Using Panel Management to Identify Adult Patients With High-Risk Metabolic Dysfunction–Associated Steatotic Liver Disease/Metabolic Dysfunction–Associated Steatohepatitis Fibrosis in a Primary Care Clinic: A Pilot Study
Published Online: October 24, 2024
Abstract
Background
As rates of metabolic dysfunction–associated steatotic liver disease (MASLD) and metabolic dysfunction–associated steatohepatitis (MASH) rise, national organizations have released new guidance for primary care–driven detection of patients with advanced fibrosis who are most likely to have clinically relevant morbidity. Yet time constraints, workflow, and practitioner awareness limit integration of risk identification into clinical care.
Materials and Methods
At the authors’ primary care clinic, they implemented a panel management strategy that utilized the electronic health record to identify patients older than 35 years of age at risk for MASLD fibrosis with abnormal Fibrosis-4 (Fib-4) scores. Using a proactive model, these patients were offered elastography-based screening and follow-up appointments focused on metabolic health, with referrals to subspecialty care when indicated.
Results
Of 855 patients older than 35 years of age, 384 were identified as having risk factors for MASLD/MASH. Of these, 53 had abnormal Fib-4 scores with no prior work-up; 29 patients consented to a shear wave elastography; 16 underwent shear wave elastography; and 6 had moderate or high results concerning for at-risk fibrosis. Twenty patients attended MASLD-focused appointments. Reluctance to pursue testing was driven by skepticism surrounding preventative medicine, perceived cost, and desire to focus on other medical problems, some of which were life-limiting.
Conclusion
Panel management represents a scalable strategy to quickly identify patients in primary care most likely to experience complications from MASLD/MASH and provides a targeted intervention to direct further management. Limitations include access to care, medical complexity, and patient acceptance.
Introduction
Metabolic dysfunction–associated steatotic liver disease (MASLD) is a prevalent, chronic condition with chance of progression to serious illness. It is the most common cause of liver disease in adults 1–3 and affects 25% to 30% of adults in the United States and > 70% of adults with type 2 diabetes mellitus. 4–7 This disease can range from simple fat in the liver (MASLD) to fat with inflammation (metabolic dysfunction–associated steatohepatitis, or MASH). The latter has a higher potential for development of hepatic fibrosis and eventual cirrhosis. 8 The prevalence of MASLD has doubled over the last 2 decades, and the rates of hepatic decompensation, hepatocellular cancer, and death related to MASH are expected to increase another 2- to 3-fold by 2030, tracking with anticipated rises in obesity. 8 By 2030, it is anticipated to be the leading indication for liver transplantation in the United States, as it already is for women and patients older than 60 years. 9
Identifying patients at highest likelihood for MASLD-related morbidity and mortality represents a diagnostic challenge for the primary care doctor, as many patients are asymptomatic until they have developed advanced disease. The presence and stage of liver fibrosis is currently the best predictor for liver-related morbidity and development of comorbidities, 10–14 with fibrosis ≥ stage 2 (with stage 4 representing cirrhosis) proposed as a critical tipping point. 15 Thus, the American Association for the Study of Liver Disease (AASLD) has suggested identification of those patients with stage 2 fibrosis or higher as a priority for general clinicians and specialists alike. 8
To achieve this goal, new guidelines from AASLD, the American Diabetes Society, and the European Association for the Study of the Liver suggest screening at-risk patients, such as those with diabetes or complicated obesity, in the primary care setting with the Fibrosis-4 Index (Fib-4 score) to determine likelihood of possible advanced fibrosis every 1–3 years based on comorbid diabetes mellitus. 8,16,17 This simple score, based on 3 common laboratory values (aspartate transaminase, alanine transaminase, and platelet count), has been shown to perform well at 2 different cut-offs: high sensitivity (77.8%) when < 1.34 or < 2 for adults older than 65 years and high specificity (95.8%) when > 3.25, with a composite area under the curve of 0.84. 18 These guidelines suggest patients with a moderate or high Fib-4 undergo a secondary assessment with shear wave elastography (SWE), a noninvasive, affordable, ultrasound-based imaging technique with high reliability to detect advanced fibrosis (area under the curve of 0.95). 18 This sequential testing pathway used in primary care has been shown to be cost-effective when applied to high-risk populations in low-prevalence settings. 19–23
Despite this guidance, the demands on primary care doctors, the medical complexity of patients, and the asymptomatic nature of MASLD make it difficult to integrate screening into routine primary care. Additionally, the rapid pace of medical innovation often leads to a delay between developments in guidance and implementation in the clinical setting. 24 This phenomenon is seen starkly in MASLD, where, in one large health care system, only 3% of patients with abnormal Fib-4 were referred to hepatology or for elastography. 25 This is a gap with potential repercussions for patients, as frequent visits to manage weight can reduce development of cirrhosis and associated complications, such as esophageal varices and hepatocellular cancer. 26,27
