Batman and Robin in Healthcare Knowledge Work: Human-AI Collaboration by Clinical Documentation Integrity Specialists

Author:

Bossen Claus1ORCID,Pine Kathleen H.2ORCID

Affiliation:

1. Digital Design & Information Studies, Aarhus University, Aarhus N, Denmark

2. College of Health Solutions, Arizona State University, Phoenix, AZ, USA

Abstract

This article describes the successful collaboration “in the wild” between Clinical Documentation Integrity Specialists (CDIS) and an Artificial Intelligence (AI)-embedded software to conduct knowledge work. CDIS review patient charts in near real-time to improve clinicians’ documentation, with the goal to make medical documentation more accurate, consistent and complete. CDIS collaborate with an AI-embedded “Computer Assisted Coding” (CAC) system that scans records from the Electronic Healthcare Record and auto-suggests codes based on natural language processing. CDIS find the CAC's suggestions are often inaccurate—often humorously so. Still, they find the CAC to be a useful helper, like Robin is to Batman. This human-AI collaboration is contingent on several factors: the flexible integration of the AI into the workflow similar to the notion of unremarkable AI; supporting the CDIS’ sensemaking; the CDIS’ knowledge about the CAC being predictably unreliable, an experience by the CDIS of the AI's value; humans remaining in control; and ability to experiment with the AI, which spurs reflection and learning for these knowledge workers.

Publisher

Association for Computing Machinery (ACM)

Subject

Human-Computer Interaction

Reference57 articles.

1. Guidelines for Human-AI Interaction

2. Sally L. Baxter, Jeremy S. Bass, and Amy M. Sitapati. 2020. Barriers to implementing an artificial intelligence model for unplanned readmissions. ACI Open 4, 2 (2020), e108--e113.

3. Does the Whole Exceed its Parts? The Effect of AI Explanations on Complementary Team Performance

4. S. Brayne and A. Christin. 2021. Technologies of crime prediction: The reception of algorithms in policing and criminal courts. Social Problems 68, 3 (2021), 608--624.

5. June Bronnert, Bonnie S. Cassidy, Shirley Eichenwald Maki, Heather Eminger James Flanagan, Mark Morsch, Kathleen Peterson, Kozie V. Phibbs, Hilip Resnik, Rita Scichilone, and Gail Smith. 2011. Cac 2010-11 Industry Outlook and Resources Report. American Health Information Management Association.

Cited by 16 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