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Gregg EW, Patorno E, Karter AJ, Mehta R, Huang ES, White M, Patel CJ, McElvaine AT, Cefalu WT, Selby J, Riddle MC, Khunti K. Use of Real-World Data in Population Science to Improve the Prevention and Care of Diabetes-Related Outcomes. Diabetes Care 2023; 46:1316-1326. [PMID: 37339346 PMCID: PMC10300521 DOI: 10.2337/dc22-1438] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/22/2022] [Accepted: 04/11/2023] [Indexed: 06/22/2023]
Abstract
The past decade of population research for diabetes has seen a dramatic proliferation of the use of real-world data (RWD) and real-world evidence (RWE) generation from non-research settings, including both health and non-health sources, to influence decisions related to optimal diabetes care. A common attribute of these new data is that they were not collected for research purposes yet have the potential to enrich the information around the characteristics of individuals, risk factors, interventions, and health effects. This has expanded the role of subdisciplines like comparative effectiveness research and precision medicine, new quasi-experimental study designs, new research platforms like distributed data networks, and new analytic approaches for clinical prediction of prognosis or treatment response. The result of these developments is a greater potential to progress diabetes treatment and prevention through the increasing range of populations, interventions, outcomes, and settings that can be efficiently examined. However, this proliferation also carries an increased threat of bias and misleading findings. The level of evidence that may be derived from RWD is ultimately a function of the data quality and the rigorous application of study design and analysis. This report reviews the current landscape and applications of RWD in clinical effectiveness and population health research for diabetes and summarizes opportunities and best practices in the conduct, reporting, and dissemination of RWD to optimize its value and limit its drawbacks.
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Affiliation(s)
- Edward W. Gregg
- School of Population Health, RRCSI University of Medicine and Health Sciences, Dublin, Ireland
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, U.K
| | - Elisabetta Patorno
- Division of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA
| | - Andrew J. Karter
- Division of Research, Kaiser Permanente, Oakland, CA
- Department of Health Systems and Population Health, University of Washington, Seattle, WA
| | - Roopa Mehta
- Metabolic Research Unit (UIEM), Department of Endocrinology and Metabolism, Instituto Nacional de Ciencias Medicas y Nutricion, Salvador Zubiran (INCMNSZ), Mexico City, Mexico
| | - Elbert S. Huang
- Section of General Internal Medicine, Center for Chronic Disease Research and Policy (CDRP), The University of Chicago, Chicago, IL
| | - Martin White
- Medical Research Council Epidemiology Unit, University of Cambridge, Cambridge, U.K
| | - Chirag J. Patel
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA
| | | | - William T. Cefalu
- Division of Diabetes, Endocrinology, and Metabolic Diseases, National Institute of Diabetes, Digestive, and Kidney Diseases, National Institutes of Health, Bethesda, MD
| | - Joseph Selby
- Patient-Centered Outcomes Institute, Washington, DC
| | - Matthew C. Riddle
- Division of Endocrinology, Diabetes, and Clinical Nutrition, Oregon Health & Science University, Portland, OR
| | - Kamlesh Khunti
- Leicester Real World Evidence Unit, Diabetes Research Centre, University of Leicester, Leicester, U.K
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Quinton JK, Jackson N, Mangione CM, Moin T, Vasilyev A, O'Shea DL, Duru OK. Differential Impact of a Plan-Led Standardized Complex Care Management Intervention on Subgroups of High-Cost High-Need Medicaid Patients. Popul Health Manag 2023; 26:100-106. [PMID: 37071688 PMCID: PMC10125392 DOI: 10.1089/pop.2022.0271] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/19/2023] Open
Abstract
Interventions to better coordinate care for high-need high-cost (HNHC) Medicaid patients frequently fail to demonstrate changes in hospitalizations or emergency department (ED) use. Many of these interventions are modeled after practice-level complex care management (CCM) programs. The authors hypothesized that a national CCM program may be effective for some subgroups of HNHC patients, and the overall null effect may obfuscate subgroup-level impact. They used a previously published typology defining 6 subgroups of high-cost Medicaid patients and evaluated program impact by subgroup. The analysis used an individual-level interrupted time series with a comparison group. Intervention subjects were high-cost adult Medicaid patients who enrolled in 1 of 2 national CCM programs implemented by UnitedHealthcare (UHC) (n = 39,687). The comparators were patients who met CCM program criteria but were ineligible due to current enrollment in another UHC/Optum led program (N = 26,359). The intervention was a CCM program developed by UHC/Optum to provide "whole person care" delivering standardized interventions to address medical, behavioral, and social needs for HNHC Medicaid patients, and the outcome was probability of hospitalization or ED use in a given month, estimated at 12 months postenrollment. A reduction in risk of ED utilization for 4 of 6 subgroups was found. A reduction in risk of hospitalization for 1 of 6 subgroups was also found. The authors conclude that standardized health plan led CCM programs demonstrate effectiveness for certain subgroups of HNHC patients in Medicaid. This effectiveness is principally in reducing ED risk and may extend to the risk of hospitalization for a small number of patients.
