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This article examines the relationship between hospital profitability and efficiency. A cross-section of 1317 U.S. metropolitan, acute care, not-for-profit hospitals for the year 2015 was employed. We use a frontier method, stochastic frontier analysis, to estimate hospital efficiency. Total margin and operating margin were used as profit variables in OLS regressions that were corrected for heteroskedacity. In addition to estimated efficiency, control variables for internal and external correlates of profitability were included in the regression models. We found that more efficient hospitals were also more profitable. The results show a positive relationship between profitability and size, concentration of output, occupancy rate and membership in a multi-hospital system. An inverse relationship was found between profits and academic medical centers, average length of stay, location in a Medicaid expansion state, Medicaid and Medicare share of admissions, and unemployment rate. The results of a Hausman test indicates that efficiency is exogenous in the profit equations. The findings suggest that not-for-profit hospitals will be responsive to incentives for increasing efficiency and use market power to increase surplus to pursue their objectives.
Multi-Institutional Systems, Medicaid, Organizations, Nonprofit, Length of Stay, Efficiency, Organizational, Financial Management, Hospital, Medicare, United States, Cross-Sectional Studies, Socioeconomic Factors, Hospital Bed Capacity, Data Interpretation, Statistical, Humans, Research Article, Bed Occupancy
Multi-Institutional Systems, Medicaid, Organizations, Nonprofit, Length of Stay, Efficiency, Organizational, Financial Management, Hospital, Medicare, United States, Cross-Sectional Studies, Socioeconomic Factors, Hospital Bed Capacity, Data Interpretation, Statistical, Humans, Research Article, Bed Occupancy
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 21 | |
popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |