Characteristics of Newly Enrolled Members of an Integrated Delivery System after the Affordable Care Act

Elizabeth A Bayliss, MD, MSPH; Jennifer L Ellis, MSPH; Mary Jo Strobel, RN, MBA;
Deanna B McQuillan, MA; Irena B Petsche, PhD; Jennifer C Barrow, MSPH; Arne Beck, PhD

Perm J 2015 Summer; 19(3):4-10 [Full Citation]


Context: Little is known about the health status and care needs of new enrollees in health plans since implementation of the Affordable Care Act.
Objective: To describe characteristics of new members of an integrated delivery system during early phases of implementation of the act.
Design: Descriptive analysis of ongoing collection of operational data.

Main Outcome Measures: The 11-question Brief Health Questionnaire, which was administered to new members of Kaiser Permanente Colorado who had benefits effective on or after January 1, 2014. Bivariate analyses compared characteristics of new enrollees by benefit.
Results: Of 89,289 newly enrolled non-Medicare members, 22,548 (25.3%) completed the Brief Health Questionnaire between January 1, 2014, and August 31, 2014. Of these, 3593 respondents were insured through Medicaid, 9434 through the individual health exchange, and 9521 through primarily commercial plans. Of Medicaid, exchange, and commercial members, 19.5%, 7.1%, and 5.3%, respectively, self-reported fair or poor health; 12.9%, 2.0%, and 3.3% of each group self-reported 2 or more Emergency Department visits during the previous year; and 8.1%, 4.3%, and 4.4% self-reported an inpatient admission during the previous year. During the preceding year, 31.5% of Medicaid, 30.8% of exchange, and 12.6% of commercial members were uninsured longer than 8 months.
Conclusion: Systematic collection of patients' self-reported information can enhance traditional approaches to initiating care, inform operational planning, and describe newly enrolled populations. Newly enrolled Medicaid beneficiaries may have more initial health care needs than new exchange or commercial members; however, health differences between the latter two groups are subtle.


The first open enrollment period under the Affordable Care Act (ACA)1 resulted in an estimated eight million individuals gaining insurance coverage through exchanges and an additional six million through Medicaid expansions nationally.2-5 Published estimates of health status for those likely to gain new coverage under the ACA vary widely and are based on limited data.6-8

Accurate and timely information on the care needs of individuals who are either newly insured or transitioning between care plans under the ACA are important because these needs will affect demand for a range of primary and specialty care services.6,8 Most methods for predicting health care resource needs rely on models that incorporate measures of previous service use, morbidity burden, and socioeconomic factors. These factors are strong predictors of future service needs, as are self-reported health and functional status.9-17 However, morbidity and utilization data are unavailable before engagement with the health care system.

In the absence of preexisting information on newly enrolled individuals, real-time data collection on health-related characteristics can inform care delivery and resource planning. Operations leaders and researchers in Kaiser Permanente Colorado (KPCO) collaborated to develop a brief health screening questionnaire to anticipate the potential health care needs of newly enrolled members. The goal of the Brief Health Questionnaire (BHQ) is twofold: 1) to identify care needs that can be met before traditional primary care appointments and 2) to characterize the newly enrolled member population. This brief report describes characteristics of new KPCO members during early phases of the ACA implementation.


A not-for-profit, integrated health care delivery system, KPCO provides services in Denver and other metropolitan areas along the Colorado "Front Range" to the north and south of Denver. New members were defined as individuals who had no previous enrollment in KPCO and had new benefits effective on or after January 1, 2014. For families with more than one new enrollee, each individual was eligible to respond to the BHQ. We defined insurance type as Medicaid, individual exchange, and all other (composed primarily of large- and small-group commercial members). New Medicare members were excluded.

The 11-question BHQ addresses the following domains: general health status, specific chronic illnesses, prescription medications, depression screening, pregnancy, financial constraints, prior-year hospitalizations, Emergency Department (ED) use, and insurance coverage.10,18-26 The BHQ is provided in the Appendix: Brief Health Questionnaire (available online at: Before administration, the questionnaire was pilot tested on 35 new members to assess comprehension and completion time. Starting in late 2013, the BHQ was offered to any new non-Medicare member calling for an appointment and was accessible on the KPCO Web site. After scheduling of an appointment, new members were asked for permission to "route the call to a New Member Specialist for assistance with ‘onboarding.'" This specialist then asked the BHQ questions and entered responses into the member's electronic health record (EHR).