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Affiliation(s)
- Jacob K. Quinton
- Department of Medicine, Division of General Internal Medicine and Health Services Research, University of California, Los Angeles, Los Angeles, California, USA
- CMS Innovation Center, Centers for Medicare and Medicaid Services, Baltimore, Maryland, USA
| | - Nicholas Jackson
- Department of Medicine, Division of General Internal Medicine and Health Services Research, University of California, Los Angeles, Los Angeles, California, USA
| | - Carol M. Mangione
- Department of Medicine, Division of General Internal Medicine and Health Services Research, University of California, Los Angeles, Los Angeles, California, USA
| | - Tannaz Moin
- Department of Medicine, Division of General Internal Medicine and Health Services Research, University of California, Los Angeles, Los Angeles, California, USA
| | - Arseniy Vasilyev
- Department of Medicine, Division of General Internal Medicine and Health Services Research, University of California, Los Angeles, Los Angeles, California, USA
| | | | - O. Kenrik Duru
- Department of Medicine, Division of General Internal Medicine and Health Services Research, University of California, Los Angeles, Los Angeles, California, USA
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Cené CW, Viswanathan M, Fichtenberg CM, Sathe NA, Kennedy SM, Gottlieb LM, Cartier Y, Peek ME. Racial Health Equity and Social Needs Interventions: A Review of a Scoping Review. JAMA Netw Open 2023; 6:e2250654. [PMID: 36656582 PMCID: PMC9857687 DOI: 10.1001/jamanetworkopen.2022.50654] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/20/2023] Open
Abstract
IMPORTANCE Social needs interventions aim to improve health outcomes and mitigate inequities by addressing health-related social needs, such as lack of transportation or food insecurity. However, it is not clear whether these studies are reducing racial or ethnic inequities. OBJECTIVE To understand how studies of interventions addressing social needs among multiracial or multiethnic populations conceptualize and analyze differential intervention outcomes by race or ethnicity. EVIDENCE REVIEW Sources included a scoping review of systematic searches of PubMed and the Cochrane Library from January 1, 1995, through November 29, 2021, expert suggestions, and hand searches of key citations. Eligible studies evaluated interventions addressing social needs; reported behavioral, health, or utilization outcomes or harms; and were conducted in multiracial or multiethnic populations. Two reviewers independently assessed titles, abstracts, and full text for inclusion. The team developed a framework to assess whether the study was "conceptually thoughtful" for understanding root causes of racial health inequities (ie, noted that race or ethnicity are markers of exposure to racism) and whether analyses were "analytically informative" for advancing racial health equity research (ie, examined differential intervention impacts by race or ethnicity). FINDINGS Of 152 studies conducted in multiracial or multiethnic populations, 44 studies included race or ethnicity in their analyses; of these, only 4 (9%) were conceptually thoughtful. Twenty-one studies (14%) were analytically informative. Seven of 21 analytically informative studies reported differences in outcomes by race or ethnicity, whereas 14 found no differences. Among the 7 that found differential outcomes, 4 found the interventions were associated with improved outcomes for minoritized racial or ethnic populations or reduced inequities between minoritized and White populations. No studies were powered to detect differences. CONCLUSIONS AND RELEVANCE In this review of a scoping review, studies of social needs interventions in multiracial or multiethnic populations were rarely conceptually thoughtful for understanding root causes of racial health inequities and infrequently conducted informative analyses on intervention effectiveness by race or ethnicity. Future work should use a theoretically sound conceptualization of how race (as a proxy for racism) affects social drivers of health and use this understanding to ensure social needs interventions benefit minoritized racial and ethnic groups facing social and structural barriers to health.