Panel management, also known as population health management, is a proactive approach to primary care that systematically identifies a practice-based patient population with a specific disease and offers a targeted intervention. 28 It requires the use of information technology tools to identify high-risk patients, dedicated physician time to direct clinical decision-making, support staff time to provide outreach, and a structured work process to approach care. 28 Panel management has been shown to improve identification, engagement, and treatment of patients with diabetes and hypertension, support smoking cessation and advanced care planning, and improve referrals for immunizations and bone density screening. 28–31 When applied among vulnerable populations, such programs have been shown to increase access to care and improve quality metrics. 32
In the authors’ primary care, faculty and resident–based practice, a novel panel management protocol was implemented to identify patients with a chance of advanced fibrosis stemming from MASLD/MASH, refer for SWE, provide targeted intervention and education for patients during dedicated patient visits, and connect to higher levels of care where indicated. Although algorithms have been initiated in primary care settings, to the authors’ knowledge, this represents the first panel management initiative in a primary care practice to identify MASLD/MASH and screen for advanced fibrosis.
Methods
Setting
This study was performed at an urban, community-based faculty-resident primary care clinic in the United States (Waterbury, Connecticut). This clinic was selected for this real-world study as it has a patient population with a majority public insurance, diverse backgrounds, and high socioeconomic need. Patients were seen by both attending and resident physicians. Laboratory testing and SWE were performed at the same campus. This project was determined to be exempt by the Institutional Review Board of Trinity Health of New England.
Electronic Medical Record
Clinical documentation was performed in the commercially available Epic electronic medical record (Epic Systems Corporation, Verona, WI). Data were extracted using the reporting workbench software, which allows users to create queries to compile custom reports on patients within their practice on the basis of defined criteria.
Inclusion criteria
Patients had a primary care doctor as a resident or attending at the practice, were older than 35 years of age on September 1, 2023, and either had type 2 diabetes or complicated obesity. The age of 35 was chosen as AASLD recommendations do not suggest using Fib-4 for risk stratification under the age of 35 due to its low accuracy, and instead using secondary assessment when there is clinical concern. 8 Complicated obesity was defined as obesity (last body mass index (BMI) ≥ 30) 33 and 1 or more of the following: prediabetes (last hemoglobin A1C > 5.7%), 34 hyperlipidemia (last low-density lipoprotein cholesterol > 130 mg/dL), 35 hypertriglyceridemia (last triglyceride > 200 mg/dL), 36 or chart diagnosis of hypertension.
Exclusion criteria
Patients were excluded if they had a known cause of hepatic dysfunction (autoimmune, genetic, alcohol, or medication-related), were already followed by hepatology, had already undergone elastography in the last 3 years, had a known diagnosis of cirrhosis, or had not had necessary blood work (aspartate transaminase, alanine transaminase, and platelet count) in the last 3 years (2 if the patient was diabetic).
Intervention
This study was conducted as a quality improvement pilot study, conducted along Plan-Do-Study-Act principles. 37 A Fib-4 score was calculated for each patient. Patients with an elevated Fib-4 ( > 1.3 if younger than 65 years old, > 2 if older than 65 years old) were called by a practitioner, provided information about recommended screening, and offered SWE and a follow-up appointment. If the patient did not answer the phone, a voicemail was left and 2 additional attempts were made. Patients interested in SWE and follow-up received 2 additional calls, 1 from the radiology department to schedule their SWE and 1 from clinical staff to schedule either an in-person or telehealth appointment per patient preference. SWE was performed with a Philips ultrasound unit with a C5-1 probe at 20 Hz. Imaging of the liver was performed as part of the examination. All patients who underwent SWE were contacted about their results. Patients who came to follow-up appointments were seen for 45-minute appointments with a resident internal medicine physician. Visits focused on personal chance of MASLD, lifestyle factors, and management of medications for metabolic health. Possible outcomes included nutrition referral and medication adjustment. Acute patient concerns were also addressed during the visit. Patients with intermediate Fib-4 (< 2.56) but high liver stiffness measurement (LSM; > 8) as well as all patients with high Fib-4 (> 2.56) were offered referral to hepatology (Figure 1). This intervention was conducted over 3 months.