Data collection is ongoing and evolving for this operational project. For example, Community Specialists still reach out to new Medicaid members to assess health and community resource needs. Additionally, new members are now directed (via a welcome telephone call and mailed identification card insert) to a 1-stop shop for all their onboarding needs, which include selecting a primary care physician, understanding benefits and care delivery options, registering on the KPCO Web site, and administration of the BHQ. This New Member Team is also responsible for outreach to new members within their first 90 days of coverage.

If new members responded "yes" to any BHQ question, New Member Specialists made telephone appointments for follow-up encounters on the basis of prespecified rules. All BHQs completed on the KPCO Web site were automatically routed to appropriate EHR in-baskets for follow-up. Pharmacists contacted new members regarding refills on prescription medications; Nurse Care Managers assessed those reporting fair or poor health status, specific chronic conditions, a "positive" depression screen (a Patient Health Questionnaire-2 score of 3 or greater27), or potential high morbidity as indicated by hospitalization and emergency service use. Social workers and Community Specialists evaluated reports of financial and social needs. The Obstetrics Department arranged for necessary prenatal care. Documentation of follow-up encounters was entered in the EHR for use at the point of care. Use of the questionnaire is ongoing.

We compared demographic characteristics and BHQ responses across groups of new members (Medicaid, exchange, and other) using c2 tests. We also conducted two descriptive subanalyses comparing 1) individuals who reported having no insurance for more than eight months during the previous year with those insured for that entire year and 2) BHQ respondents and nonrespondents.

The KPCO institutional review board reviewed the protocol for the BHQ program and analyses, and determined that it met criteria for an operations intervention with intent to publish, rather than human subjects research.


A total of 89,289 members were newly enrolled between January 1, 2014, and August 31, 2014. Of these, 22,548 (25.3%) completed a BHQ by August 31, 2014. By insurance type, 3593 respondents were insured through Medicaid, 9434 through the individual health exchange, and 9521 through other mechanisms, primarily large and small group commercial plans. These responses represented 43.2% (3593/8318) of new Medicaid enrollees, 26.8% (9434/35,113) of new exchange enrollees, and 20.8% (9521/45,858) of other new enrollees. Most (91.0%) of the BHQ data were collected through telephone calls, with the remainder collected through the KPCO patient portal into the EHR. Responses for new members under age 18 years were provided by parents or guardians.

Table 1 lists demographic characteristics of new members by insurance category. New Medicaid and exchange members were older than other/commercial members (mean ages for Medicaid, exchange, and other were 33.8, 40.0, and 29.5 years, respectively). Approximately 58% of respondents were female. Table 2 summarizes responses to the BHQ questions across insurance groups. Fair or poor health was self-reported by 19.5%, 7.1%, and 5.3% of Medicaid, exchange, and other groups, respectively. A greater proportion of Medicaid enrollees (30.7%) reported physical functioning interfering with health, and a greater proportion of exchange enrollees (40.8%) reported prescription medication use. Of BHQ respondents, 11.8% of Medicaid, 4.7% of exchange, and 3.4% of other/commercial enrollees screened positive for possible depression. During the preceding year there was a greater difference in self-reported ED utilization across groups than in self-reported inpatient hospital admissions, with 12.9% of Medicaid enrollees reporting 2 or more ED visits (compared with 2.0% of exchange and 3.3% of other new members), but less than 2% of all groups reporting 2 or more inpatient admissions. Comparable percentages of Medicaid and exchange enrollees (just over 30%) reported no insurance during more than 8 months during the previous year, compared with 12.6% of other beneficiaries. All variable differences across groups of enrollees were significant at p < 0.001 except for sex, which was significant at p < 0.05. Of new Medicaid enrollees, 60.8% were referred for any additional services on the basis of BHQ responses, compared with 55.8% of new exchange enrollees and 48.6% of other enrollees (p < 0.001). The highest percentage of referrals across insurance groups was because of prescription medication use.

