Deriving optimal policies for selecting knee replacement patients for rapid recovery post-surgery using causal forest and policy tree

Project description

A hospital’s capacity, i.e., infrastructure and personnel, determines how many patients can be treated at any given time. Evidence from the literature suggests that hip and knee replacement patients benefit from a rapid recovery path (mobilization within 6h post-surgery) compared with a conventional recovery path (mobilization after 6h post-surgery). However, the rapid recovery path is more personnel intensive; thus patients qualifying for rapid recovery might not be put on this path due to capacity constraints. Therefore, assuming that capacity is fixed, a hospital aiming to maximize health outcomes needs to identify the patients that benefit the most from the rapid recovery path.  

We aim at determining the optimal assignment rule for the rapid recovery path under capacity constraints, and at identifying the welfare effects of its implementation. We aim to show that welfare can be increased without the need to change the hospital capacity, but simply through a better assignment of which patients get to follow the rapid recovery path. 


Project team

Johannes CordierIrene Salvi, Viktoria Steinbeck, Prof. Dr. Alexander GeisslerDr. Justus Vogel



Cooperation partner

Technical University of Berlin


Financing source




12 months (January 2023 to January 2024)