A Collaborative Filtering Recommender System in Primary Care

Abstract

We propose a collaborative filtering recommender system to match patients with doctors in primary care. In particular, we model patient trust in primary care doctors using a large-scale dataset of consultation histories, and account for the temporal dynamics of their relationships, defined in a novel quantitative measure of patient-doctor trust. Our proposed approach shows higher predictive accuracy than a heuristic baseline, as well as a collaborative filtering approach without the trust measures.