Statistical Methods
For categorical values, a Pearson’s χ2 test was performed; when counts were < 5, a Fisher’s exact test was performed. Significance was defined as a P value < 0.05. All statistical analyses were performed using a standard software package (Stata, version 14.2.431; StataCorp).
Results
Of 855 patients older than 35 years of age in the authors’ practice, 384 met criteria for advanced fibrosis screening. Of these, 7 had known cirrhosis. One patient had an elevated Fib-4 but was already being followed by hepatology and had up-to-date SWE. Fifty-three patients had an elevated Fib-4 and no prior SWE or referral to gastroenterology, and 39 did not have blood work within the prior 3 years (2 if diabetic) to calculate a Fib-4.
Of the 53 patients with elevated Fib-4 and no prior evaluation, 39 answered the phone, with 29 interested in SWE. Out of the 10 who did not want to be screened, 4 cited burden of other health care problems (recent amputation, dementia, recent hospitalization, and anxiety), 3 cited a desire to not “go looking for trouble,” 1 wanted to speak with their primary care doctor first, 1 was concerned about insurance approval, and 1 recently changed practice. Sixteen patients had SWE performed, 14 attended follow-up visits within 2 months, and 6 patients had scans with at-risk fibrosis (Figure 2).
Of these 6 patients, 4 were referred to hepatology. Given the choice, 1 elected an academic dedicated hepatology practice at a further distance, and 3 elected a community gastroenterology practice. The other 2 were not referred due to burden of other illnesses, including rapidly progressive dementia and lung cancer. The two patients not referred had the highest LSM of all participants (16.2 and 12, respectively). Of the 9 patients with high Fib-4 ( > 2.56) scores, 7 answered the phone, and 6 were interested in appointments and elastography. Five were scheduled for appointments and 3 went. Of these 3, 2 had undergone elastography and had low-risk (LSM < 8) results. They were both offered referral to hepatology given their high Fib-4 score, however both declined, 1 citing a desire to focus on diabetes management and the other citing challenges with transportation. The third requested an additional appointment with her primary care doctor before deciding to see a specialist or get a scan.
Patients with elevated Fib-4 who underwent SWE within the study period were more likely to have had a more recent office visit prior to the study period (last visit 3.3 [IQR 1.8–4.5] vs 4.9 [IQR 2.5–11] months, P = 0.019) and were more likely to have their ethnicity listed as Hispanic or Latino in the electronic medical record than patients with elevated Fib-4 who did not undergo SWE (81.2% vs 43.2%, P = 0.022). 28.3% of patients had prior abdominal imaging with steatosis; 41.5% had never had abdominal imaging within the authors’ medical records system (Table 1). Of patients who underwent SWE, patients with a reassuring result (LSM < 8) were significantly older (70 [IQR 62–79] vs 55 [IQR 52–58] years old, P = 0.035; Table 2).
| All patients with elevated fib-4 (N = 53) | Did not undergo SWE (n = 37) | Underwent SWE (n = 16) | P value | |
|---|---|---|---|---|
| Age (y), median (IQR) | 62 (57–72) | 63 (55–71) | 62 (57–79) | 0.822 |
| Sex (male), n (%) | 21 (39.6) | 15 (40.5) | 6 (37.5) | 0.835 |
| Race, n (%) | 0.378 | |||
| Asian American | 1 (1.9) | 1 (2.7) | 0 (0.0) | |
| Black or African American | 13 (24.5) | 11 (29.7) | 2 (12.5) | |
| White or European American | 30 (56.6) | 18 (48.7) | 12 (75) | |
| Other | 9 (17.0) | 7 (18.9) | 2 (12.5) | |
| Ethnicity, n (%) | 0.022* | |||
| Hispanic or Latino | 29 (54.7) | 16 (43.2) | 13 (81.2) | |
