Rapid recovery (RR) is a post-surgery recovery path which entails the mobilization of patients within 6h after joint replacement. Evidence from the literature has focused on the ability of RR to decrease the length of stay, confirmed cost savings for hospitals, and suggested that also patients benefit from RR compared with conventional care (CC). However, no study has so far investigated the payer’s perspective regarding the cost-utility and cost-effectiveness of RR as opposed to CC after knee replacement.
In this project, we implement an innovative approach to determine the cost-utility and cost-effectiveness of RR for knee replacements from the payer’s perspective by exploiting a machine learning methodology for the analysis of retrospective observational data.
Irene Salvi, Lukas Schöner, Johannes Cordier, Dr. Justus Vogel
Technical University of Berlin
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12 Monate (Juli 2023 bis Juli 2024)