bundle of care designed to reduce SSIs in patients undergoing colorectal operations. The NSQIP database was used to evaluate the efficacy of the colorectal care bundle. Methods Study Design The study design was prospective implementation of multiple interventions (Colorectal SSI Bundle) with retrospective analysis of data. KSMC has been participating in NSQIP since January 2006. Patients who underwent laparoscopic and open colorectal operations, whose data were submitted to NSQIP from January 2006 through June 2011, were included in the study. Patients were identified using Current Procedural Terminology codes (Table 1).8 Data were accrued into the NSQIP database by trained dedicated nurses, who prospectively collected information from the preoperative, intraoperative, and 30-day postoperative periods. Development of the Colorectal “Care Bundle” At KSMC, a 300-bed hospital in a large metropolitan city, approximately 250 to 300 major elective and emergency colorectal procedures are performed annually. In a review of our site-specific NSQIP data, general surgery SSI rates were statistically higher (high outlier) than at other NSQIP participating institutions. Between 2006 and 2009, we received 5 semiannual reports indicating that SSIs were an area of needs improvement. Inspired by our NSQIP risk-adjusted reports, in 2009 a program to eliminate SSIs at KSMC was developed, called “Pathway to Zero Surgical Site Infections.” There was a sense of urgency to drive down SSI rates. Colorectal surgery was identified as a subset of operations with the potential for high impact given their high rate of SSIs. On the basis of published literature, consensus views on feasibility, and recommendations from individual surgeons, the colorectal “care bundle” was proposed (Table 2). Education of general surgery attending physicians and house staff regarding elements of the care bundle was done before its implementation and has become a part of orientation for all new staff. The colorectal care bundle was implemented in January 2010. Compliance with the steps of the bundle was not prospectively tracked in all areas. Data Collection and Analysis The SSI rates were compared before and after implementation of the colorectal care bundle. Established NSQIP definitions for superficial, deep, and organ/space infections were used.9 The SSI rates were calculated every month, a run chart was developed (Figure 1), and quarterly reports were established. The SSI Quality Group’s monthly meetings allowed for tracking data and provided for opportunities to increase awareness for recommended SSI prevention strategies to all appropriate care providers. Each case of an SSI was identified and reviewed every month with regard to elements of the bundle. If any part of the bundle was omitted, the SSI was declared preventable and a standardized report regarding the specific case was provided to the surgeon. This allowed for identification of defects, and as they were identified, actions were taken, which included individual feedback and broad education to groups of providers. Some interventions were addressed more globally. One example was production of standardized tables for prophylactic antibiotics that were posted in the operating rooms and included appropriate redosing intervals and weight-based dosing guidelines. In addition, to decrease variation, the electronic medical record was leveraged to standardize the preoperative orders, which include elements such as oral antibiotics and mechanical bowel preparation. Also, SSI “dashboards” were created and posted in the surgeon and operating room lounges for data transparency. Every month the total number of documented SSIs was divided by the total number of patients at risk in that period and was expressed as the overall case rate. Rates for superficial, deep, and organ/space SSIs were calculated in a similar fashion. Case rates were compared by the difference of proportions test for two independent samples, before and after implementation of the colorectal care bundle (test for null hypothesis: H0: P1 − P2; 95% confidence interval limits set at α = 0.05). QI SPC Macros (1996-2011) version 2016.01 (KnowWare International; Denver, CO) was used for statistical analysis. Results Between 2006 and 2009, NSQIP captured 430 of the targeted Current Procedural Terminology codes, and overall there were 91 infections, a rate of 21.16%. In comparison, there were only 13 of 195 overall infections in the postintervention study period (January 2010 to June 2011), a rate of 6.67% (Table 3). This absolute decrease of 14.49% was highly significant (p < 0.0001). The