The pattern of new Medicaid enrollees having greater morbidity than new exchange or other new enrollees was also evident in proportions of self-reported chronic conditions. Asthma was reported by 8.4% of new Medicaid enrollees, 6.9% of new exchange enrollees, and 6.4% of new other enrollees (p = 0.003). Diabetes was reported by 5.8%, 4.7%, and 3.1% of each group, respectively; heart disease by 2.6%, 2.3%, and 1.6%; and high blood pressure by 13.8%, 13.1%, and 8.2% (p < 0.001 for all).

Descriptive subanalyses of new members previously uninsured for more than 8 months vs those insured for the entire year are listed in Table 3. In each benefit group, the previously uninsured individuals report slightly higher rates of fair or poor health, and of health interfering with daily activity, but they do not report greater rates of specific chronic conditions. A higher proportion of individuals in the previously uninsured subpopulations had a positive depression screen, and a higher proportion reported financial constraints.

Table 4 compares BHQ respondents vs nonrespondents. Compared with nonrespondents, respondents were significantly more likely to be female, to be older, and to carry Medicaid or exchange insurance (p < 0.001).






Accurate information on the health status and care needs of individuals enrolling in insurance plans during the early phases of the ACA implementation can help optimize care delivery for newly insured and transitioning populations. This snapshot of new members in an integrated delivery system in the Denver Front Range area suggests that new Medicaid enrollees are less healthy than new exchange and new commercial members are; however, differences between new exchange enrollees and new commercial members are more subtle.

We found that 19.5% of new Medicaid members and 7.1% of new exchange members overall had fair or poor health. In the smaller subsample of individuals without previous insurance, 25.9% of new Medicaid members and 11.4% of new exchange members reported fair or poor health. Our Medicaid findings are consistent with previous estimates6,7,28 that proportions of the ACA target population with fair or poor health would range from 10% to 25%, with the greater burden falling on individuals below 200% of the Federal Poverty Level. However, the general health status in new exchange enrollees in this population is somewhat better than these predictions.6,7,28 It is also somewhat better than a national population of nongroup enrollees (individuals who purchased their own insurance) surveyed after ACA implementation in Spring 2014, in which 14% reported fair or poor health.29 It is possible that our results reflect characteristics of Colorado residents—which may differ from a nationally representative sample—or that individuals enrolling in Year 1 of the ACA may have better health status than those who remain uninsured. Ongoing surveillance of health status among the newly insured will help clarify their health status and care needs and should inform service requirements for integrated and other delivery systems.

Rates of chronic disease are notoriously difficult to predict because individuals who are unable to access care may be unaware of diagnoses. Estimates of heart disease in our Medicaid and exchange sample to date (2% to 3%) are comparable to literature-based predictions, whereas the rate of asthma in BHQ respondents (6.4% to 8.4%) is comparable to rates in previously uninsured populations, but half of asthma rates in Medicaid populations.7,30 Published estimates suggest depression rates in the range of 2% to 17% for Medicaid and exchange enrollees.7,30 Although BHQ respondents had positive depression screens within this range, their diagnoses of depression require further evaluation.27

In 2011, the Kaiser Family Foundation predicted that 65% of exchange purchasers would have been previously uninsured.30 We found that previous insurance coverage was not comprehensive for any of the 3 groups, and that just over 30% of new Medicaid and exchange enrollees reported being uninsured for more than 8 months during the previous year. These proportions may be slightly skewed by missing data, but they are lower than the 57% national figure reported in a 2014 Kaiser Family Foundation survey.29 They may also reflect the insurance marketplace in Colorado and uptake of exchange plans by both insured and uninsured individuals. (Our sample does not include the small-business exchange.)

New Medicaid members reported greater past utilization of the ED than did other respondents. Studies of Medicaid expansions suggest that this pattern may continue after obtaining insurance, although it may be modified by effective primary care relationships.23,31 In the longer term, gaining insurance benefits increases utilization of health care resources, improves mental and physical health, increases the use of preventive services, and decreases mortality for both Medicaid and non-Medicaid populations.28,32-34 Optimizing long-term health outcomes will require maximizing both informational and interpersonal continuity of care for patients who may move between Medicaid and exchange benefit categories and between being insured and uninsured.

