Literature DB >> 29036296

Unintended adverse consequences of a clinical decision support system: two cases.

Erin G Stone1.   

Abstract

Many institutions have implemented clinical decision support systems (CDSSs). While CDSS research papers have focused on benefits of these systems, there is a smaller body of literature showing that CDSSs may also produce unintended adverse consequences (UACs). Detailed here are 2 cases of UACs resulting from a CDSS. Both of these cases were related to external systems that fed data into the CDSS. In the first case, lack of knowledge of data categorization in an external pharmacy system produced a UAC; in the second case, the change of a clinical laboratory instrument produced the UAC. CDSSs rely on data from many external systems. These systems are dynamic and may have changes in hardware, software, vendors, or processes. Such changes can affect the accuracy of CDSSs. These cases point to the need for the CDSS team to be familiar with these external systems. This team (manager and alert builders) should include members in specific clinical specialties with deep knowledge of these external systems.

Mesh:

Year:  2018        PMID: 29036296     DOI: 10.1093/jamia/ocx096

Source DB:  PubMed          Journal:  J Am Med Inform Assoc        ISSN: 1067-5027            Impact factor:   4.497


  7 in total

1.  Importance of clinical decision support system response time monitoring: a case report.

Authors:  David Rubins; Adam Wright; Tarik Alkasab; M Stephen Ledbetter; Amy Miller; Rajesh Patel; Nancy Wei; Gianna Zuccotti; Adam Landman
Journal:  J Am Med Inform Assoc       Date:  2019-11-01       Impact factor: 4.497

2.  What do senior physicians think about AI and clinical decision support systems: Quantitative and qualitative analysis of data from specialty societies.

Authors:  Haroldas Petkus; Jan Hoogewerf; Jeremy C Wyatt
Journal:  Clin Med (Lond)       Date:  2020-05       Impact factor: 2.659

3.  Consequences of Rapid Telehealth Expansion in Nursing Homes: Promise and Pitfalls.

Authors:  Kimberly R Powell; Gregory L Alexander
Journal:  Appl Clin Inform       Date:  2021-10-06       Impact factor: 2.762

4.  Algorithmic Detection of Boolean Logic Errors in Clinical Decision Support Statements.

Authors:  Adam Wright; Skye Aaron; Allison B McCoy; Robert El-Kareh; Daniel Fort; Steven Z Kassakian; Christopher A Longhurst; Sameer Malhotra; Dustin S McEvoy; Craig B Monsen; Richard Schreiber; Asli O Weitkamp; DuWayne L Willett; Dean F Sittig
Journal:  Appl Clin Inform       Date:  2021-03-10       Impact factor: 2.342

5.  Smashing the strict hierarchy: three cases of clinical decision support malfunctions involving carvedilol.

Authors:  Adam Wright; Aileen P Wright; Skye Aaron; Dean F Sittig
Journal:  J Am Med Inform Assoc       Date:  2018-11-01       Impact factor: 4.497

6.  Design, effectiveness, and economic outcomes of contemporary chronic disease clinical decision support systems: a systematic review and meta-analysis.

Authors:  Winnie Chen; Kirsten Howard; Gillian Gorham; Claire Maree O'Bryan; Patrick Coffey; Bhavya Balasubramanya; Asanga Abeyaratne; Alan Cass
Journal:  J Am Med Inform Assoc       Date:  2022-09-12       Impact factor: 7.942

7.  User-centred design for machine learning in health care: a case study from care management.

Authors:  Martin G Seneviratne; Ron C Li; Meredith Schreier; Daniel Lopez-Martinez; Birju S Patel; Alex Yakubovich; Jonas B Kemp; Eric Loreaux; Paul Gamble; Kristel El-Khoury; Laura Vardoulakis; Doris Wong; Janjri Desai; Jonathan H Chen; Keith E Morse; N Lance Downing; Lutz T Finger; Ming-Jun Chen; Nigam Shah
Journal:  BMJ Health Care Inform       Date:  2022-10
  7 in total

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