2019
DOI: 10.1111/1475-6773.13188
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Comparing methods of grouping hospitals

Abstract: Objective To compare the performance of widely used approaches for defining groups of hospitals and a new approach based on network analysis of shared patient volume. Study Setting Non‐federal acute care hospitals in the United States. Study Design We assessed the measurement properties of four methods of grouping hospitals: hospital referral regions (HRRs), metropolitan statistical areas (MSAs), core‐based statistical areas (CBSAs), and community detection algorithms (CDAs). Data Extraction Methods We combine… Show more

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Cited by 7 publications
(9 citation statements)
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References 30 publications
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“…The community detection algorithm yields 363 distinct hospital markets for pediatric care in our data, similar to the market construction in Everson et al. (2019). The median market includes 275 unique zip codes and accounts for 159 procedures in our data.…”
Section: Data and Descriptive Statisticssupporting
confidence: 69%
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“…The community detection algorithm yields 363 distinct hospital markets for pediatric care in our data, similar to the market construction in Everson et al. (2019). The median market includes 275 unique zip codes and accounts for 159 procedures in our data.…”
Section: Data and Descriptive Statisticssupporting
confidence: 69%
“…We construct hospital markets based on observed patient flows using community detection methods. As shown in Everson et al (2019), such methods provide more reasonable measures of hospital markets than the commonly used Hospital Referral Regions (HRRs) or Hospital Service Areas (HSAs). Constructing our own markets is particularly important in our pediatric setting given that HSAs and HRRs derive from claims for Medicare beneficiaries.…”
Section: Market Definitionmentioning
confidence: 99%
See 1 more Smart Citation
“…The quality of a HSA delineation can be evaluated according to multiple and often conflicting metrics [7,3]. The following four delineation metrics of a HSA c were used: the number of communities (N C ), the localization index (LI c ),network conductance (C c ), and the total number of discharges (D c ).…”
Section: Evaluation Of Health Service Areas (Hsa) Delineationmentioning
confidence: 99%
“…Such comparative analysis is needed given the heterogeneity of communities extracted by different community detection algorithms [6]. Though such comparative analysis was previously provided for grouping hospitals [3], the underlying networks differ from HPDNs in two fundamental aspects: nodes were hospitals instead of geographical regions, and links were patients sharing between hospitals instead of the total number of hospital discharges.…”
Section: Introductionmentioning
confidence: 99%