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Affiliation(s)
- Crystal W. Cené
- Department of Medicine, University of California, San Diego Health, San Diego
- School of Medicine, University of California, San Diego
| | - Meera Viswanathan
- RTI International–University of North Carolina at Chapel Hill Evidence-based Practice Center, RTI International, Research Triangle Park
| | - Caroline M. Fichtenberg
- University of California, San Francisco Social Intervention Research and Evaluation Network, San Francisco
- School of Medicine, Department of Family and Community Medicine, Center for Health and Community, University of California, San Francisco
| | - Nila A. Sathe
- RTI International–University of North Carolina at Chapel Hill Evidence-based Practice Center, RTI International, Research Triangle Park
| | - Sara M. Kennedy
- RTI International–University of North Carolina at Chapel Hill Evidence-based Practice Center, RTI International, Research Triangle Park
| | - Laura M. Gottlieb
- School of Medicine, Department of Family and Community Medicine, Center for Health and Community, University of California, San Francisco
| | - Yuri Cartier
- University of California, San Francisco Social Intervention Research and Evaluation Network, San Francisco
| | - Monica E. Peek
- Section of General Internal Medicine, MacLean Center for Clinical Medical Ethics, Center for the Study of Race, Politics and Culture, The University of Chicago, Chicago, Illinois
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Bilazarian A, McHugh J, Schlak AE, Liu J, Poghosyan L. Primary Care Practice Structural Capabilities and Emergency Department Utilization Among High-Need High-Cost Patients. J Gen Intern Med 2023; 38:74-80. [PMID: 35941491 PMCID: PMC9849605 DOI: 10.1007/s11606-022-07706-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/29/2021] [Accepted: 06/16/2022] [Indexed: 01/22/2023]
Abstract
BACKGROUND US primary care practices are actively identifying strategies to improve outcomes and reduce costs among high-need high-cost (HNHC) patients. HNHC patients are adults with high health care utilization who suffer from multiple chronic medical and behavioral health conditions such as depression or substance abuse. HNHC patients with behavioral health conditions face heightened challenges accessing timely primary care and managing their conditions, which is reflected by their high rates of emergency department (ED) utilization and preventable spending. Structural capabilities (i.e., care coordination, chronic disease registries, shared communication systems, and after-hours care) are key attributes of primary care practices which can enhance access and quality of chronic care delivery. OBJECTIVE The purpose of this study was to analyze the association between structural capabilities and ED utilization among HNHC patients with behavioral health conditions. DESIGN AND MEASURES We merged cross-sectional survey data on structural capabilities from 240 primary care practices in Arizona and Washington linked with Medicare claims data on 70,182 HNHC patients from 2019. KEY RESULTS Using multivariable Poisson models, we found shared communication systems were associated with lower rates of all-cause and preventable ED utilization among HNHC patients with alcohol use (all-cause: aRR 0.72, 95% CI: 0.62, 0.84; preventable: aRR 0.5, 95% CI: 0.40, 0.64) and HNHC patients with substance use disorders (all-cause: aRR 0.76, 95% CI: 0.68, 0.85; preventable: aRR 0.61, 95% CI: 0.52, 0.71). Care coordination was also associated with decreased rates of ED utilization among the overall HNHC population and those with alcohol use, but not among HNHC patients with depression or substance use disorders. CONCLUSION Shared communication systems and care coordination have the potential to increase the effectiveness of primary care delivery for specific HNHC patients.
