Validating the electronic Post Operative Morbidity Survey
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AI plain-English summaryEvery day in UK hospitals, nurses and doctors manually tick boxes to record whether a patient has developed complications after surgery—a slow, paper-based process that is ripe for error and eats up clinical time. This project tests whether an automated system called ePOMS can do the same job by pulling information directly from a patient’s electronic health record, without any extra human effort. The researchers will collect post-operative complication data manually using the existing Post Operative Morbidity Survey (POMS), then compare those scores with the automatically generated ePOMS scores. The goal is to prove that the electronic version is equivalent in accuracy. If ePOMS works, hospitals could track surgical outcomes in real time, without burdening staff with extra data entry. That would allow earlier detection of complications, more efficient use of resources, and better comparisons of surgical quality across wards and hospitals. The change would be invisible to patients but could quietly improve the safety and efficiency of post-surgical care across the NHS.
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