rate of superficial SSIs decreased from 15.12% to 3.59% after the intervention, and this change was also highly significant (p < 0.0001). The rate of deep incision infections decreased from 1.2% to 0.5% after the intervention but was not statistically significant (p = 0.066). The rate of organ/space SSI decreased from 4.9% to 2.6% after the intervention, which was not statistically significant (p = 0.131). General surgery Class II cases had a significant decrease in overall SSI rates from 11.75% before the intervention to 5.31% after the intervention (p < 0.0001; Table 4). For fiscal years 2006 to 2009, KSMC was a statistically high outlier institution in general surgery SSIs in NSQIP risk-adjusted reports (Table 4); our O/E ratios ranged from 1.40 to 1.68. The overall rate of colorectal SSIs at KSMC was 21.16% compared with 14.44% at other NSQIP participating hospitals, a difference that was statistically significant (p < 0.001), and O/E ratios ranged from 1.27 to 1.83 during this 4-year period. The rate of superficial SSIs was 15.11% for KSMC compared with 8.44% for other NSQIP institutions, and the difference was statistically significant (p < 0.0001). The rate of deep and organ/space SSIs was not statistically different between KSMC and other NSQIP hospitals. After the intervention (2010 to 2011), there was a significant improvement in the O/E ratio in colorectal surgery SSIs at KSMC. In 2010, the O/E ratio was 0.54 and was the lowest since the Medical Center joined NSQIP. Compared with 2009, KSMC was no longer a high outlier institution. The rate of overall colorectal SSIs at KSMC was 6.67% vs 12.58% for other NSQIP hospitals, and this difference was statistically significant (p < 0.001). The rate for superficial SSIs at KSMC was 3.59% vs 7.19% for other NSQIP hospitals, a significant difference (p < 0.007). The rates for deep and organ/space SSIs between KSMC and other NSQIP hospitals were not significantly different (p < 0.084 and p < 0.210, respectively). Figure 2 shows the graphed rates of colorectal SSIs for both KSMC and NSQIP. In 2010, we also noted a corresponding drop in the O/E ratio for SSIs in general surgery to 0.70, placing KSMC in the low outlier category 1 year after implementation of the colorectal care bundle (Table 4). Discussion The most frequent complication after colorectal procedures is SSI,10 and few studies have been able to isolate results in such a way as to standardize care around the issue. One of the most challenging aspects of quality improvement has been the identification of best practice. The literature demonstrating direct cause and effect on relationships for a specific intervention is scarce, and there are few Category IA recommendations from the US Centers for Disease Control and Prevention (CDC). Recently, there has been some evidence that implementation of bundles of care elements can reduce the number of SSIs.11-13 The Surgical Care Improvement Project (SCIP), developed by the Centers for Medicare and Medicaid Services and implemented in 2006, was designed as an evidence-based initiative to be applied broadly across selected surgical services, with a stated goal of reducing morbidity and mortality rates 25% by the year 2010.14 The SSI reduction measures from SCIP include: 1) removal of hair with clippers, 2) use of appropriate antibiotics, 3) prophylactic antibiotics given intravenously in appropriate time, 4) discontinuation of antibiotics within 24 hours, and 5) maintenance of perioperative normothermia. These are so-called core strategies, based on high levels of scientific evidence with high levels of feasibility. However, the overall success of SCIP has been decidedly mixed. Hedrick et al15 reported a 10% reduction in colorectal infection rate (26% to 16%) following implementation of the SCIP protocols. In a study involving a larger sample of patients undergoing colorectal resection, the investigators observed a significant increase in compliance with SCIP process measures over 2 consecutive 14-month study periods (p < 0.001).16 However, this greater compliance did not result in a significant reduction of SSIs in patients undergoing colorectal procedures (p < 0.92).16 In a retrospective study using the Premier Inc Perspective Database (Charlotte, NC), SCIP compliance data for 405,720 patients from 398 hospitals were analyzed using a hierarchical logistic model. No relationship was found between adherence to SCIP process measures and occurrence of SSIs. Indeed, the authors documented an increase in SSIs despite substantial improvement in SCIP compliance over a 2-year period.13 Furthermore, the authors