Evidence map›Paper›PMID 31689806›Full record

SynthesisMedicine2019

Association of hospital and surgeon volume with mortality following major surgical procedures: Meta-analysis of meta-analyses of observational studies.

Hiroshi Hoshijima, Zen'ichiro Wajima, Hiroshi Nagasaka, Toshiya Shiga

Open access · goldAbstract readMeta-Analysis
In one paragraph

Synthesis in Medicine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed, 2 pooled it
2.3field-weighted citation impact, top 10% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

12 citing papers in PubMed, 2 syntheses or guidelines pooled it, 28 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. [Minimum case volumes from the perspective of specialists in smaller facilities].Der Chirurg; Zeitschrift fur alle Gebiete der operativen Medizen · 2022
    Review
  10. Article
  11. The Benefits of Robotic Surgery: Are They Technical or Molecular?Journal of gastrointestinal surgery : official journal of the Society for Surgery of the Alimentary Tract · 2021
    Article
  12. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors at 2 institutions in 1 country.

Hiroshi HoshijimaDepartment of Anesthesiology, Saitama Medical University Hospital, Saitama.
Zen'ichiro WajimaDepartment of Anesthesiology, Tokyo Medical University Hachioji Medical Center, Tokyo.
Hiroshi NagasakaDepartment of Anesthesiology, Saitama Medical University Hospital, Saitama.
Toshiya ShigaDepartment of Anesthesiology and Intensive Care Medicine, International University of Health and Welfare Ichikawa Hospital, Ichikawa, Chiba, Japan.
Saitama Medical University Hospital · JPTokyo Medical University Hachioji Medical Center · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Accumulation of the literature has suggested an inverse association between healthcare provider volume and mortality for a wide variety of surgical procedures. This study aimed to perform meta-analysis of meta-analyses (umbrella review) of observational studies and to summarize existing evidence for associations of healthcare provider volume with mortality in major operations.We searched MEDLINE, SCOPUS, and Cochrane Library, and screening of references.Meta-analyses of observational studies examining the association of hospital and surgeon volume with mortality following major operations. The primary outcome is all-cause short-term morality after surgery. Meta-analyses of observational studies of hospital/surgeon volume and mortality were included. Overall level of evidence was classified as convincing (class I), highly suggestive (class II), suggestive (class III), weak (class IV), and non-significant (class V) based on the significance of the random-effects summary odds ratio (OR), number of cases, small-study effects, excess significance bias, prediction intervals, and heterogeneity.Twenty meta-analyses including 4,520,720 patients were included, with 19 types of surgical procedures for hospital volume and 11 types of surgical procedures for surgeon volume. Nominally significant reductions were found in odds ratio in 82% to 84% of surgical procedures in both hospital and surgeon volume-mortality associations. To summarize the overall level of evidence, however, only one surgical procedure (pancreaticoduodenectomy) fulfilled the criteria of class I and II for both hospital and surgeon volume and mortality relationships, with a decrease in OR for hospital (0.42, 95% confidence interval[CI] [0.35-0.51]) and for surgeon (0.38, 95% CI [0.30-0.49]), respectively. In contrast, most of the procedures appeared to be weak or "non-significant."Only a very few surgical procedures such as pancreaticoduodenectomy appeared to have convincing evidence on the inverse surgeon volume-mortality associations, and yet most surgical procedures resulted in having weak or "non-significant" evidence. Therefore, healthcare professionals and policy makers might be required to steer their centralization policy more carefully unless more robust, higher-quality evidence emerges, particularly for procedures considered as having a weak or non-significant evidence level including total knee replacement, thyroidectomy, bariatric surgery, radical cystectomy, and rectal and colorectal cancer resections.

Indexed as

Hospital MortalityFemaleHospitalsHospitals, High-VolumeHospitals, Low-VolumeHumansMaleMeta-Analysis as TopicObservational Studies as TopicOdds RatioSurgeonsSurgical Procedures, Operative

Identifiers

PMID31689806
PMCPMC6946306
OpenAlexW2987460739

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.