# Integrated Care Plans and Health Care Quality, Outcomes, and Equity for Medicare-Medicaid Dual Eligible Beneficiaries with Multimorbidity, Frailty, or Dementia > **NIH NIH RF1** · HARVARD UNIVERSITY D/B/A HARVARD SCHOOL OF PUBLIC HEALTH · 2024 · $2,283,522 ## Abstract PROJECT SUMMARY / ABSTRACT Integrating coverage for dually eligible Medicare-Medicaid beneficiaries (‘duals’), a population with complex medical and social needs, is a national priority. There is substantial concern that duals in non-integrated Medicare Advantage (MA) plans or Traditional Medicare receive ineffective, inefficient, and potentially harmful care due to unnecessary administrative burdens, lack of financial incentives for care coordination, and plans’ perverse incentives to shift costs across bifurcated insurance programs. To address this concern, policymakers have sought to expand integrated care plans (ICPs)—managed care plans that coordinate care and manage both Medicare and Medicaid services for duals. However, only ~1 in 10 duals is currently enrolled in an ICP. Furthermore, in recent years, a major threat to integration has emerged in the form of non-integrated Dual- Eligible Special Needs Plans (D-SNP) “look-alike” plans. These “look-alike” plans primarily serve duals, but unlike ICPs, they are not subject to federal and state requirements to provide coordinated Medicaid services. In 2023, the Centers for Medicare and Medicaid Services (CMS) instituted a new “80% rule” in which it stopped renewing contracts with any conventional, non-integrated MA plan where 80% or more of enrollees are duals. However, it remains unclear whether this policy will curb the growth of look-alike plans, catalyze enrollment in ICPs (especially among high-risk duals with dementia, mental illness, frailty, and from minoritized groups, who may disproportionately benefit from integrated coverage), or lead to meaningful improvements in quality, equity, and outcomes. Therefore, in Aim 1, we will evaluate the impact of the CMS 80% rule on enrollment changes of duals from look-alike plans into ICPs, and we will identify patient-, market-, and community-level factors associated with ICP enrollment. In Aim 2, we will determine the impact of the CMS 80% rule as a natural experiment—using a control group of plans slightly below the 80% threshold—to examine its effects on potentially avoidable or low-value care among duals previously enrolled in look-alike plans, and between duals who transition to ICPs vs. non-ICPs. Aim 3 will determine the impact of the 80% rule on changes in quality and clinical outcomes among duals from look-alike plans, and among those who transitioned into ICPs vs. non- ICPs. Across all aims, we will assess the impact of the 80% rule on a subset of high-risk duals who experience worse quality of care at baseline and have high levels of potentially avoidable and low value health care use, including duals with dementia, frailty, serious mental illness, complex multimorbidity, and among historically marginalized Black and Latino people. This study will provide critical insight into the effectiveness of the CMS policy to expand integrated care among duals, using the termination of plans above the 80% threshold as a natural experiment. It will a... ## Key facts - **NIH application ID:** 10944172 - **Project number:** 1RF1AG088640-01 - **Recipient organization:** HARVARD UNIVERSITY D/B/A HARVARD SCHOOL OF PUBLIC HEALTH - **Principal Investigator:** Jose Francisco Figueroa - **Activity code:** RF1 (R01, R21, SBIR, etc.) - **Funding institute:** NIH - **Fiscal year:** 2024 - **Award amount:** $2,283,522 - **Award type:** 1 - **Project period:** 2024-09-17 → 2027-08-31 ## Primary source NIH RePORTER: https://reporter.nih.gov/project-details/10944172 ## Citation > US National Institutes of Health, RePORTER application 10944172, Integrated Care Plans and Health Care Quality, Outcomes, and Equity for Medicare-Medicaid Dual Eligible Beneficiaries with Multimorbidity, Frailty, or Dementia (1RF1AG088640-01). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10944172. Licensed CC0. --- *[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*