suggested that even if compliance had been 100%, the stated SCIP goal of 25% reduction in SSI was unachievable. At KSMC, despite following SCIP infection measures, NSQIP data continued to demonstrate high SSI rates. Like other researchers, we decided that the SCIP process has considerable shortcomings as a stand-alone intervention strategy.13,17 However, SCIP is the largest surgical patient safety and surgical infection reduction initiative in US history18 and should be viewed as more of a baseline to which other adjunctive strategies are added to create a total risk-reduction package. Supplemental strategies that have some scientific evidence with variable levels of feasibility are the adjunctive measures we added to complete the colorectal care bundle (listed below). These were deemed to be critical factors to achieve success in lowering the SSI rates. The SCIP infection measures were the base of the colorectal care bundle. Nurses and surgeons were trained in the importance of these processes. We sought to ensure consistent delivery of the interventions. Razors were removed from the operating room. Our anesthesia group “owned” (was responsible for) the normothermia measure and developed appropriate processes. Body warming devices were used in all cases. The electronic medical record was modified so that only approved and appropriate antibiotics could be chosen for prophylaxis and were given in the appropriate time frame before surgery. We expanded this SCIP measure so that it is best described as antibiotic management. Appropriate weight-based dosing and redosing based on duration of the case and the half-life of the antibiotic was addressed.19 Standard protocols were developed for the anesthesia team reflecting these factors as well. The SCIP does not evaluate all the important surgical quality issues; however, it does begin to give surgeons infrastructure on quality improvement.20 In completing the bundle, we added adjunctive measures and believe they played a critical role in reducing the risk for SSIs. Although these measures have some evidence to support their use, we recognize that some remain controversial and they have varying levels of feasibility. Adjunctive strategies included the following: 1.    mechanical bowel preparation with oral antibiotics (neomycin and metronidazole) 2.    aggressive glycemic control3.    chlorhexidine wipes, used the night before and the morning of surgery 4.    high fraction of inspired oxygen (>80%) during and after surgery (15-L nonrebreather mask for 4 hours)5.    double gloving for all scrubbed staff 6.    pulse lavage of subcutaneous tissues before skin closure with 2 L of normal saline 7.    standardized antimicrobial dressing. The role of mechanical bowel preparation has been questioned recently in three meta-analyses of the randomized controlled trials (RCTs) evaluating omission of mechanical bowel preparation.21-23 Yet two other meta-analyses have found that oral antibiotics in combination with systemic antibiotics lead to the lowest SSI rates.24,25 Whether the oral antibiotics are as effective when a mechanical bowel preparation is omitted is a question that remains unanswered. Thus, we decided to proceed with use of a mechanical bowel preparation in addition to oral antibiotics as part of our bundle. Mechanical cleansing is completed the morning before surgery, and oral antibiotics are administered the night before. There is ample evidence showing that perioperative hyperglycemia in noncardiac surgery has been associated with postoperative infections, increased length of stay, hospital complications, and mortality.26-28 Other studies have demonstrated that reductions in postoperative complications can be achieved with postoperative normoglycemia.29,30 In December 2006, KSMC developed a multidisciplinary glycemic work group that led to the formation and implementation of the “glycemic control team” in 2009. This team is made up of pharmacists and internists trained in postoperative glucose control. Since then, all patients undergoing inpatient surgery at KSMC have had a blood glucose level checked in the holding area and 1 hour into an operation. For any patient with a level greater than 140 mg/dL, insulin infusion is started. The glycemic control team then assumes management of the infusions, ensures proper transitions off the intravenous “drips,” and maintains a glucose level between 80 and 180 mg/dL using standard protocols.31 Despite the limited evidence for other adjunctive measures in our bundle, we approached the bundle as an opportunity for thinking outside the box to find ways to reduce the