Ashis Kumar Chanda, Tian Bai, Brian L Egleston, Slobodan Vucetic
{"title":"MedCV:从医疗索赔数据中识别患者队列的交互式可视化系统。","authors":"Ashis Kumar Chanda, Tian Bai, Brian L Egleston, Slobodan Vucetic","doi":"10.1145/3511808.3557157","DOIUrl":null,"url":null,"abstract":"<p><p>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.</p>","PeriodicalId":74507,"journal":{"name":"Proceedings of the ... ACM International Conference on Information & Knowledge Management. ACM International Conference on Information and Knowledge Management","volume":"2022 ","pages":"4828-4832"},"PeriodicalIF":0.0000,"publicationDate":"2022-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9830554/pdf/","citationCount":"2","resultStr":"{\"title\":\"MedCV: An Interactive Visualization System for Patient Cohort Identification from Medical Claim Data.\",\"authors\":\"Ashis Kumar Chanda, Tian Bai, Brian L Egleston, Slobodan Vucetic\",\"doi\":\"10.1145/3511808.3557157\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>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.</p>\",\"PeriodicalId\":74507,\"journal\":{\"name\":\"Proceedings of the ... ACM International Conference on Information & Knowledge Management. ACM International Conference on Information and Knowledge Management\",\"volume\":\"2022 \",\"pages\":\"4828-4832\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9830554/pdf/\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the ... ACM International Conference on Information & Knowledge Management. ACM International Conference on Information and Knowledge Management\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3511808.3557157\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2022/11/4 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the ... ACM International Conference on Information & Knowledge Management. ACM International Conference on Information and Knowledge Management","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3511808.3557157","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2022/11/4 0:00:00","PubModel":"Epub","JCR":"","JCRName":"","Score":null,"Total":0}
MedCV: An Interactive Visualization System for Patient Cohort Identification from Medical Claim Data.
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.