| Not Hispanic or Latino | 23 (43.4) | 20 (54.1) | 3 (18.8) | |
| Unknown | 1 (1.9) | 1 (2.7) | 0 (0.0) | |
| PCP type: attending, n (%) | 40 (75.5) | 28 (75.7) | 12 (75.0) | 0.958 |
| State-sponsored insurance, n (%) | 48 (90.6) | 35 (94.6) | 13 (81.25) | 0.155 |
| Area deprivation index (state decile), median (IQR) | 10 (8–10) | 10 (8–10) | 10 (8–10) | 0.548 |
| Area deprivation index (national percentile), median (IQR) | 74 (56–83) | 72 (56–81) | 75.5 (57–84) | 0.6113 |
| Mo since last in-person visit, median (IQR) | 4.2 (2.4–6.4) | 4.9 (2.5–11) | 3.3 (1.8–4.5) | 0.019* |
| Last A1C value, median (IQR) | 6.1 (5.7–7.0) | 6.0 (5.6–6.6) | 6.7 (5.9–7.5) | 0.065 |
| Last LDL cholesterol, median (IQR) | 82 (72–116) | 89 (73–125) | 79 (72–93) | 0.262 |
| Last BMI | 32.3 (30.7–36.9) | 32.7 (31–36.9) | 31.1 (27.4–35.6) | 0.116 |
| Chart diagnosis of HTN, n (%) | 36 (67.9) | 22 (59.5) | 14 (87.5) | 0.058 |
| Steatosis on prior imaging, n (%) | 0.230 | |||
| Yes | 15 (28.3) | 10 (27.0) | 5 (31.2) | |
| No | 16 (30.2) | 9 (24.3) | 7 (43.75) | |
| None available | 22 (41.5) | 18 (48.7) | 4 (25.0) | |
| Hepatitis C infection, n (%) | 0.835 | |||
| Yes | 0 (0.0) | 0 (0.0) | 0 (0.0) | |
| No | 21 (39.6) | 15 (40.5) | 6 (37.5) | |
| Never tested | 32 (60.4) | 22 (59.5) | 10 (62.5) | |
| Fib-4, median (IQR) | 1.8 (1.45–2.48) | 2.01 (1.45–2.55) | 1.56 (1.44–2.35) | 0.542 |
* denotes statistical significance
BMI, body mass index; Fib-4, Fibrosis-4 score; HTN, hypertension; LDL, low-density lipoprotein; PCP, primary care practitioner; SWE, shear wave elastography.
| Underwent SWE (N = 16) | Low LSM (n = 10) | High LSM (n = 6) | P value | |
|---|---|---|---|---|
| Age (y), median (IQR) | 62 (57–79) | 70 (62–79) | 55 (52–58) | 0.035* |
| Sex (male), n (%) | 6 (37.5) | 3 (30.0) | 3 (50.0) | 0.607 |
| Race, n (%) | 0.242 | |||
| Asian American | 0 (0.0) | 0 (0.0) | 0 (0.0) | |
| Black or African American | 2 (12.5) | 2 (20.0) | 0 (0.0) | |
| White or European American | 12 (75) | 8 (80.0) | 4 (66.7) | |
| Other | 2 (12.5) | 0 (0.0) | 2 (33.3) | |
| Ethnicity, n (%) | 1.000 | |||
| Hispanic or Latino | 13 (81.2) | 8 (80.0) | 5 (83.3) | |
| Not Hispanic or Latino | 3 (18.8) | 2 (20.0) | 1 (16.7) | |
| Unknown | 0 (0.0) | 0 (0.0) | 0 (0.0) | |
| PCP type: attending, n (%) | 12 (75.0) | 7 (70.0) | 5 (83.3) | 1.000 |
| State-sponsored insurance, n (%) | 13 (81.25) | 9 (90.0) | 4 (66.7) | 0.518 |
| Area deprivation index (state decile), median (IQR) | 10 (8–10) | 10 (8–10) | 10 (8–10) | 0.7448 |
| Area deprivation index (national percentile), median (IQR) | 75.5 (57–84) | 75.5 (56–89) | 77 (58–83) | 0.9785 |
| Mo since last in-person visit, median (IQR) | 3.3 (1.8–4.5) | 3.1 (2.1–4.2) | 3.7 (1.5–4.7) | 0.773 |
| Last A1C value, median (IQR) | 6.7 (5.9–7.5) | 6.8 (5.7–7.4) | 6.5 (6.1–8.1) | 0.810 |
| Last LDL cholesterol, median (IQR) | 79 (72–93) | 75 (71–82) | 93 (77–125) | 0.211 |
| Last BMI | 31.1 (27.4–35.6) | 29.6 (26.6–34) | 31.8 (29.8–38.2) | 0.562 |
| Chart diagnosis of HTN, n (%) | 14 (87.5) | 10 (100.0) | 4 (66.7) | 0.125 |
| Steatosis on prior imaging, n (%) | 1.000 | |||
| Yes | 5 (31.2) | 3 (30.0) | 2 (33.3) | |
| No | 7 (43.75) | 4 (40.0) | 3 (50.0) | |
| None available | 4 (25.0) | 3 (30.0) | 1 (16.67) | |
| Hepatitis C infection, n (%) | 0.392 | |||
| Yes | 0 (0.0) | 0 (0.0) | 0 (0.0) | |
| No | 6 (37.5) | 3 (30.0) | 3 (50.0) | |
| Never tested | 10 (62.5) | 7 (70.0) | 3 (50.0) | |
| Fib-4, median (IQR) | 1.56 (1.44–2.35) | 1.82 (1.53–2.56) | 1.44 (1.39–1.58) | 0.056 |
Fib-4, Fibrosis-4 score; HTN, hypertension; LDL, low-density lipoprotein; LSM, liver stiffness measurement; SWE, shear wave elastography.
