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      Do More Hospital Beds Lead to Higher Hospitalization Rates? A Spatial Examination of Roemer’s Law

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          Abstract

          Background

          Roemer’s Law, a widely cited principle in health care policy, states that hospital beds that are built tend to be used. This simple but powerful expression has been invoked to justify Certificate of Need regulation of hospital beds in an effort to contain health care costs. Despite its influence, a surprisingly small body of empirical evidence supports its content. Furthermore, known geographic factors influencing health services use and the spatial structure of the relationship between hospital bed availability and hospitalization rates have not been sufficiently explored in past examinations of Roemer’s Law. We pose the question, “Accounting for space in health care access and use, is there an observable association between the availability of hospital beds and hospital utilization?”

          Methods

          We employ an ecological research design based upon the Anderson behavioral model of health care utilization. This conceptual model is implemented in an explicitly spatial context. The effect of hospital bed availability on the utilization of hospital services is evaluated, accounting for spatial structure and controlling for other known determinants of hospital utilization. The stability of this relationship is explored by testing across numerous geographic scales of analysis. The case study comprises an entire state system of hospitals and population, evaluating over one million inpatient admissions.

          Results

          We find compelling evidence that a positive, statistically significant relationship exists between hospital bed availability and inpatient hospitalization rates. Additionally, the observed relationship is invariant with changes in the geographic scale of analysis.

          Conclusions

          This study provides evidence for the effects of Roemer’s Law, thus suggesting that variations in hospitalization rates have origins in the availability of hospital beds. This relationship is found to be robust across geographic scales of analysis. These findings suggest continued regulation of hospital bed supply to assist in controlling hospital utilization is justified.

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          Most cited references42

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          Neighborhood of residence and incidence of coronary heart disease.

          Where a person lives is not usually thought of as an independent predictor of his or her health, although physical and social features of places of residence may affect health and health-related behavior. Using data from the Atherosclerosis Risk in Communities Study, we examined the relation between characteristics of neighborhoods and the incidence of coronary heart disease. Participants were 45 to 64 years of age at base line and were sampled from four study sites in the United States: Forsyth County, North Carolina; Jackson, Mississippi; the northwestern suburbs of Minneapolis; and Washington County, Maryland. As proxies for neighborhoods, we used block groups containing an average of 1000 people, as defined by the U.S. Census. We constructed a summary score for the socioeconomic environment of each neighborhood that included information about wealth and income, education, and occupation. During a median of 9.1 years of follow-up, 615 coronary events occurred in 13,009 participants. Residents of disadvantaged neighborhoods (those with lower summary scores) had a higher risk of disease than residents of advantaged neighborhoods, even after we controlled for personal income, education, and occupation. Hazard ratios for coronary events in the most disadvantaged group of neighborhoods as compared with the most advantaged group--adjusted for age, study site, and personal socioeconomic indicators--were 1.7 among whites (95 percent confidence interval, 1.3 to 2.3) and 1.4 among blacks (95 percent confidence interval, 0.9 to 2.0). Neighborhood and personal socioeconomic indicators contributed independently to the risk of disease. Hazard ratios for coronary heart disease among low-income persons living in the most disadvantaged neighborhoods, as compared with high-income persons in the most advantaged neighborhoods were 3.1 among whites (95 percent confidence interval, 2.1 to 4.8) and 2.5 among blacks (95 percent confidence interval, 1.4 to 4.5). These associations remained unchanged after adjustment for established risk factors for coronary heart disease. Even after controlling for personal income, education, and occupation, we found that living in a disadvantaged neighborhood is associated with an increased incidence of coronary heart disease.
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            An enhanced two-step floating catchment area (E2SFCA) method for measuring spatial accessibility to primary care physicians.

            Wei Luo, Yi Qi (2009)
            This paper presents an enhancement of the two-step floating catchment area (2SFCA) method for measuring spatial accessibility, addressing the problem of uniform access within the catchment by applying weights to different travel time zones to account for distance decay. The enhancement is proved to be another special case of the gravity model. When applying this enhanced 2SFCA (E2SFCA) to measure the spatial access to primary care physicians in a study area in northern Illinois, we find that it reveals spatial accessibility pattern that is more consistent with intuition and delineates more spatially explicit health professional shortage areas. It is easy to implement in GIS and straightforward to interpret.
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              The ecology of medical care revisited.

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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, USA )
                1932-6203
                2013
                13 February 2013
                : 8
                : 2
                : e54900
                Affiliations
                [1 ]Department of Geography, Michigan State University, East Lansing, Michigan, United States of America
                [2 ]Department of Geography, Center for Global Change and Earth Observations, Michigan AgBioResearch, Michigan State University, East Lansing, Michigan, United States of America
                [3 ]Georgetown University Medical Center, Washington, D.C., United States of America
                The University of Hong Kong, Hong Kong
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Conceived and designed the experiments: PLD JPM SCG VWP AMS. Contributed reagents/materials/analysis tools: PLD JPM SCG VWP AMS. Analyzed the data: PLD. Performed the experiments: PLD. Wrote the paper: PLD.

                Article
                PONE-D-12-18697
                10.1371/journal.pone.0054900
                3572098
                23418432
                249d4618-c648-4e43-a161-4a9b00250636
                Copyright @ 2013

                This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 22 June 2012
                : 17 December 2012
                Page count
                Pages: 16
                Funding
                This research was funded by the Michigan Department of Health, Certificate of Need Program. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Medicine
                Non-Clinical Medicine
                Health Care Policy
                Geographic and National Differences
                Health Economics
                Health Services Research
                Socioeconomic Aspects of Health
                Public Health
                Behavioral and Social Aspects of Health
                Social and Behavioral Sciences
                Economics
                Health Economics
                Cost-Minimization Analysis
                Health Care Sector
                Geography
                Human Geography
                Spatial Analysis

                Uncategorized
                Uncategorized

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