Detailed Description
Title
Determining the Effects of Hospital Consolidation: An Examination of the Impact of Hospital M&A on Financial and Quality Metrics
Department(s)
Economics
Creator(s)
Advisor(s)
Date of Original
3/1/2018
Description
The modern explosion of M&A activity in the United States has generated significant controversy and advocates both for and against hospital consolidation have been quite vocal in presenting their cases. Using mergers and acquisitions reports from Irving Levin Associates as well as financial and quality metrics from the Centers for Medicare and Medicaid Services and the American Hospital Directory, this study examines the differences between consolidated and unconsolidated hospitals in terms of overall revenue and quality, in addition to prices and costs for specified diagnoses.
Consolidated hospitals undergo significant changes during their transition and oftentimes operate in a manner different than that of an unconsolidated hospital, suggesting that these figures will be different on a comparisonbasis.
To asses the differences between consolidated and unconsolidated hospitals, this paper uses Ordinary Least Squares regressions and three propensity score matching methods: nearest neighbor, kernel, and stratification matching. These matching methods are used to mitigate for the potential endogeneity associated with hospital M&A analysis.
This study finds that hospitals which underwent M&A between 2012 and 2014 have higher revenues but lower quality, while they charge lower prices and cost less to payers for several of the presented diagnoses. To make hospital mergers and acquisitions truly efficient, consolidated hospitals should strive to increase quality while continuing to operate in a financially efficient manner.
Consolidated hospitals undergo significant changes during their transition and oftentimes operate in a manner different than that of an unconsolidated hospital, suggesting that these figures will be different on a comparisonbasis.
To asses the differences between consolidated and unconsolidated hospitals, this paper uses Ordinary Least Squares regressions and three propensity score matching methods: nearest neighbor, kernel, and stratification matching. These matching methods are used to mitigate for the potential endogeneity associated with hospital M&A analysis.
This study finds that hospitals which underwent M&A between 2012 and 2014 have higher revenues but lower quality, while they charge lower prices and cost less to payers for several of the presented diagnoses. To make hospital mergers and acquisitions truly efficient, consolidated hospitals should strive to increase quality while continuing to operate in a financially efficient manner.
Genre
thesis
Publisher of Digital Record
Union College Schaffer Library Digital Projects
Source
Union College Schaffer Library Special Collections
Contact Information
Union College Schaffer Library Special Collections, 807 Union St., Schenectady, NY 12308; 518-388-6620; https://www.union.edu/schaffer-library
Harmful Language Statement
Language
English