For the 14 patients who attended visits, 10 were conducted over telehealth. During these visits, medications were adjusted for diabetes, cholesterol, and medical weight loss management. Five patients were overdue for screening labs for metabolic health, which were ordered. All patients were counseled regarding personal risk for MASLD/MASH, a need for future screening, and lifestyle mitigation. For patients who had not undergone SWE yet, questions and concerns were addressed (Table 3).
| Number of patients with visits scheduled: | 20 |
|---|---|
| Number of patients who attended visits: | 14 |
| Number of telehealth appointments: | 10 |
| MASLD education provided and lifestyle counseling performed: | 14 |
| Diabetes management adjusted: | 3 |
| Lipid management adjusted: | 1 |
| Medical weight loss initiated: | 3 |
| Screening labs ordered: | 5 |
| Other chronic conditions managed: | cardiac disease, constipation, dementia, dizziness, dysuria, erectile dysfunction, hepatic cysts, insomnia, obstructive sleep apnea, opioid use disorder, osteoarthritis |
MASLD, metabolic dysfunction–associated steatotic liver disease.
Discussion
This study represents a real-world, quality improvement initiative for patients with MASLD/MASH to offer patients appropriate, guidance-based care to identify advanced hepatic fibrosis. By using a panel management strategy, the authors’ clinical team was able to efficiently identify high-risk patients in their practice based on preexisting data and offer targeted screening and follow-up.
This project is especially relevant given the challenging social determinants of health among the authors’ patient population. Using the area deprivation index, a marker of relative neighborhood socioeconomic deprivation based on ZIP code, this study population had the highest relative deprivation possible on a state level (median 10th percentile, IQR 8–10) as well as a high national percentile (74%, IQR 56–83). 38,39 Over 90% of the authors’ patients receive state-sponsored insurance and, in the clinic as a whole, 63% have housing issues, 47% have transportation limitations, and 45% have food insecurity. 40 Patients from vulnerable populations have been shown to have lower access rates to specialty care with resultant increases in liver-related morbidity and mortality. 41 The authors’ program shows promise to effectively identify patients at risk for developing cirrhosis and its associated complications in other high-risk, low-prevalence, and socially complex populations.
There is additional value in performing population-based proactive medicine that extends beyond identification of target patients. For clinicians, such interventions raise awareness among clinical staff of new guidance and appropriate management. For patients, there is benefit in a clinical encounter that is not problem-based, but instead focused on mitigating risk. Though only 2 of the 14 patients with full follow-up appointments had abnormal SWE, all 14 received further information on their personal risk for MASLD as well as lifestyle counseling. Five had yet to schedule their SWE and questions were addressed in more detail. Of 14 visits, 8 involved ordering overdue blood work or medical management of diabetes/prediabetes, hyperlipidemia, and obesity. Additionally, a myriad of broad-ranging patient concerns were addressed, increasing touch points for vulnerable patients. This intervention was facilitated by the normalization of telehealth, demonstrated by 10 of 14 visits occurring through telehealth at patient request. However, this study highlights one weakness of telehealth: the lack of physical examination screening for compensated cirrhosis, such as evaluating for splenomegaly, firm or nodular liver edges, gynecomastia, spider angiomata, and palmar erythema. 8
A potential weakness in this approach is the lack of screening based on individual risk (ie, family history), comorbidities, and age. However, this may also reflect a weakness in current society guidance, as no advice is provided to help decide at what age and life expectancy screening is no longer of value to a patient. It is remarkable that, of the 16 patients with an abnormal Fib-4, the only significant difference between those with a low and high SWE is age, with mean age for patients with a low-risk SWE 15 years older than for those with a moderate or high-risk SWE. Median Fib-4 for these patients was also higher (1.82 vs 1.44), although this did not reach statistical significance (P = 0.056). This suggests that there might be a bias in the Fib-4 formula for older adults to score higher, partially due to age being in the numerator of the equation as well as higher prevalence of other causes of thrombocytopenia among older adults, although this study is not calibrated to investigate this observation thoroughly. Of the 6 patients with moderate or high-risk SWE, 2 were not referred to hepatology due to burden of other diseases and perception that, in the absence of clinical signs of cirrhosis, other medical comorbidities would likely be life-limiting before complications of cirrhosis emerge. At what age and life expectancy one should stop screening for hepatic fibrosis is an area that requires further delineation.
