An Interpretable Algorithm on Post-injury Health Service Utilization Patterns to Predict Injury Outcomes
Hadi Akbarzadeh Khorshidi, Behrooz Hassani-Mahmooei, Gholamreza Haffari
JOURNAL OF OCCUPATIONAL REHABILITATION | SPRINGER/PLENUM PUBLISHERS | Published : 2019
Purpose Post-injury health service utilization (HSU) contributes to injury outcomes, but limited studies investigated their relationship. This study aims to group injured patients in transport accidents based on minimal historical information of their HSU so that the groups are meaningfully associated with the outcome of interest. Methods The data include 20,692 injured patients who had compensation claims over 3 years. We propose a hybrid approach, combining unsupervised and supervised machine learning methods. Based on the first week post-injury data, we identify a proper clustering of patients best associated with total cost to recovery, as well as the discovery of HSU patterns. This allo..View full abstract
This study is funded by Transport Accident Commission (TAC) through the Institute of Safety, Compensation and Recovery Research (ISCRR).