risk of an SSI. For example, although preoperative chlorhexidine has been recommended for SSI prevention,32,33 a meta-analysis of the RCTs investigating the use of preoperative chlorhexidine cleansing in preventing SSIs failed to show a benefit.34 However, one study published in 2008 showed that individuals who used a 2% chlorhexidine gluconate polyester cloth to cleanse with had skin surface concentrations that approached 350Χ the minimal inhibitory concentration for staphylococcal skin isolates.35 Because of potential benefits with few side effects, the CDC and the Association of Perioperative Registered Nurses have endorsed the concept of preadmission skin cleansing.31,32,36 We use a dual skin cleansing done the night before surgery and then in the preoperative holding area. Similarly, some studies have shown a benefit from high fraction of inspired oxygen during and after surgery in reducing SSIs. A meta-analysis in 2009 examined 5 RCTs evaluating the utility of perioperative hyperoxia to reduce the risk of SSIs and showed a statistically significant reduction from 12% to 9%, without an increase in pulmonary complications.37 The PROXI trial (PeRioperative OXygen Fraction—Effect on SSI and Pulmonary Complications After Abdominal Surgery), published after the 2009 meta-analysis, was an RCT that failed to show the positive influence of hyperoxia on SSIs; however, it also showed no increased risk of complications from it either.38 Again, hyperoxia is a low-cost intervention with little risk, and implementation makes sense. We routinely use 80% intraoperative oxygen and a nonrebreather mask at 15 L for 4 hours postoperatively. We decided to make double gloving a requirement for all scrubbed personnel. In a large observational cohort study in Switzerland, the authors showed that without surgical antimicrobial prophylaxis, glove perforation increases the risk of SSI.39 To our knowledge, that was the first study to explore the correlation between SSI and glove leakage in a large series of surgical procedures.39 Other studies have demonstrated the increased risk of glove perforation as well as the increase in bacterial density with duration of an operation.40 Thus, double gloving may be beneficial in lowering the risk of an SSI and is a low-cost measure. Before skin closure, the standard practice has been to rinse the wound with a pour of irrigation. This produces less than 1 psi of pressure and is of little clinical value. Lavage at greater than 10 psi can potentially protect wounds from gross contamination.41 In one retrospective review of laparotomies lasting greater than 4 hours, there was a significantly lower SSI rate when the subcutaneous tissues were lavaged with 2 L of normal saline.42 This measure is inexpensive, is easy to do, and may further reduce the risk of SSI, and thus we employ this measure in all open colorectal cases before skin closure. We also decided to standardize our wound dressings. Currently, the CDC Guidelines for Prevention of Surgical Site Infection recommend the use of sterile dressing to protect closed incisions for 24 to 48 hours postoperatively.32,33 However, there is no evidence to support this recommendation, and none exists with regard to dressing types. Topical silver is an effective bactericidal agent against a broad range of microorganisms that does not appear to induce bacterial resistance. Some single-center reports have demonstrated a lower risk of SSI with silver-impregnated dressings (Acticoat; Smith&Nephew; London, UK).43,44 Antimicrobial gauze coated with polyhexamethylene biguanide (AMD) has recently been introduced as another alternative with effective antimicrobial activity. We implemented use of a standard silver-impregnated (Acticoat) dressing or AMD gauze and leave it in place for 5 days postoperatively. Despite our efforts to adhere to SCIP infection measures, KSMC continued to have high SSI rates compared with other NSQIP institutions. Thus, we hypothesized that incorporating multiple strategies into a single treatment bundle that involves not only these core strategies but also supplemental measures would have a synergistic effect on reduction of SSIs in colorectal operations. Since implementation, we have seen a significant reduction in the total number of infections in colon and rectal operations. Furthermore, we have seen significant reductions in overall general surgery infections and in Class II wounds, the class into which most colorectal operations fall. The O/E ratio for colorectal and general surgery SSIs fell as well after implementation. In establishing a bundle of care, we were able to decrease