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A systematic review of the impact of volume of surgery and specialization on patient outcome
Abstract
Background and methods: Volume of surgery and specialization may affect patient outcome. Articles examining the effects of one or more of three variables (hospital volume of surgery, surgeon volume and specialization) on outcome (measured by length of hospital stay, mortality and complication rate) were analysed. Reviews, opinion articles and observational studies were excluded. The methodological quality of each study was assessed, a correlation between the variables analysed and the outcome accepted if it was significant. Results: The search identified 55 391 articles published between 1957 and 2002; 1075 were relevant to the study, of which 163 (9 904 850 patients) fulfilled the entry criteria. These 163 examined 42 different surgical procedures, spanning 13 surgical specialities. None were randomized and 40 investigated more than one variable. Hospital volume was reported in 127 studies; high-volume hospitals had significantly better outcomes in 74·2 per cent of studies, but this effect was limited in prospective studies (40 per cent). Surgeon volume was reported in 58 studies; high-volume surgeons had significantly better outcomes in 74 per cent of studies. Specialization was reported in 22 studies; specialist surgeons had significantly better outcomes than general surgeons in 91 per cent of studies. The benefit of high surgeon volume and specialization varied in magnitude between specialities. Conclusion: High surgeon volume and specialization are associated with improved patient outcome, while high hospital volume is of limited benefit.
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Metadata
- Authors
- Chowdhury, M. M., Dagash, H., & Pierro, A.
- Venue
- British Journal of Surgery
- Publisher
- Oxford University Press (OUP)
- Published
- 2007-01-29
- Volume
- 94
- Issue
- 2
- Pages
- 145-161
- ISSN
- 0007-1323 (ISSN-L)
- 1365-2168
- OpenAlex
- W2147944213
- Cited by
- 608
- References
- 115
- FWCI
- 5.45
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.