The Implications of Insurance Benefit Design for Health and Disability Among Low Income Adults with Diabetes.

NIH Pandemic-Era Grants

Pandemic Era Grants

2024

Document text

Principal Investigator: KIMBERLY D NARAIN
Organization: UNIVERSITY OF CALIFORNIA LOS ANGELES
Fiscal Year: 2024
Award: $177,444
Funding agency: National Institute on Aging

Project Summary/Abstract
This career development award will establish Dr. Kimberly Narain, MD, PhD, MPH, as an independent
investigator focused on evaluating the health, aging and healthcare costs implications of social, economic and
health policies/programs, among adults with low socioeconomic status (SES), using both quasi-experimental
and microsimulation approaches. This KO8 award will provide her the support she needs to develop expertise
in 3 areas 1) analysis of administrative claims and longitudinal data; 2) aging epidemiology and SES disparities
in aging; and 3) microsimulation and cost-benefit analysis. Non-adherence to medications and treatment
recommendations due to costs is an important driver of the SES gradient in health and disability among adults
with diabetes.1 Value Based Insurance Design (VBID) strategies that reduce out-of-pocket (OOP) costs for
medications to treat diabetes and associated conditions (hyperlipidemia and hypertension) as well as disease
management appointments (primary care and endocrinologist visits) have been shown to improve medication
adherence and cardiovascular risk factor control, among privately insured individuals. However, little is known
about the effects of VBID among low income adults with Type 2 diabetes. 2,3 Understanding the effect of VBID
among low income adults is important because they face the highest disease burden associated with Type 2
diabetes and they may be particularly responsive to VBID given their higher level of price sensitivity, relative to
higher income individuals.4 However, they may also face barriers outside of costs such as low health literacy,
making the effects of VBID among this population uncertain. Additionally, it is important to know if there is any
heterogeneity in response to VBID, across baseline medication adherence levels, given that prior studies have
shown the largest effect magnitudes among subgroups with the lowest baseline medication adherence levels.
Lastly, the long-term impacts of VBID on the health, disability and healthcare costs of low income adults with
diabetes remains uninvestigated. Dr. Narain will clarify the impact of VBID among this population by examining
the impact of the Diabetes Health Plan (DHP), an employer-sponsored VBID, offered by Unitedhealthcare,
among low income (salaries < $30,000), adults with Type 2 diabetes. This project will leverage an existing data
set of more than 200 employers, housed at UCLA, to estimate both the short and long-term impacts of the
DHP, using quasi-experimental methods and a microsimulation modeling approach, respectively. The specific
aims of the proposed project are to 1) Estimate the impact of the DHP on (A) medication adherence, (B)
cardiovascular risk factors (HbA1c and LDL) and (C) healthcare utilization among low income adults with Type
2 diabetes; 2) Compare DHP treatment effects across baseline levels of medication adherence and 3)
Estimate the long-term impact of the DHP, relative to standard health insurance plans, on disability-free life
expectancy and healthcare costs among aging low income adults with Type 2 diabetes. The project will provide
key insight for informing health insurance benefit design and improving health equity.