variability for patients receiving a colorectal operation. One of the key features of this project was sharing our data openly. NSQIP provides risk-adjusted data that allowed us to examine how our Medical Center performs with respect to our peers. This information was distributed among all involved stakeholders at KSMC (administrators, surgeons, nursing staff, infection control, SSI Quality Committee). Although our data between 2006 and 2009 was not favorable, it provided a catalyst for all involved parties to improve SSIs, none more than the surgeons who “own” these outcomes. Despite not monitoring all elements of the bundle, the components that were monitored (SCIP) were posted in the surgical lounges and physicians’ lounge for all to see. We reviewed process measures and outcomes data on a monthly basis, and perceived gaps were addressed. The outcomes were reviewed on a regular basis at departmental meetings, which allowed for further opportunity to educate and share knowledge and to identify more barriers that had to be addressed. Several limitations in this study exist. The current study is not powerful enough and was not designed to isolate specific strategies to eliminate SSIs. We felt an urgency to improve our SSI rates; thus, our goal was to eliminate SSI as quickly and efficiently as possible. Ultimately, this was a “just do it” project. Compliance with all elements of the colorectal care bundle was incomplete, and therefore the association of interventions with SSI prevention could not be assessed. Although some experts argue that aggregated metrics would be a better representation of the quality of care provided to each patient and would allow for better outcome comparisons, we hypothesized that patients who instead receive multiple risk reduction interventions will have a lower risk of SSI. All or none metrics would capture this effectively and allow for better comparison of the actual complication rates; however, this is much more difficult to perform in our current system. Surgical risk mitigation is multifactorial, and our observed reduction in SSI rates may have been affected by an improved culture in the operating room, more attention by leadership, or improved skill and knowledge of the surgical team. As a result of these factors, our reduction in SSIs may yet prove to be a statistical aberration; however, the sustained reduction through 18 months and the decrease in the risk-adjusted NSQIP O/E ratio is very promising. It remains to be seen if this 18-month reduction in SSI rate is sustainable long term or can be reduced even more. Further investigation will be required to assess the degree and sustainability of risk reduction delivered using this colorectal care bundle. Conclusion Participation in NSQIP can identify areas of increased hospital morbidity compared with peer hospitals on a national basis. Through NSQIP participation, KSMC identified SSIs as an area of critical need for improvement. We implemented a bundle of care elements incorporating both core and supplemental strategies and demonstrated a significant decrease in overall colorectal SSIs. Despite being only a single-center case study, the effectiveness of our bundle lends strength to the argument that a bundle of care can act in a synergistic manner to reduce SSIs. As hospitals, physicians, and nurses embrace the quality movement and adopt preventive strategies, large reductions in complications will likely be seen. Disclosure Statement The author(s) have no conflicts of interest to disclose. Acknowledgment Kathleen Louden, ELS, of Louden Health Communications provided editorial assistance. References     1.    Tang R, Chen HH, Wang YL, et al. Risk factors for surgical site infection after elective resection of the colon and rectum: a single-center prospective study of 2809 consecutive patients. Ann Surg 2001 Aug;234(2):181-9.    2.    Itani KM, Wilson SE, Awad SS, Jensen EH, Finn TS, Abramson MA. Ertapenem versus cefotetan prophylaxis in elective colorectal surgery. N Engl J Med 2006 Dec 21;355(25):2640-51.    3.    Wick EC, Shore AD, Hirose K, et al. Readmission rates and cost following colorectal surgery. Dis Colon Rectum 2011 Dec;54(12):1475-9.    4.    Khuri SF. The NSQIP: a new frontier in surgery. Surgery 2005 Nov;138(5):837-43.    5.    Rowell KS, Turrentine FE, Hutter MM, Khuri SF, Henderson WG. Use of National Surgical Quality Improvement Program data as a catalyst for quality improvement. J Am Coll Surg 2007 Jun;204(6):1293-300.    6.    Raval MV, Hamilton BH, Ingraham AM, Ko CY, Hall BL. The importance of assessing both inpatient and outpatient surgical quality. Ann Surg 2011 Mar;253(11);611-8.    