Clinical decision support systems’ effect in reducing medication errors and adverse drug events: an expanded review from Making Healthcare Safer IV

Clinical decision support systems (CDSSs) are used to provide alerts and recommendations on prescribing and order verification with the intent of reducing the frequency and harm of medication errors (MEs) and adverse drug events (ADEs). This review assessed recent evidence on the effects of CDSSs on reducing MEs and ADEs. Related implementation outcomes such as alert overrides and unintended consequences of use were also assessed, and literature around the effective implementation of CDSSs was summarised. The review followed processes proposed by the Agency for Healthcare Research and Quality Evidence-based Practice Center Programme. PubMed and the Cochrane Library were searched from 2015 to 2023. Results were narratively synthesised, and overall certainty of evidence was assessed for outcomes of interest. The search yielded 1335 unique abstracts, of which 34 articles met the criteria for inclusion. The type of clinical decision support and outcomes were heterogeneous between studies. Overall, computerised provider order entry with medication-related clinical decision support functions was associated with reduced MEs ( moderate certainty of evidence) and prevention of ADEs ( low certainty of evidence). Improved or targeted medication-related CDSSs were associated with reductions of MEs and ADEs ( moderate certainty of evidence). However, alert override rates were high and varied between studies, and the appropriateness of the overrides was largely influenced by the type of alert. Other unintended consequences included CDSS-related errors, overdependence on alerts, alert fatigue, inappropriate alert overrides and provider burnout. An additional seven systematic reviews focused on barriers and facilitators of CDSS implementation. CDSSs reduce MEs and ADEs, with moderate -certainty and low -certainty evidence, respectively. However, there are several unintended consequences of CDSS use. PROSPERO registration number: CRD42023449710.

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Publication Details

Journal
BMJ Digital Health & AI
Published
2025-09-01
DOI
https://doi.org/10.1136/bmjdhai-2025-000083
Primary Topic
Electronic Health Records Systems
Type
article
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article

Clinical decision support systems’ effect in reducing medication errors and adverse drug events: an expanded review from Making Healthcare Safer IV

Emily Lawson, Ania Syrowatka, Aneesa Motala, Paul G Shekelle
BMJ Digital Health & AI
Electronic Health Records Systems
article

Clinical decision support systems’ effect in reducing medication errors and adverse drug events: an expanded review from Making Healthcare Safer IV

Emily Lawson, Ania Syrowatka, Aneesa Motala, Paul G Shekelle
article en

Abstract

Clinical decision support systems (CDSSs) are used to provide alerts and recommendations on prescribing and order verification with the intent of reducing the frequency and harm of medication errors (MEs) and adverse drug events (ADEs). This review assessed recent evidence on the effects of CDSSs on reducing MEs and ADEs. Related implementation outcomes such as alert overrides and unintended consequences of use were also assessed, and literature around the effective implementation of CDSSs was summarised. The review followed processes proposed by the Agency for Healthcare Research and Quality Evidence-based Practice Center Programme. PubMed and the Cochrane Library were searched from 2015 to 2023. Results were narratively synthesised, and overall certainty of evidence was assessed for outcomes of interest. The search yielded 1335 unique abstracts, of which 34 articles met the criteria for inclusion. The type of clinical decision support and outcomes were heterogeneous between studies. Overall, computerised provider order entry with medication-related clinical decision support functions was associated with reduced MEs ( moderate certainty of evidence) and prevention of ADEs ( low certainty of evidence). Improved or targeted medication-related CDSSs were associated with reductions of MEs and ADEs ( moderate certainty of evidence). However, alert override rates were high and varied between studies, and the appropriateness of the overrides was largely influenced by the type of alert. Other unintended consequences included CDSS-related errors, overdependence on alerts, alert fatigue, inappropriate alert overrides and provider burnout. An additional seven systematic reviews focused on barriers and facilitators of CDSS implementation. CDSSs reduce MEs and ADEs, with moderate -certainty and low -certainty evidence, respectively. However, there are several unintended consequences of CDSS use. PROSPERO registration number: CRD42023449710.

BMJ Digital Health & AIVol. 1(1)
University of Southern California (US), Brigham and Women's Hospital (US), RAND Corporation (US), Harvard University (US)
Openalex Percentile: Top 73%
Electronic Health Records Systems
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