Predicting Practice Setting Using Topic Modeling

The implementation of problem lists in EHRs has a potential to help practitioners to provide customized care to patients. However, it remains an open question on how to leverage problem lists in different practice settings to provide tailored care, of which the bottleneck lies in the associations between problem list and practice setting. In this study, we investigated their association and predicted practice setting based on problem list using topic modeling.