7.    Schilling PL, Dimick JB, Birkmeyer JD. Prioritizing quality improvement in general surgery. J Am Coll Surg 2008 Nov;207(5):698-704.    8.    Abraham M, Ahlman JT, Boudreau AJ, Connelly JL, Evans DD. Current procedural terminology 2011, Standard Edition. Chicago, IL: American Medical Association; 2010.     9.    Chapter 4: ACS NSQIP Classic, essential, small-rural, targeted, and Florida variables & definitions [monograph on the Internet]. Chicago, IL: American College of Surgeons; 2012 Jan 1 [cited 2012 Jul 18]. Available from: http://intranet.uchicago.edu/Portals/0/Variable_and_Definitions_July_2012.pdf.    10.    Wick EC, Vogel JD, Church JM, Remzi F, Fazio VW. Surgical site infections in a “high outlier” institution: are colorectal surgeons to blame? Dis Colon Rectum 2009 Mar;52(3):374-9.    11.    Bratzler DW, Hunt DR. The surgical infection prevention and surgical care improvement projects: national initiatives to improve outcomes for patients having surgery. Clin Infect Dis 2006 Aug 1;43(3):322-30.    12.    Dellinger EP, Hausmann SM, Bratzler DW, et al. Hospitals collaborate to decrease surgical site infections. Am J Surg 2005 Jul;190(1):9-15.    13.    Stulberg JJ, Delaney CP, Neuhauser DV, Aron DC, Fu P, Koroukian SM. Adherence to surgical care improvement project measures and the association with postoperative infections. JAMA 2010 Jun 23;303(24):2479-85.    14.    Jones RS, Brown C, Opelka F. Surgeon compensation: “Pay for performance,” the American College of Surgeons National Surgical Quality Improvement Program, the Surgical Care Improvement Project and other programs. Surgery 2005 Nov;138(5):829-36.    15.    Hedrick TL, Heckman JA, Smith RL, Sawyer RG, Friel CM, Foley EF. Efficacy of protocol implementation on incidence of wound infection in colorectal operations. J Am Coll Surg 2007 Sept;205(3):432-8.    16.    Pastor C, Artinyan A, Varma MG, Kim E, Gibbs L,Garcia-Aguilar J. An increase in compliance with the Surgical Care Improvement Project measures does not prevent surgical site infections in colorectal surgery. Dis Colon Rectum 2010 Jan;53(1):24-30.    17.    Hawn MT. Surgical care improvement: should performance measures have performance measures? JAMA 2010 Jun 23;303(24):2527-8.    18.    Potenza B, Diligencia M, Estigoy B, et al. Lessons learned from the institution of the Surgical Care Improvement Project at a teaching medical center. Am J Surg 2009 Dec;198(6):881-8.    19.    Bratzler DW, Houck PM; Surgical Infection Prevention Guidelines Writers Workgroup; American Academy of Orthopaedic Surgeons; American Association of Critical Care Nurses; American Association of Nurse Anesthetists; American College of Surgeons; American College of Osteopathic Surgeons; American Geriatrics Society; American Society of Anesthesiologists; American Society of Colon and Rectal Surgeons; American Society of Health-System Pharmacists; American Society of PeriAnesthesia Nurses; Ascension Health; Association of periOperative Registered Nurses; Association for Professionals in Infection Control and Epidemiology; Infectious Diseases Society of America; Medical Letter; Premier; Society for Healthcare Epidemiology of America; Society of Thoracic Surgeons; Surgical Infection Society. Antimicrobial prophylaxis for surgery: an advisory statement from the National Surgical Infection Prevention Project. Clin Infect Dis 2004 Jun;38(12):1706-15.    20.    Bratzler DW. The Surgical Infection Prevention and Surgical Care Improvement Projects: promises and pitfalls. Am Surg 2006 Nov;72(11):1010-6,1021-30,1133-48.    21.    Wille-Jørgensen P, Guenaga KF, Matos D. Pre-operative mechanic bowel cleansing or not? an updated meta-analysis. Colorectal Dis 2005 Jul;7(4):304-10.    22.    Guenaga KK, Matos D, Wille-Jørgensen P. Mechanical bowel preparation for elective colorectal surgery. Cochrane Database Syst Rev 2009 Jan 21;(1);CD001544. Update in: Cochrane Database Syst Rev 2011;9:CD001544.    23.    Slim K, Vicaut E, Launay-Savary MV, Contant C, Chipponi J. Updated systemic review and meta-analysis of randomized clinical trials on the role of mechanical bowel preparation before colorectal surgery. Ann Surg 2009 Feb;249(2):203-9.    24.    Lewis, RT. Oral versus systemic antibiotic prophylaxis in elective colon surgery: a randomized study and meta-analysis send a message from the 1990s. Can J Surg 2002 Jun;45(3):173-80.    25.    Nelson RL, Glenny AM, Song F. Antimicrobial prophylaxis for colorectal surgery. Cochrane Database Syst Rev 2009 Jan 21;(1):CD001181.    26.    