In Proceedings of the ... ACM International Conference on Information & Knowledge Management. ACM International Conference on Information and Knowledge Management
Healthcare providers generate a medical claim after every patient visit. A medical claim consists of a list of medical codes describing the diagnosis and any treatment provided during the visit. Medical claims have been popular in medical research as a data source for retrospective cohort studies. This paper introduces a medical claim visualization system (MedCV) that supports cohort selection from medical claim data. MedCV was developed as part of a design study in collaboration with clinical researchers and statisticians. It helps a researcher to define inclusion rules for cohort selection by revealing relationships between medical codes and visualizing medical claims and patient timelines. Evaluation of our system through a user study indicates that MedCV enables domain experts to define high-quality inclusion rules in a time-efficient manner.
Chanda Ashis Kumar, Bai Tian, Egleston Brian L, Vucetic Slobodan
2022-Oct
Medical claims, cohort identification, deep learning, electronic health records, embedding, retrospective study, visual analytics