Although patient-reported data on health status, physical function, emotional well-being, and other constructs are predictive of mortality and utilization, and can guide interventions to improve the quality of care, such measures have previously been used almost exclusively in the context of research rather than care delivery.10,35-38 Recently, health assessments have been incorporated into care delivery for defined populations such as seniors, employees, and Health Plan members.39 The BHQ assessment exemplifies how patient-reported data can be systematically collected to inform care delivery, especially in light of 2014 net growth of approximately 15%, compared with previous annual net growth rates in the range of 2% to 3% for the delivery system. To date, approximately 54% of all BHQ respondents have been referred for either care management or pharmacy services. Future retrospective analyses will determine whether referrals for early medication and care management affect more distal health outcomes such as hospitalization and disease-specific adverse events.

Our study has several limitations. Medicaid enrollees enrolling in KPCO were a relatively small subset of all Colorado Medicaid beneficiaries. New KPCO exchange enrollees reflect an approximate 38% share of the Colorado exchange marketplace and only represent those who selected a single integrated delivery system. Newly enrolled patients in other delivery systems and settings will have different characteristics. This sample primarily reflects a subset of members who contacted the delivery system during the first 6 months of enrollment, and data collection was limited by the capacity of the call center's service associates. As illustrated in Table 4, there were a number of demographic differences between BHQ respondents and nonrespondents. Respondents to the BHQ are also more likely to have used health care services. These comparisons support (but do not confirm) a hypothesis that new enrollees with higher morbidity were initial users of the delivery system and more likely to complete a BHQ. Finally, most of the responses were obtained via telephone; although responses obtained through the Web portal may be systematically different, Web-based responses represent a very small proportion of the total and are unlikely to bias the results. Our preliminary cross-sectional description must be supplemented with longitudinal assessments that link patient-reported BHQ responses with subsequent utilization patterns and that link all of these factors with robust health outcomes.


This description suggests that newly enrolled Medicaid beneficiaries may have more initial health care needs than either new exchange or commercial members; however, health differences between the latter 2 groups in this population sample are more subtle. The Congressional Budget Office estimates that by 2023, insurance will be obtained by 13 million individuals through Medicaid expansions and by 24 million through exchange-based plans.40 There is likely to be increasing movement of individuals across benefit categories, as well as increasing inclusion of previously insured populations in Medicaid and exchange insurance plans. Adequately informing care delivery for this changing landscape will require an understanding of which subpopulations are likely to transition between benefit categories and between delivery systems and settings, and which subpopulations risk adverse health outcomes as a function of these transitions. Further evaluation of needs assessments, such as the BHQ process, will inform the development of systematic interventions to optimize health outcomes in newly enrolled populations.

Disclosure Statement

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


This project was supported by a grant from the Kaiser Permanente Garfield Memorial Fund.

Kathleen Louden, ELS, of Louden Health Communications provided editorial assistance.

 1.    The Patient Protection and Affordable Care Act of 2010. Public Law 111-148, 111th Congress, 124 Stat 119, HR 3590, enacted 2010 Mar 23.
    2.    Health insurance marketplace: summary enrollment report for the initial annual open enrollment period [Internet]. Washington, DC: Department of Health and Human Services, Office of the Assistant Secretary for Planning and Evaluation; 2014 May 1 [cited 2015 Mar 9]. Available from:
    3.    Medicaid & CHIP: March 2014 monthly applications, eligibility determinations, and enrollment report [Internet]. Baltimore, MD: Centers for Medicare and Medicaid Services, Department of Health and Human Services; 2014 May 1 [cited 2015 Mar 9]. Available from:
    4.    Claxton G, Levitt L, Brodie M, Garfield R,