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Affiliation(s)
- Ani Bilazarian
- School of Nursing, Columbia University, New York, NY, USA.
| | - John McHugh
- School of Nursing, Columbia University, New York, NY, USA
- Mailman School of Public Health, Columbia University, New York, NY, USA
| | | | - Jianfang Liu
- School of Nursing, Columbia University, New York, NY, USA
| | - Lusine Poghosyan
- School of Nursing, Columbia University, New York, NY, USA
- Mailman School of Public Health, Columbia University, New York, NY, USA
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High-cost high-need patients in Medicaid: segmenting the population eligible for a national complex case management program. BMC Health Serv Res 2021; 21:1143. [PMID: 34686170 PMCID: PMC8539737 DOI: 10.1186/s12913-021-07116-6] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2021] [Accepted: 09/27/2021] [Indexed: 02/07/2023] Open
Abstract
Background High-cost high-need patients are typically defined by risk or cost thresholds which aggregate clinically diverse subgroups into a single ‘high-need high-cost’ designation. Programs have had limited success in reducing utilization or improving quality of care for high-cost high-need Medicaid patients, which may be due to the underlying clinical heterogeneity of patients meeting high-cost high-need designations. Methods Our objective was to segment a population of high-cost high-need Medicaid patients (N = 676,161) eligible for a national complex case management program between January 2012 and May 2015 to disaggregate clinically diverse subgroups. Patients were eligible if they were in the top 5 % of annual spending among UnitedHealthcare Medicaid beneficiaries. We used k-means cluster analysis, identified clusters using an information-theoretic approach, and named clusters using the patients’ pattern of acute and chronic conditions. We assessed one-year overall and preventable hospitalizations, overall and preventable emergency department (ED) visits, and cluster stability. Results Six clusters were identified which varied by utilization and stability. The characteristic condition patterns were: 1) pregnancy complications, 2) behavioral health, 3) relatively few conditions, 4) cardio-metabolic disease, and complex illness with relatively 5) low or 6) high resource use. The patients varied by cluster by average ED visits (2.3–11.3), hospitalizations (0.3–2.0), and cluster stability (32–91%). Conclusions We concluded that disaggregating subgroups of high-cost high-need patients in a large multi-state Medicaid sample identified clinically distinct clusters of patients who may have unique clinical needs. Segmenting previously identified high-cost high-need populations thus may be a necessary strategy to improve the effectiveness of complex case management programs in Medicaid. Supplementary Information The online version contains supplementary material available at 10.1186/s12913-021-07116-6.
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Filling the Public Health Science Gaps for Diabetes With Natural Experiments. Med Care 2020; 58 Suppl 6 Suppl 1:S1-S3. [PMID: 32412947 DOI: 10.1097/mlr.0000000000001330] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
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Trends in Costs of Care and Utilization for Medicaid Patients With Diabetes in Accountable Care Communities. Med Care 2020; 58 Suppl 6 Suppl 1:S40-S45. [PMID: 32412952 DOI: 10.1097/mlr.0000000000001318] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
BACKGROUND/OBJECTIVES Medicaid beneficiaries with diabetes have complex care needs. The Accountable Care Communities (ACC) Program is a practice-level intervention implemented by UnitedHealthcare to improve care for Medicaid beneficiaries. We examined changes in costs and utilization for Medicaid beneficiaries with diabetes assigned to ACC versus usual care practices. RESEARCH DESIGN Interrupted time series with concurrent control group analysis, at the person-month level. The ACC was implemented in 14 states, and we selected comparison non-ACC practices from those states to control for state-level variation in Medicaid program. We adjusted the models for age, sex, race/ethnicity, comorbidities, seasonality, and state-by-year fixed effects. We examined the difference between ACC and non-ACC practices in changes in the time trends of expenditures and hospital and emergency room utilization, for the 4 largest categories of Medicaid eligibility [Temporary Assistance to Needy Families, Supplemental Security Income (without Medicare), Expansion, Dual-Eligible]. SUBJECTS/MEASURES Eligibility and claims data from Medicaid adults with diabetes from 14 states between 2010 and 2016, before and after ACC implementation. RESULTS Analyses included 1,200,460 person-months from 66,450 Medicaid patients with diabetes. ACC implementation was not associated with significant changes in outcome time trends, relative to comparators, for all Medicaid categories. CONCLUSIONS Medicaid patients assigned to ACC practices had no changes in cost or utilization over 3 years of follow-up, compared with patients assigned to non-ACC practices. The ACC program may not reduce costs or utilization for Medicaid patients with diabetes.
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