Noordzij PG, Boersma E, Schreiner F, et al. Increased preoperative glucose levels are associated with perioperative mortality in patients undergoing noncardiac, nonvascular surgery. Eur J Endocrinol 2007 Jan;156(1):137-42.    27.    King JT Jr, Goulet JL, Perkal MF, Rosenthal RA. Glycemic control and infections in patients with diabetes undergoing noncardiac surgery. Ann Surg 2011 Jan;253(1):158-65.    28.    Frisch A, Chandra P, Smiley D, et al. Prevalence and clinical outcome of hyperglycemia in the perioperative period in noncardiac surgery. Diabetes Care 2010 Aug;33(8):1783-8.    29.    Umpierrez GE, Smiley D, Jacobs S, et al. Randomized study of basal-bolus insulin therapy in the inpatient management of patients with type 2 diabetes undergoing general surgery (RABBIT 2 surgery). Diabetes Care 2011 Feb;34(2):256-61.    30.    Subramaniam B, Panzica PJ, Novack V, et al. Continuous perioperative insulin infusion decreases major cardiovascular events in patients undergoing vascular surgery: a prospective, randomized trial. Anesthesiology 2009 May;110(5):970-7.    31.    Inpatient pharmacy manual: glycemic control protocol [monograph on the Intranet]. Clackamas, OR: Kaiser Sunnyside Medical Center; 2008 [cited 2012 Jun 20]. Available from: http://internal.or.kp.org/ksmc/documents/policies_procedures/clinical/inpatient_pharmacy/glycemic_control_protocol.pdf [password protected].    32.    Anderson DJ, Kaye KS, Classen D, et al. Strategies to prevent surgical site infection in acute care hospitals. Infect Control Hosp Epidemiol 2008 Oct;29 Suppl 1:s51-61.    33.    Mangram AJ, Horan TC, Pearson ML, Silver LC, Jarvis WR. Guideline for prevention of surgical site infection, 1999. Hospital Infection Control Practices Advisory Committee. Infect Control Hosp Epidemiol 1999 Apr;20(4):217-77.    34.    Webster J, Osborne S. Preoperative bathing or showering with skin antiseptics to prevent surgical site infection. Cochrane Database Syst Rev 2007 Apr 18;CD004985.    35.    Emiston CE Jr, Krepel JC, Seabrook GR, Lewis BD, Brown KR, Towne JB. Preoperative shower revisited: can high topical antiseptic levels be achieved on the skin surface before surgical admission? J Am Coll Surg 2008 Aug;207(2):233-9.    36.    Recommended Practices for Preoperative Patient Skin Antisepsis. In: Conner R, Blanchard J, Burlingame B, et al (eds). AORN Perioperative Standards and Recommended Practices. Denver, CO: Association of periOperative Registered Nurses; 2012. p 445-64.    37.    Qadan M, Akca O, Mahid SS, Hornung CA, Polk HC Jr. Perioperative supplemental oxygen therapy and surgical site infection: a meta-analysis of randomized controlled trials. Arch Surg 2009 Apr;144(4):359-66.    38.    Meyhoff CS, Wetterslev J, Jorgensen LN, et al; PROXI Trial Group. Effect of high perioperative oxygen fraction on surgical site infection and pulmonary complications after abdominal surgery: the PROXI randomized clinical trial. JAMA 2009 Oct 14;302(14):1543-50.    39.    Mistel H, Weber WP, Reck S, et al. Surgical glove perforation and the risk of surgical site infection. Arch Surg 2009 Jun;144(6):553-8.    40.    Eklund AM, Ojajärvi J, Laitinen K, Valtonen M, Werkkala KA. Glove puncture and postoperative skin flora of hands in cardiac surgery. Ann Thorac Surg 2002 Jul;74(1):149-53.    41.    Luedtke-Hoffmann KA, Schafer DS. Pulsed lavage in wound cleansing. Phys Ther 2000 Mar;80(3):292-300.    42.    Nikfarjam M, Kimchi ET, Gusani NJ, et al. Reduction of surgical site infection by use of pulsatile lavage irrigation after prolonged intra-abdominal surgical procedures. Am J Surg 2009 Sep;198(3):381-6.    43.    Childress BB, Berceli SA, Nelson PR, Lee WA, Ozaki CK. Impact of an absorbent silver-eluting dressing system on lower extremity revascularization wound complications. Ann Vasc Surg 2007 Sep;21(5):598-602.    44.    Epstein NE. Do silver-impregnated dressings limit infections after lumbar laminectomy with instrumented fusion? Surg Neurol 2007 Nov;68(5):483-5.

Journal Circulation

25,000 print readers per quarter, 6,900 eTOC readers, 1 million Internet hits in 2013 from 187 countries/territories, and 460,000 TPJ-article hits on PubMed.

Journal Subscriptions

The Permanente Journal is published quarterly by The Permanente Press. Subscribe now for a one-year subscription.

Letters to the Editor

Articles, editorials, letters to the editor, and other material represent the opinion of the authors. Send your comments to permanente.journal@kp.org.


Home | Issues Index | CME | Collections | Bookstore
Authors | Artists | Reviewers | About the Journal | Search
Copyright 2014 The Permanente Journal - Kaiser Permanente. All Rights Reserved.