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2022
- handle: 10670/1.v7sf4m
- halshs: halshs-01801598
- doi: 10.1186/s12913-021-07449-2
- PUBMEDCENTRAL: PMC8760746
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info:eu-repo/semantics/altIdentifier/doi/10.1186/s12913-021-07449-2
http://creativecommons.org/licenses/by/ , info:eu-repo/semantics/OpenAccess
Mots-clés
Volume outcome relationship France Epithelial Ovarian Cancer Instrumental variable Organization of care Care pathway Learning effect Centralization of care C - Mathematical and Quantitative Methods/C.C3 - Multiple or Simultaneous Equation Models • Multiple Variables/C.C3.C31 - Cross-Sectional Models • Spatial Models • Treatment Effect Models • Quantile Regressions • Social Interaction Models I - Health, Education, and Welfare/I.I1 - Health/I.I1.I11 - Analysis of Health Care Markets I - Health, Education, and Welfare/I.I1 - Health/I.I1.I18 - Government Policy • Regulation • Public Health L - Industrial Organization/L.L1 - Market Structure, Firm Strategy, and Market Performance/L.L1.L11 - Production, Pricing, and Market Structure • Size Distribution of FirmsSujets proches
Care and treatmentCiter ce document
Marius Huguet et al., « What underlies the observed hospital volume- outcome relationship? », Archive ouverte de Sciences Po (SPIRE), ID : 10.1186/s12913-021-07449-2
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Résumé
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.