Barriers to using clinical decision support in ambulatory care: Do clinics in health systems fare better?
- PMID: 33895828
- PMCID: PMC8324224
- DOI: 10.1093/jamia/ocab064
Barriers to using clinical decision support in ambulatory care: Do clinics in health systems fare better?
Abstract
Objective: We quantify the use of clinical decision support (CDS) and the specific barriers reported by ambulatory clinics and examine whether CDS utilization and barriers differed based on clinics' affiliation with health systems, providing a benchmark for future empirical research and policies related to this topic.
Materials and methods: Despite much discussion at the theoretic level, the existing literature provides little empirical understanding of barriers to using CDS in ambulatory care. We analyze data from 821 clinics in 117 medical groups, based on in Minnesota Community Measurement's annual Health Information Technology Survey (2014-2016). We examine clinics' use of 7 CDS tools, along with 7 barriers in 3 areas (resource, user acceptance, and technology). Employing linear probability models, we examine factors associated with CDS barriers.
Results: Clinics in health systems used more CDS tools than did clinics not in systems (24 percentage points higher in automated reminders), but they also reported more barriers related to resources and user acceptance (26 percentage points higher in barriers to implementation and 33 points higher in disruptive alarms). Barriers related to workflow redesign increased in clinics affiliated with health systems (33 points higher). Rural clinics were more likely to report barriers to training.
Conclusions: CDS barriers related to resources and user acceptance remained substantial. Health systems, while being effective in promoting CDS tools, may need to provide further assistance to their affiliated ambulatory clinics to overcome barriers, especially the requirement to redesign workflow. Rural clinics may need more resources for training.
Keywords: adoption barriers; ambulatory care; clinical decision support; health systems; user acceptance.
© The Author(s) 2021. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For permissions, please email: journals.permissions@oup.com.
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