Damico A. Measuring change in insurance coverage under the Affordable Care Act [Internet]. Menlo Park, CA: The Henry J Kaiser Family Foundation; 2014 Apr 30 [cited 2015 Mar 9]. Available from:
    5.    Grob R, Schlesinger M, Pollitz K, Grubstein L. Taking stock and taking steps: a report from the field after the first year of marketplace consumer assistance under the ACA [Internet]. Menlo Park, CA: The Henry J Kaiser Family Foundation; 2014 Oct 1 [cited 2015 Mar 9]. Available from:
    6.    Abraham JM. How might the Affordable Care Act's coverage expansion provisions influence demand for medical care? Milbank Q 2014 Mar;92(1):63-87. DOI: Erratum in: Milbank Q 2014 Jun;92(2):404-5. DOI:
    7.    Decker SL, Kostova D, Kenney GM, Long SK. Health status, risk factors, and medical conditions among persons enrolled in Medicaid vs uninsured low-income adults potentially eligible for Medicaid under the Affordable Care Act. JAMA 2013 Jun 26;309(24):2579-86. DOI:
    8.    Sommers BD, Rosenbaum S. Issues in health reform: how changes in eligibility may move millions back and forth between Medicaid and insurance exchanges. Health Aff (Millwood) 2011 Feb;30(2):228-36. DOI:
    9.    DeSalvo KB, Jones TM, Peabody J, et al. Health care expenditure prediction with a single item, self-rated health measure. Med Care 2009 Apr;47(4):440-7. DOI:
    10.    DeSalvo KB, Fan VS, McDonell MB, Fihn SD. Predicting mortality and healthcare utilization with a single question. Health Serv Res 2005 Aug;40(4):1234-46. DOI:
    11.    Machlin SR, Soni A. Health care expenditures for adults with multiple treated chronic conditions: estimates from the Medical Expenditure Panel Survey, 2009. Prev Chronic Dis 2013 Apr 25;
10:E63. DOI:
    12.    Naessens JM, Baird MA, Van Houten HK, Vanness DJ, Campbell CR. Predicting persistently high primary care use. Ann Fam Med 2005 Jul-Aug;3(4):324-30. DOI:
    13.    Parkerson GR Jr, Harrell FE Jr, Hammond WE, Wang XQ. Characteristics of adult primary care patients as predictors of future health services charges. Med Care 2001 Nov;39(11):1170-81.
    14.    Hoffman C, Rice D, Sung HY. Persons with chronic conditions. Their prevalence and costs. JAMA 1996 Nov 13;276(18):1473-9. DOI:
    15.    Boyd C, Leff B, Weiss C, Wolff J, Hamblin A,

Martin L. Faces of Medicaid: clarifying multimorbidity patterns to improve targeting and delivery of clinical services for Medicaid populations [Internet]. Hamilton, NJ: Center for Health Care Strategies; 2010 Dec [cited 2015

Mar 9]. Available from:
    16.    Gao J, Moran E, Li YF, Almenoff PL. Predicting potentially avoidable hospitalizations. Med Care 2014 Feb;52(2):164-71. DOI:
    17.    Nagasako EM, Reidhead M, Waterman B, Dunagan WC. Adding socioeconomic data to hospital readmissions calculations may produce more useful results. Health Aff (Millwood) 2014 May;33(5):786-91. DOI:
    18.    Dorr DA, Jones SS, Burns L, et al. Use of health-related, quality-of-life metrics to predict mortality and hospitalizations in community-dwelling seniors. J Am Geriatr Soc 2006 Apr;54(4):
667-73. DOI:
    19.    de Boer AG, Wijker W, de Haes HC. Predictors of health care utilization in the chronically ill: a review of the literature. Health Policy 1997 Nov;42(2):101-15. DOI:
    20.    Donnan PT, Dorward DW, Mutch B, Morris AD. Development and validation of a model for predicting emergency admissions over the next year (PEONY): a UK historical cohort study. Arch Intern Med 2008 Jul 14;168(13):1416-22. DOI:
    21.    McCusker J, Karp I, Cardin S, Durand P, Morin J.

Determinants of emergency department visits by older adults: a systematic review. Acad Emerg Med 2003 Dec;10(12):1362-70. DOI:
    22.    Halfon N, Newacheck PW, Wood DL, St Peter RF. Routine emergency department use for sick care by children in the United States. Pediatrics 1996 Jul;98(1):28-34.
    23.    Ginde AA, Lowe RA, Wiler JL. Health insurance status change and emergency department use among US adults. Arch Intern Med 2012 Apr 23;172(8):642-7. DOI:
    24.    Li AK, Covinsky KE, Sands LP, Fortinsky RH, Counsell SR, Landefeld CS. Reports of financial disability predict functional decline and death in older patients discharged from the hospital. J Gen Intern Med 2005 Feb;20(2):168-74. DOI:
    25.    Bindman AB, Chattopadhyay A, Auerback GM.