In implementing this program, this team encountered a number of challenges. Some patients were not able to be initially contacted despite 3 separate phone calls, possibly due to outdated contact information, work and family demands, reluctance to pick up unknown phone calls, and financial or physical inabilities to use technologies. Other patients declined further evaluation due to the burden of preexisting medical illness, skepticism around proactive preventative care, wariness regarding receiving a call from a practitioner who was not their primary care doctor, and financial concerns regarding coverage. The authors do not know if patients dropped out during future steps, such as being contacted to schedule an ultrasound or attending the follow-up appointment, for similar issues. It is possible that, on the phone with a practitioner, there is pressure to agree to testing even if the patient may not understand why the test is being recommended, leading to decreased adherence. Additional issues with transportation, scheduling, and evolving medical issues likely contributed to challenges in test completion.
There are some limitations to the authors’ study. First, it is unclear if there are individual factors associated with their single center that limit the generalizability of the results. The authors also had a short follow-up duration of only 3 months, which does not demonstrate if markers of metabolic health improved in correlation with this intervention. The authors do not know what portion of the patients referred to specialty care attended those appointments and what further evaluation demonstrated.
There are additional limitations to the authors’ program generally. Their panel management strategy is unable to evaluate patients with risk factors for MASLD but without laboratory data within the needed time frame to calculate a Fib-4, which affected 39 patients. Additional systems need to be built to reach out to and schedule appropriate laboratory screening for these patients. This approach also does not address systemic issues with access to care. It is likely that the reason that systemic factors, including transportation, health literacy, language barriers, and work obligations contributed to the authors’ finding that patients who did not undergo screening had been seen in the office more remotely from this program. These factors likely drove the fact that only 16/53 (30%) patients with high Fib-4 scores underwent further evaluation. Given the high degree of financial, housing, and transportation issues in the authors’ population, 40 screening for a largely asymptomatic disease may be low priority for their patients. Remedying this gap with future interventions will be critical in trying to affect the natural course of MASLD/MASH, particularly given the rapid development of new therapies aimed at slowing fibrosis.
Conclusion
As both the burden of MASLD/MASH-related morbidity and mortality and the development of effective strategies to reverse or slow progression of disease increase, it is the duty of the primary care practitioner to be vigilant to detect disease before it causes meaningful morbidity. In a single-center, faculty-resident based primary care clinic, a panel management program was successfully implemented to efficiently identify higher risk patients, screen for advanced fibrosis, and refer to specialty care when appropriate. The authors believe this study models how panel management strategies might allow for rapid implementation of new guidance in preventative medicine in primary care, for MASLD and other chronic diseases. As the prevalence and morbidity associated with MASLD-related fibrosis and cirrhosis continue to rise in the years to come, more research is needed to create innovations to identify and modify disease early before it becomes clinically relevant, and for many, too late.
Footnote
Data-Sharing Statement
Data are available upon request. Readers may contact the corresponding author to request underlying data.
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© 2024 The Authors. Published by The Permanente Federation LLC under the terms of the CC BY-NC-ND 4.0 license https://creativecommons.org/licenses/by-nc-nd/4.0/.
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Author Contributions
Sarah Householder, MD, and Andrew J Loza, MD, PhD, contributed to the conception of the paper, with Vikas Gupta, MD, PhD, and Benjamin Doolittle, MD, MDiv, assisting with design. Householder performed the investigation as well as acquisition and analysis of data, with Gupta and Doolittle contributing to interpretation. Householder and Doolittle wrote the first draft, and all authors revised the article and approved the final paper.
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