Medical Decision Support Systems: Old Dilemmas and new Paradigms?

Author:

Dufour J.-C.,Staccini P.,Gouvernet J.,Bouhaddou O.,Fieschi M.

Abstract

Summary Objectives: The purpose of this paper is to examine past and present medical decision support systems and the environment in which they operate and to propose specific research tracks that improve integration and adoption of these systems in today’s health care systems. Methods: In preamble, we examine the objectives, decision models, and performances of past decision support systems. Results: Medical decision support tools were essentially formulated from a technical capability perspective and this view has met limited adoption and slowed down new development as well as integration of these important systems into patient management work flows and clinical information systems. The science base of these systems needs to include evidence-based medicine and clinical practice guidelines and the paradigms need to be extended to include a collaborative provider model, the users and the organization perspectives. The availability of patient record and medical terminology standards is essential to the dissemination of decision support systems and so is their integration into the care process. Conclusion: To build new decision support systems based on practice guidelines and taking into account users preferences, we do not so much advocate new technological solutions but rather suggest that technology is not enough to ensure successful adoption by the users, the integration into practice workflow, and consequently, the realisation of improved health care outcomes.

Publisher

Georg Thieme Verlag KG

Subject

Health Information Management,Advanced and Specialized Nursing,Health Informatics

Cited by 34 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

1. New Real Time Clinical Decision System Using Machine Learning – Disease Prediction;2023 International Conference on Computer Communication and Informatics (ICCCI);2023-01-23

2. Artificial Intelligence for Medical Decisions;Artificial Intelligence in Medicine;2022

3. s2Cloud: A Novel Cloud System for Mobile Health Big Data Management;2021 IEEE International Conferences on Internet of Things (iThings) and IEEE Green Computing & Communications (GreenCom) and IEEE Cyber, Physical & Social Computing (CPSCom) and IEEE Smart Data (SmartData) and IEEE Congress on Cybermatics (Cybermatics);2021-12

4. Artificial Intelligence for Medical Decisions;Artificial Intelligence in Medicine;2021

5. Multi-layered deep learning perceptron approach for health risk prediction;Journal of Big Data;2020-07-23

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