As with many other parts of the NHS we have significant workforce challenges meaning that the clinical team can often not interact with as many patients as they would like. As a result a tool was developed that scores each patient based on a defined set of criteria. In theory, the patients with the highest score would benefit most from seeing a pharmacy professional. Feedback from the current system is that the score often doesn’t reflect the clinical priority of the patient and that it could be improved.
his project aims to enhance the existing Clinical Prioritisation Tool in our pharmacy department by introducing a machine learning and feedback loop system. The objective is to streamline the identification of high-risk patients and gather feedback from pharmacists and pharmacy technicians to improve the scoring accuracy over time.