Project Summary Private equity acquisitions have accelerated in primary care, comprising thousands of physicians covering hundreds of thousands of lives across the U.S. Despite this growth, the effects of these acquisitions on clinical and economic outcomes remains unknown. Limited evidence in other parts of the delivery system, including nursing homes, hospitals, and procedural specialists, shows that PE acquisition is associated with higher prices and spending, as well as potential negative effects on quality. How PE ownership of primary care practices affects the health and health care of Medicare beneficiaries is a fundamental question, as Medicare covers primary care for nearly 60 million beneficiaries with chronic diseases - an AHRQ priority population. This proposal focuses on the specific mechanisms by which PE firms may affect provider behavior under different financial incentives in Traditional Medicare (TM) and Medicare Advantage (MA), and estimates effects on quality of care and patient outcomes. We propose to link primary care acquisition data to TM claims and MA encounter data from 2016-2024; using a quasi-experimental event study framework, we compare changes among beneficiaries in PE-acquired primary care practices with matched control beneficiaries of non-PE acquired primary care practices. In TM, we hypothesize that PE increases the utilization of services, and specifically low-value services like unnecessary or wasteful tests, imaging, or procedures. In MA, increased utilization can be counterproductive under a capitated budget, and we thus hypothesize that PE maximizes revenue through differentially more intensive coding of clinical diagnoses to garner higher risk-adjusted payments from the federal government. Our aims are to: 1) examine changes in provider behavior associated with PE acquisition of primary care practices, including utilization of low-value services and diagnostic coding intensity; 2) estimate changes in quality of care and patient outcomes; and 3) understand treatment effect heterogeneity, including by patient racial/ethnic and geographic composition, as well as by provider and practice characteristics. We apply a number of innovations, including the development of a novel dataset of PE acquisitions in primary care, which will be made publicly available for future use. In order to better approach causal inference, we also apply statistical innovations, including identification strategies in difference-in- differences analyses, risk set matching and cardinality matching to match a treated individual to comparable controls, and application of minimum variance balance weights. Findings will provide novel, timely, and comprehensive quantitative assessments of changes in key clinical and economic outcomes associated with a growing trend of PE ownership in primary care, and will be highly policy relevant as federal and state governments consider ways to preserve and support access to high-value primary care. 1