The convergence between for-profit and nonprofit hospitals in the United States (original) (raw)
Related papers
The RAND Journal of Economics, 2003
Our objective is to determine the effect of ownership type (for-profit, not-for-profit, government) on firm conduct in hospital markets. Secondary objectives include estimating hospital demand systems useful for market definition and merger simulation. To this end, we estimate a structural model of demand and pricing in the short term hospital industry in California, and then use the estimates to simulate the effect of a merger. Demand is modeled at the level of individual consumers using discrete choice techniques and micro data on individuals. Price in the demand equation is endogenous, and we use recently developed instrumental variables techniques to correct for this. We allow the behavior of for-profit and not-for-profit firms to differ, modeling these differences structurally following the relevant theory literature. We find that California hospitals in 1995 faced a downward-sloping demand for their products, with an average price elasticity of demand of -5.67.
Hospital competition in major U.S. metropolitan areas: An empirical evidence
The Journal of Socio-Economics, 1999
In response to dramatic rises in health care costs, policymakers have been debating the relative merits of competitive strategies as a means of containing costs. We study the 29 largest metropolitan statistical areas for 1991, and controlling for environmental conditions in each market, we examined the impact of competition on hospital costs. We conclude that competition had a significant positive impact on overall hospital costs.
Research Methodologies in Studies on Concentration of American Hospitals
The objective of this study is to know which methodologies and databases that were used in articles treat variables, such as efficiency and costs in the hospital segment and their relationship with the concentration of American organizations. The quantitative methodologies used were, by order of preference, the multivariate statistical analysis and the econometric analysis. The most used data basis was the Annual Report of the American Hospital Association (AHA), followed by data made available by insurance companies having long lasting relationships with the hospitals analyzed, besides the specific case studies. Finally, it was observed that the concentration in the sector is reflected in the reduction in competition and efficiency gains, notably in the first year after the fusion, which does not mean that there was reduction in the prices charged by the hospitals.
Measures of hospital market structure: a review of the alternatives and a proposed approach
Socio-Economic Planning Sciences, 1990
Efforts to evaluate the plethora of recent programs adopted by public and private payers to promote hospital price competition critically depend on the availability of measures of local market structure. To gauge the effects of these policies, researchers must be able to delineate hospital market areas and measure the intensity of competition within these markets. This article reviews alternative methods that have been used to define hospital market areas and measure market structure. We propose an empirical patient origin-based method for measuring hospital market structure. The results of sensitivity analyses using data on California hospitals demonstrate the robustness ofour measures over a broad range of parameter values.
Factors Impacting Market Concentration of Not-for-Profit Hospitals
Journal of Business Ethics, 2017
We attempt to identify and evaluate the association between key characteristics of not-for-profit (NP) hospitals and market concentration, as measured by the Herfindahl-Hirschman Index, using data available from the American Hospital Association, the Centers for Medicare and Medicaid Services, and the Internal Revenue Service Form 990. Our goal is to provide decision support to policy makers on factors that contribute to market competitiveness, which has been linked to improvements in efficiency, costs, and access to health care. We find that contributions are positively associated with market concentration. This could indicate that well-run NP hospitals (that deliver on their mission) are rewarded both financially (through increased contributions) as well as with increased market share. We also find that a higher percentage of Medicare patients is positively correlated with market concentration (i.e., reduces the competitiveness of the NP market). This could be explained by the fact that Medicare reimbursement rates are generally lower than those paid by private insurers (approximately 80%); thus, hospitals might not necessarily choose to operate in areas with high Medicare populations. Further, median income is negatively associated with market concentration. One explanation for this effect could be the fact that a population with a higher median income is in a better position to pay for services, making them attractive to hospitals as a potential market. Finally, we find that the presence of managers with voting rights on the boards of directors has no significant impact.
