Summary
The objective of this study from Sharma et al. 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. They found that 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.
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