Author: Rafay Nasir

Publisher:

Published: 2021

Total Pages:

ISBN-13:

The U.S. healthcare system is being constantly reformed. One popular policy proposal to overhaul the current healthcare system is to universally cover individuals under a single payer system of healthcare finance. Commonly known as "Medicare for All," this proposal is a substantial departure from the structure of the current American healthcare finance system; it requires the elimination of all private payers in favor of a single public payer. This study focuses specifically on determining the impact of universal single payer on Pennsylvania acute care hospital net patient revenue (NPR). Three research questions are explored in this investigation: What are the primary causal pathways of the implementation of universal single payer on Pennsylvania acute care hospital NPR? Assuming current Medicare payment rates and no change in hospital service utilization patterns, what changes in NPR would we expect for Pennsylvania hospitals after establishment of universal single payer? Assuming current Medicare payment rates and no change in hospital service utilization patterns, would changes in hospital NPR differ by county-level indicators of health determinants? This study first explores the potential impact of universal single payer on hospital NPR on a conceptual level, conducting a literature review and constructing a conceptual framework in the form of a Directed Acyclic Graph. Then, a quantitative analysis is conducted on current Pennsylvania hospitals to determine the precise impact that such a system would have. We use data from the 2019 Pennsylvania Health Care Cost Containment Council (PHC4) Financial Analysis, 2019 Centers for Medicare and Medicaid Services (CMS) Inpatient Prospective Payment System (IPPS) Proposed Rule Impact data, and 2018 County Health Rankings data to estimate the change in Pennsylvania hospital NPR associated with a shift from a mix of public and private payers to a single payer, based on the single payer adopting current Medicare payment rates and assuming that hospital service utilization does not change. These calculations are done using a generalized additive model (GAM) regression. We investigate whether those changes in revenues systematically differ based on demographics of the areas in which hospitals are located. This is followed and concluded with a discussion of what these results mean for the future of health policy and administration. Answering these questions will provide guidance to policy makers, hospital executives, and advocates.