Dissatisfaction rates after TKA are reported to be between 15 – 25%, with unmet outcome expectations being a key contributor. Shared decision making tools (SDMT) are designed to align a patient's and surgeon's expectations. This study demonstrates clinical validation of a patient specific shared decision making tool. Patient reported outcome measures (PROMs) were collected in 150 patients in a pre-consultation environment of one surgeon. The data was processed into a probabilistic predictive model utilising prior data to generate a preoperative baseline and an expected outcome after TKA. The surgeon was blinded to the prediction algorithm for the first 75 patients and exposed for the following 75 patients. PROMs collected were the knee injury and osteoarthritis outcome score (KOOS) and questions on lower back pain, hip pain and falls. The patients booked and not booked before and after exposure to the prediction were collected. The clinical validation involved 27 patients who had their outcome predicted and had their PROMs captured at 12 months after TKA. The predicted change in severity of pain and the patients actual change from pre-op to 12 month post operative KOOS pain was analysed using a Spearman's Rho correlation. Further analysis was performed by dividing the group into those predicted by the model to have improved by more than 10 percentile points and those who were predicted to improve by less than 10 percentile points.Introduction
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