Predicting missed health care visits during the COVID-19 pandemic using machine learning methods: evidence from 55,500 individuals from 28 European Countries - Reuter, Anna; Smolić, Šime; Bärnighausen, Till; Sudharsanan, Nikkil (medRxiv, 2022)
Background The COVID-19 pandemic has led many individuals to miss essential care. Machine-learning models that predict which patients are at greatest risk of missing care visits can help health administrators prioritize retentions efforts towards patients with the most need. Such approaches may be especially useful for efficiently targeting interventions for health systems overburdened by the COVID-19 pandemic.
This version: February 28, 2022
Gesehen am 04.08.2022