1976
BARRY R. CHISWICK Sun mr Soft Fr (mcUti1uit (ou fl(ii 01 hut irtcinl i Adv se,-. Hospital Utilization: An Analysis of SMSA Differences in Occupancy Rates, Admission Rates, and Bed Rates. The national surpluS of hospital cds by no means t ()fltrdth(t.c the tact that there are frequent shortagu In particular con mumtmes at particular fruit's The New York Times, Editorial, August 26, I ¶17 ABSTRACT: This study examines the determinants of regional differences in the utilization of short-term general hospitals in Standard Metropolitan Statistical Areas (SMSAs) in 1967. Three interrelated dependent variables are used: the bed rate (the number of beds per thousand population), the occupancy rate (the proportion of days iii the year the average bed is occupied), and the admission rate (the number of admissions per thousand population). ¶ The analyses of the occu-NOTr: This study has lwrietaed substantially from c rnrnents received 1mm dOduals and at various seminars. My thanks go, in par*icuias, to (:arniel U. Chisst di. Victor Fuchs, Michael Grossman, Fdssard Hughes, Bruce Zeilner, the NBER staff reading conimItee-0tte Ross han. Henry Grabowski, arid Ms'lsin Rester-ansI the NBER Board of Directms reading comrnitteeAtherton Bean. Charles Berry, and Nathaniel Gnldfinger. The seminars ssere gisen at the National Bureau of [cononuic Research, c.ljN.y. (Grjduate Schooll. th University of Chicago, the Uniu'rsity of Maryland, and at the Health Services Administration 01 New York City, appreciate he research assistance of Carrul Breckner and Phyllis Goldberg hi, data collc-clion and or lanice PlaIt and Christine Wilson for data proi,essing. ansI thank Hecty 0. leliinm-k for her editing and H. Irving For,rian for his charts. The project was financed in part by a grant to the Natic,nal Bureau from the National Center for Health Services Research arid Development (Grant No. SPOIHSOO4StI and by the Industrial Rr-latinnt Section, Prim eton University. I alone an'i meslx)nsihle for any errors 01 cornnuu5sion or omission, and for the viests espressed in this paper, which are riot necessarily those of th CEA Parts ot this monograph have appeared in the Proceedings of the Arnt'rican Statistur al Association and the frmurnal of Urban waomics, and appear here Oth their permission 326 t Hospital Utilization: SMSA Differences in Rates 327 pancy rate and the bed rate are largely i)ased on the existence of short-run (stochasticI variations in the demand br hospital care. Because of the costs of constructing and maintain;ng rarely used capacity and the costs associated with delayed treatment due to insutticient capacity, the randomness of deniand for care is an essential ingredient in hospital planning. The empirical analysis indicates that the hospital sector appears to respond to the short-run variations in demand, to the cost of delayed treatment, and to a positive income elasticity of demand for available hospital beds. ¶ Beds in different hospitals are now imperfect substitutes for each other. Hospital facilities could be used more efficiently by coordinating admissions among hospitals in an SMSA and by removing artificial barriers to admission in particular hospitals (e.g., veteran status). With the existing stock of beds, a coordinated admissions policy would give the average SMSA an excess bed capacity in all but one week in about thirteen years. This would appear to represent "too much' capacity. ¶ The analysis indicates that hospital admission rates are greater in SMSAs where there is more hospital and surgical insurance coverage, more unused capacity (lower occupancy rate, greater bed rate), more surgeons per capita, an absence of HMOs, and more nonwhites. The presence of nonsurgical MDs is apparently not related to hospital admissions. 1974 St)URCES-946 to 1960: Histon ai5tatiiic of hc (Jrit.J Sats roar (vhnial Trrnrs to the t,'orr:
Local Hospital Competition in Large Metropolitan Areas
Journal of Economics <html_ent glyph="@amp;" ascii="&"/> Management Strategy, 1994
This paper uses origin-destination data to define geographic local hospital markets in large metropolitan statistical areas (MSAs). Results support past findings of service rather than price competition, with negatiue-cost Herfandahl-Hirschman indexes relationships at the market Ieuel ( a i d sub-MSA level) and with profit margins izegafiuely related to hospital market competition. The effects of total (direct plus indirect) market competition are unchanged between 1983 and 1988, precisely estimated, robust to estimation techniques, and unaffected by whether the number of direct competitors is included as an explanatory variable.