Open AccessMedCV: An Interactive Visualization System for Patient Cohort Identification from Medical Claim Data
Author(s) -
Ashis Kumar Chanda,
Brian L. Egleston,
Tian Bai,
Slobodan Vučetić
Publication year - 2022
Publication title -
proceedings of the 31st acm international conference on information andamp; knowledge management
Language(s) - English
Resource type - Conference proceedings
pISSN - 2155-0751
DOI - 10.1145/3511808.3557157
Subject(s) - timeline , computer science , cohort , visualization , medical record , inclusion (mineral) , data visualization , domain (mathematical analysis) , identification (biology) , information visualization , data science , information retrieval , data mining , medicine , psychology , statistics , social psychology , mathematical analysis , botany , mathematics , radiology , biology
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.