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Volumn 30, Issue 9, 2011, Pages 1728-1733

The increased concentration of health plan markets can benefit consumers through lower hospital prices

Author keywords

[No Author keywords available]

Indexed keywords

ARTICLE; CONSUMER; COST BENEFIT ANALYSIS; HEALTH CARE PLANNING; HEALTH CARE POLICY; HEALTH ECONOMICS; HOSPITAL COST;

EID: 84855643207     PISSN: 02782715     EISSN: 15445208     Source Type: Journal    
DOI: 10.1377/hlthaff.2010.0406     Document Type: Article
Times cited : (47)

References (31)
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    • Madison and Chakravarty's data for system membership are from the American Hospital Association. We updated the data with merger acquisition data from other sources such as Modern Healthcare, a hospital trade publication. We checked the data using a hospital systems database constructed for California hospitals, which has a high degree of correlation with Madison and Chakravarty's database
    • Madison and Chakravarty's data for system membership are from the American Hospital Association. We updated the data with merger acquisition data from other sources such as Modern Healthcare, a hospital trade publication. We checked the data using a hospital systems database constructed for California hospitals, which has a high degree of correlation with Madison and Chakravarty's database.
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    • We performed several tests. First, to test for the possibility that the market penetration of health maintenance organizations is not random, we followed previous studies, reestimating our models but using labor market characteristics that others have used to predict managed care penetration. The results from this test were similar to those in our original models. Second, since payer-mix data were not available for adjusted days, we used payer-specific discharge data to construct payer mix measures, finding that adjusted days and admissions were highly correlated (0.84). And third, we used pooled data across years to provide more precise estimates (the pooled coefficients were essentially the weighted average of the coefficients from the two separate models)
    • We performed several tests. First, to test for the possibility that the market penetration of health maintenance organizations is not random, we followed previous studies, reestimating our models but using labor market characteristics that others have used to predict managed care penetration. The results from this test were similar to those in our original models. Second, since payer-mix data were not available for adjusted days, we used payer-specific discharge data to construct payer mix measures, finding that adjusted days and admissions were highly correlated (0.84). And third, we used pooled data across years to provide more precise estimates (the pooled coefficients were essentially the weighted average of the coefficients from the two separate models).
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    • Adjusted patient days equals actual inpatient days plus the estimated equivalent of inpatient days associated with the hospitals' outpatient volume, based on the methodology that the American Hospital Association uses to estimate a single measure for the total hospital output
    • Adjusted patient days equals actual inpatient days plus the estimated equivalent of inpatient days associated with the hospitals' outpatient volume, based on the methodology that the American Hospital Association uses to estimate a single measure for the total hospital output.
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    • Under this specification, the dependent variable becomes the average revenue per unit of output (adjusted patient days), and the estimated coefficients for the other variables can be interpreted as the marginal relationship between the independent variables, including concentration measures, on average hospital price.
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    • We measured each hospital's market separately, using actual hospitalspecific ZIP code-level data on patient flow and following the detailed method described in Note 13. We used Medicare discharge data to construct annual, hospital-specific indexes based on each hospital's geographic market, adjusted for hospitals that are part of multihospital systems with other members in the same geographic market
    • We measured each hospital's market separately, using actual hospitalspecific ZIP code-level data on patient flow and following the detailed method described in Note 13. We used Medicare discharge data to construct annual, hospital-specific indexes based on each hospital's geographic market, adjusted for hospitals that are part of multihospital systems with other members in the same geographic market.
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* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.