Terms: <21+ years old><Accident and Emergency department><Adherence><Adult><Adult Human><Adult-Onset Diabetes Mellitus><Aging><Analgesic Management><Appointment><Area><Award><Career Development Awards><Career Development Awards and Programs><Career Development Programs K-Series><Caring><Cost of Illness><Cost-Benefit Analysis><Costs and Benefits><Data><Data Set><Diabetes Mellitus><Disability outcome><Disability related outcomes><Disease Costs><Disease Management><Disorder Management><Disparities><Disparity><Doctor of Philosophy><Drug Prescribing><Drug Prescriptions><Drugs><ED visit><ER visit><Economic Income><Economic Policy><Economical Income><Emergency Department><Emergency care visit><Emergency department visit><Emergency hospital visit><Emergency room><Emergency room visit><Employee><Endocrinologist><Epidemiology><Face><Financial Hardship><Glycohemoglobin A><Glycosylated hemoglobin A><Goals><Hb A1><Hb A1a+b><Hb A1c><HbA1><HbA1c><Health><Health Benefit><Health Care Costs><Health Care Utilization><Health Costs><Health Insurance><Health Policy><Healthcare Costs><Hemoglobin A(1)><Heterogeneity><High-Income Populations><Hospital Admission><Hospitalization><Household><Hyperlipemia><Hyperlipidemia><Hypertension><Income><Individual><Insurance><Insurance Benefits><Investigators><Investments><K-Awards><K-Series Research Career Programs><Ketosis-Resistant Diabetes Mellitus><LDL><LDL Lipoproteins><Life Expectancy><Low income><Low-Density Lipoproteins><Maturity-Onset Diabetes Mellitus><Medical><Medication><Medication Management><NIDDM><Non-Insulin Dependent Diabetes><Non-Insulin-Dependent Diabetes Mellitus><Noninsulin Dependent Diabetes><Noninsulin Dependent Diabetes Mellitus><Out-of-Pocket Expense><Outcome><Outcomes for persons with disabilities><Outcomes in disabilities><Ph.D.><PhD><Pharmaceutical Preparations><Pharmacologic Management><Policies><Population><Price><Primary Care><Privatization><Quasi-experiment><Quasi-experimental analysis><Quasi-experimental approach><Quasi-experimental design><Quasi-experimental methods><Quasi-experimental research><Quasi-experimental study><Quasi-experimental technique><Recommendation><Research Career Program><Research Personnel><Researchers><Salaries><Sickness Cost><Slow-Onset Diabetes Mellitus><Social Policies><Socio-economic status><Socioeconomic Status><Stable Diabetes Mellitus><Subgroup><Survey Instrument><Surveys><T2 DM><T2D><T2DM><Time><Type 2 Diabetes Mellitus><Type 2 diabetes><Type II Diabetes Mellitus><Type II diabetes><Uncovered Medical Expenses><Uncovered Uninsured Medical Expense><Uninsured Medical Expense><Vascular Hypertensive Disease><Vascular Hypertensive Disorder><Visit><Wages><Work><adult onset diabetes><adulthood><beta-Lipoproteins><burden of disease><burden of illness><cardiovascular risk><cardiovascular risk factor><copayment><cost><cost benefit economics><cost benefit effectiveness><design><designing><diabetes><disability><disease burden><drug adherence><drug compliance><drug/agent><epidemiologic><epidemiological><faces><facial><financial adversity><financial burden><financial distress><financial insecurity><financial strain><financial stress><health care policy><health care service use><health care service utilization><health equity><health insurance plan><health plan><health plans><healthcare policy><healthcare service use><healthcare service utilization><healthcare utilization><hemoglobin A1c><high blood pressure><high income group><high income individual><high income people><hospital utilization><hyperpiesia><hyperpiesis><hypertensive disease><hypertensive disorder><implementation design><implementation research design><improved><inadequate health literacy><incomes><insight><intervention design><intervention program><ketosis resistant diabetes><low SES><low health literacy><low socio-economic position><low socio-economic status><low socioeconomic position><low socioeconomic status><maturity onset diabetes><medical expenses not covered by insurance><medication adherence><medication compliance><medication prescription><medication therapy management><mid life><mid-life><middle age><middle aged><midlife><model-based simulation><models and simulation><out-of-pocket costs><out-of-pocket health care costs><patient subclass><patient subcluster><patient subgroups><patient subpopulations><patient subsets><patient subtypes><poor health literacy><prescribed medication><pricing><programs><reduced health literacy><response><simulation><social implication><socio-economic position><socioeconomic position><therapy design><total medical expenditure><treatment adherence><treatment compliance><treatment design><treatment effect><type 2 DM><type II DM><type two diabetes>