Disentangling the clinical data chaos: User-centered interface system design for trauma centers

Author:

Park JaeYeonORCID,Rhim Soyoung,Han Kyungsik,Ko JeongGilORCID

Abstract

This paper presents a year-long study of our project, aiming at (1) understanding the work practices of clinical staff in trauma intensive care units (TICUs) at a trauma center, with respect to their usage of clinical data interface systems, and (2) developing and evaluating an intuitive and user-centered clinical data interface system for their TICU environments. Based on a long-term field study in an urban trauma center that involved observation-, interview-, and survey-based studies to understand our target users and their working environment, we designed and implemented MediSenseView as a working prototype. MediSenseView is a clinical-data interface system, which was developed through the identification of three core challenges of existing interface system use in a trauma care unit—device separation, usage inefficiency, and system immobility—from the perspectives of three staff groups in our target environment (i.e., doctors, clinical nurses and research nurses), and through an iterative design study. The results from our pilot deployment of MediSenseView and a user study performed with 28 trauma center staff members highlight their work efficiency and satisfaction with MediSenseView compared to existing clinical data interface systems in the hospital.

Funder

Yonsei University

National Research Foundation Korea

Publisher

Public Library of Science (PLoS)

Subject

Multidisciplinary

Reference78 articles.

1. “Big data” in the intensive care unit;L Anthony Celi;Closing the data loop,2013

2. Big data analytics in healthcare: promise and potential;W Raghupathi;Health Information Science and Systems,2014

3. Big data analytics in intensive care units: challenges and applicability in an Argentinian hospital;J Balladini;Journal of Computer Science & Technology,2015

4. Information technology in critical care: Review of monitoring and data acquisition systems for patient care and research;M De Georgia;Scientific World Journal,2015

5. Ghassemi M, Naumann T, Doshi-Velez F, Brimmer N, Joshi R, Rumshisky A, et al. Unfolding physiological state: Mortality modelling in intensive care units. In: Proceedings of the 20th ACM SIGKDD international conference on Knowledge discovery and data mining. ACM; 2014. p. 75–84.

Cited by 6 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3