MedCV: An Interactive Visualization System for Patient Cohort Identification from Medical Claim Data.

Proceedings of the ... ACM International Conference on Information & Knowledge Management. ACM International Conference on Information and Knowledge Management Pub Date : 2022-10-01 Epub Date: 2022-11-04 DOI:10.1145/3511808.3557157

Ashis Kumar Chanda, Tian Bai, Brian L Egleston, Slobodan Vucetic

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引用次数: 2

Abstract

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.

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MedCV:从医疗索赔数据中识别患者队列的交互式可视化系统。

医疗保健提供者在每次患者就诊后生成医疗索赔。医疗索赔包括描述诊断和就诊期间提供的任何治疗的医疗代码列表。医学索赔作为回顾性队列研究的数据来源在医学研究中很受欢迎。本文介绍了一个医疗索赔可视化系统（MedCV），该系统支持从医疗索赔数据中进行队列选择。MedCV是与临床研究人员和统计学家合作开发的设计研究的一部分。它通过揭示医疗代码之间的关系以及可视化医疗索赔和患者时间表，帮助研究人员定义队列选择的纳入规则。通过用户研究对我们的系统进行的评估表明，MedCV使领域专家能够以高效的方式定义高质量的包含规则。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Proceedings of the ... ACM International Conference on Information & Knowledge Management. ACM International Conference on Information and Knowledge Management

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