ArticleBMJ health & care informatics2023
Accuracy of a tool to prioritise patients awaiting elective surgery: an implementation report.
Article in BMJ health & care informatics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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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.
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Who cites it
1 citing paper in PubMed.
- Ethical aspects of waiting lists in neurosurgery.Acta neurochirurgica · 2026Review
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
STUDY
objectiveThe objective of this study was to evaluate the accuracy of a new elective surgery clinical decision support system, the 'Patient Tacking List' (PTL) tool (C2-Ai(c)) through receiver operating characteristic (ROC) analysis.
methodsWe constructed ROC curves based on risk predictions produced by the tool and compared these with actual patient outcomes on a retrospective cohort of patients awaiting elective surgery.
resultsA total of 11 837 patients were included across three National Health Service (NHS) hospitals in England. ROC analysis revealed an area under the curve of 0.95 (95% CI 0.92 to 0.98) for mortality and 0.8 (95% CI 0.78 to 0.82) for complications. DISCUSSION: The PTL tool was successfully integrated into existing data infrastructures, allowing real-time clinical decision support and a low barrier to implementation. ROC analysis demonstrated a high level of accuracy to predict the risk of mortality and complications after elective surgery. As such, it may be a valuable adjunct in prioritising patients on surgical waiting lists.Health systems, such as the NHS in England, must look at innovative methods to prioritise patients awaiting surgery in order to best use limited resources. Clinical decision support tools, such as the PTL tool, can improve prioritisation and thus positively impact clinical care and patient outcomes.
conclusionsThe high level of accuracy for predicating mortality and complications after elective surgery using the PTL tool indicates the potential for clinical decision support tools to help tackle rising waiting lists and improve surgical planning.
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