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What underlies the observed hospital volume-outcome relationship?

Marius Huguet (), Xavier Joutard, Isabelle Ray-Coquart and Lionel Perrier
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Marius Huguet: Univ Lyon, Université Lumière Lyon 2, GATE UMR 5824, F-69130 Ecully, France
Xavier Joutard: Aix Marseille Univ, CNRS, LEST, Aix-en-Provence; OFCE, sciences Po, Paris
Isabelle Ray-Coquart: Univ Lyon, Université Claude Bernard Lyon 1, Centre Léon Bérard, EA7425 HESPER, F-69008 Lyon, France
Lionel Perrier: Univ Lyon, Université Lumière Lyon 2, Centre Léon Bérard, GATE UMR 5824, F-69008 Lyon, France

No 1809, Working Papers from Groupe d'Analyse et de Théorie Economique Lyon St-Étienne (GATE Lyon St-Étienne), Université de Lyon

Abstract: Studies of the hospital volume-outcome relationship have highlighted that a greater volume activity improves patient outcomes. While this finding has been known for years in health services research, most studies to date have failed to delve into what underlies this relationship. This study aimed to shed light on the basis of the hospital volume effect by comparing treatment modalities for epithelial ovarian carcinoma patients. Hospital volume activity was instrumented by the distance from patients’ homes to their hospital, the population density, and the median net income of patient municipalities. We found that higher volume hospitals appear to more often make the right decisions in regard to how to treat patients, which contributes to the positive impact of hospital volume activities on patient outcomes. Based on our parameter estimates, we found that the rate of complete tumor resection would increase by 10% with centralized care, and by 6% if treatment decisions were coordinated by high volume centers compared to the ongoing organization of care. In both scenarios, the use of neoadjuvant chemotherapy would increase by 10%. As volume alone is an imperfect correlate of quality, policy makers need to know what volume is a proxy for in order to devise volume-based policies.

Keywords: Volume outcome relationship; France; Epithelial Ovarian Cancer; Instrumental variable; Organization of care; Care pathway; Learning effect; Centralization of care (search for similar items in EconPapers)
JEL-codes: C31 C36 I11 I18 L11 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-eur and nep-hea
Date: 2018
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