ArticleMedical care2020
Estimating the Net Benefit of Improvements in Hospital Performance: G-Computation With Hierarchical Regression Models.
Article in Medical care, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
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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.
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.
Who cites it
2 citing papers in PubMed.
- Case-mix adjustment through inverse probability weighting to compare health indicators across territories or providers - an application in the agency for health protection of Milan.BMC health services research · 2025Article
- Effect of out-of-village working activities on recent malaria exposure in the Peruvian Amazon using parametric g-formula.Scientific reports · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
backgroundIt is important to be able to estimate the anticipated net population benefit if the performance of hospitals is improved to specific standards.
objectiveThe objective of this study was to show how G-computation can be used with random effects logistic regression models to estimate the absolute reduction in the number of adverse events if the performance of some hospitals within a region was improved to meet specific standards. RESEARCH
designA retrospective cohort study using health care administrative data. SUBJECTS: Patients hospitalized with acute myocardial infarction in the province of Ontario in 2015.
resultsOf 18,067 patients hospitalized at 97 hospitals, 1441 (8.0%) died within 30 days of hospital admission. If the performance of the 25% of hospitals with the worst performance had their performance changed to equal that of the 75th percentile of hospital performance, 3.5 deaths within 30 days would be avoided [95% confidence interval (CI): 0.4-26.5]. If the performance of those hospitals whose performance was worse than that of an average hospital had their performance changed to that of an average hospital, 6.0 deaths would be avoided (95% CI: 0.7-47.0). If the performance of the 75% of hospitals with the worst performance had their performance changed to equal that of the 25th percentile of hospital performance, 11.0 deaths would be avoided (95% CI: 1.2-79.0).
conclusionG-computation can be used to estimate the net population reduction in the number of adverse events if the performance of hospitals was improved to specific standards.
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Registered trials
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.