Machine learning versus regression modelling in predicting individual healthcare costs from a representative sample of the nationwide claims database in France.
Journal:
The European journal of health economics : HEPAC : health economics in prevention and care
PMID:
34373958
Abstract
BACKGROUND: Innovative provider payment methods that avoid adverse selection and reward performance require accurate prediction of healthcare costs based on individual risk adjustment. Our objective was to compare the performances of a simple neural network (NN) and random forest (RF) to a generalized linear model (GLM) for the prediction of medical cost at the individual level.