Vincent Ochs, Anja Tobler, Bassey Enodien, Baraa Saad, Stephanie Taha-Mehlitz, Julia Wolleb, Joelle El Awar, Katerina Neumann, Susanne Drews, Ilan Rosenblum, Reinhard Stoll, Robert Rosenberg, Daniel M Frey, Philippe C Cattin, Anas Taha
Hospitals are facing difficulties in predicting, evaluating, and managing cost-affecting parameters in patient treatments. Inaccurate cost prediction leads to a deficit in operational revenue. This study aims to determine the ability of Machine Learning (ML) algorithms to predict the cost of care in bariatric and metabolic surgery and develop a predictive tool for improved cost analysis. 602 patients who underwent bariatric and metabolic surgery at Wetzikon hospital from 2013 to 2019 were included in the study...
October 28, 2023: Obesity Research & Clinical Practice