Clinical Decision Support Opportunities among Clinicians Caring for People Receiving Invasive Mechanical Ventilation: A Cross-sectional Survey

Author:

Weissman Gary E.,Bishop Nicholas S.,Schmid Benjamin E.,Madden Vanessa,Pirracchio Romain,Jentzer Jacob C.,Riman Kathryn A.,Krutsinger Dustin C.,DiGiovine Bruno,Ungar Lyle H.,Halpern Scott D.,Auriemma Catherine L.,Valley Thomas S.,Kerlin Meeta Prasad

Abstract

AbstractTreatment decisions for patients receiving invasive mechanical ventilation (IMV) are complex and depend simultaneously on the current ventilator settings, the function of multiple interrelated organ systems, and other treatments. An artificial intelligence (AI)-based clinical decision support system (CDSS) offers a promising approach to alleviate uncertainty in this complex management and provide personalized treatment recommendations. However, little is known about clinician preferences for which treatment decisions clinicians think would most benefit from a CDSS. Therefore, we conducted a cross-sectional electronic survey of practicing physicians, nurses, advanced practice providers, and respiratory therapists to identify key treatment decisions in IMV care. We sent the survey instrument to 132 clinicians across six geographically diverse health systems. Among 51 respondents (39% response rate), there were 24 (47%) physicians, 7 (14%) registered nurses, 8 (16%) advanced practice providers, and 12 (24%) respiratory therapists. Participants were from five US states including Pennsylvania, California, Michigan, Minnesota, and Nebraska. At least 50% of participants identified 18 distinct treatment decisions for IMV care asvery importantorabsolutely essential, including many that were outside of the ventilator settings themselves. The highest agreement about importance was for the decision to extubate (N=51, 100%), and the decisions to conduct a spontaneous awakening trial (N=48, 94%) and spontaneous breathing trial (N=48, 94%). The highest agreement about a decision beingnot importantor onlyslightly importantwas for the shape of the inspiratory flow pattern (N=15, 29%). These findings underscore the scope and complexity of clinical decision making across multidisciplinary teams in caring for people receiving IMV. Furthermore, they underscore the gap between important clinician-identified decisions and existing IMV CDSSs that provide suggestions for at most 5 ventilator settings without support for other related decisions. Future work is needed to identify which of these decisions might be most appropriate for inclusion in a CDSS to support IMV management.

Publisher

Cold Spring Harbor Laboratory

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