Interruptions in Medicaid coverage and risk for hospitalization for ambulatory care-sensitive conditions. Ann Intern Med 2008 Dec 16;149(12):854-60. DOI:
    26.    Sudano JJ Jr, Baker DW. Intermittent lack of health insurance coverage and use of preventive services. Am J Public Health 2003 Jan;93(1):130-7. DOI:
    27.    Kroenke K, Spitzer RL, Williams JB. The Patient Health Questionnaire-2: validity of a two-item depression screener. Med Care 2003 Nov;41(11):1284-92.
    28.    Sommers BD, Baicker K, Epstein AM. Mortality and access to care among adults after state Medicaid expansions. N Engl J Med 2012 Sep 13;367(11):1025-34. DOI:
    29.    Hamel L, Norton M, Levitt L, et al. Survey of non-group health insurance enrollees [Internet]. Menlo Park, CA: The Henry J Kaiser Family Foundation; 2014 Jun 19 [cited 2015 Mar 9]. Available from:
    30.    A profile of health insurance exchange enrollees [Internet]. Menlo Park, CA: The Henry J Kaiser Family Foundation; 2011 Mar 1 [cited 2015 Mar 9]. Available from:
    31.    Taubman SL, Allen HL, Wright BJ, Baicker K, Finkelstein AN. Medicaid increases emergency-department use: evidence from Oregon's health insurance experiment. Science 2014 Jan 17;343(6168):263-8. DOI:
    32.    Michalopoulos C, Wittenburg D, Israel DA, Warren A. The effects of health care benefits on health care use and health: a randomized trial for disability insurance beneficiaries. Med Care 2012 Sep;50(9):764-71. DOI:
    33.    Freeman JD, Kadiyala S, Bell JF, Martin DP. The causal effect of health insurance on utilization and outcomes in adults: a systematic review of US studies. Med Care 2008 Oct;46(10):1023-32.

    34.    Baicker K, Taubman SL, Allen HL, et al. The Oregon experiment—effects of Medicaid on clinical outcomes. N Engl J Med 2013 May 2;368(18):1713-22. DOI:
    35.    Perrin NA, Stiefel M, Mosen DM, Bauck A, Shuster E, Dirks EM. Self-reported health and functional status information improves prediction of inpatient admissions and costs. Am J Manag Care 2011 Dec 1;17(12):e472-8.
    36.    Diehr P, Williamson J, Patrick DL, Bild DE,

Burke GL. Patterns of self-rated health in older adults before and after sentinel health events.

J Am Geriatr Soc 2001 Jan;49(1):36-44. DOI:
    37.    Wagner EH, LaCroix AZ, Grothaus LC, Hecht JA.

Responsiveness of health status measures to change among older adults. J Am Geriatr Soc 1993 Mar;41(3):241-8.
    38.    Min L, Ubhayakar N, Saliba D, et al. The vulnerable elders survey-13 predicts hospital complications and mortality in older adults with traumatic injury: a pilot study. J Am Geriatr Soc 2011 Aug;59(8):1471-6. DOI:
    39.    Stiefel M, Nolan K. A guide to measuring the triple aim: population health, experience of care, and per capita cost. IHI innovation series white paper. Cambridge, MA: Institute for Healthcare Improvement; 2012.
    40.    CBO's May 2013 estimate of the effects of the Affordable Care Act on health insurance coverage: Table 1 [Internet]. Washington, DC: Congressional Budget Office; 2014 May [cited 2015 Mar 9]. Available from:


Click here to join the eTOC list or text ETOC to 22828. You will receive an email notice with the Table of Contents of The Permanente Journal.


2 million page views of TPJ articles in PubMed from a broad international readership.


Indexed in MEDLINE, PubMed Central, EMBASE, EBSCO Academic Search Complete, and CrossRef.




ISSN 1552-5775 Copyright © 2021

All Rights Reserved