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Do providers use computerized clinical decision support systems? A systematic review and meta-regression of clinical decision support uptake.
Kouri, Andrew; Yamada, Janet; Lam Shin Cheung, Jeffrey; Van de Velde, Stijn; Gupta, Samir.
Affiliation
  • Kouri A; Division of Respirology, Department of Medicine, St. Michael's Hospital, Unity Health Toronto, 6 PGT, 30 Bond St, Toronto, ON, Canada.
  • Yamada J; Daphne Cockwell School of Nursing, Faculty of Community Services, Ryerson University, Toronto, ON, Canada.
  • Lam Shin Cheung J; Keenan Research Center, Li Ka Shing Knowledge Institute, St. Michael's Hospital, University of Toronto, Toronto, Ontario, Canada.
  • Van de Velde S; Division for Health Services, Norwegian Institute of Public Health, Oslo, Norway.
  • Gupta S; Division of Respirology, Department of Medicine, St. Michael's Hospital, Unity Health Toronto, 6 PGT, 30 Bond St, Toronto, ON, Canada. samir.gupta@unityhealth.to.
Implement Sci ; 17(1): 21, 2022 03 10.
Article in En | MEDLINE | ID: mdl-35272667
ABSTRACT

BACKGROUND:

Computerized clinical decision support systems (CDSSs) are a promising knowledge translation tool, but often fail to meaningfully influence the outcomes they target. Low CDSS provider uptake is a potential contributor to this problem but has not been systematically studied. The objective of this systematic review and meta-regression was to determine reported CDSS uptake and identify which CDSS features may influence uptake.

METHODS:

Medline, Embase, CINAHL, and the Cochrane Database of Controlled Trials were searched from January 2000 to August 2020. Randomized, non-randomized, and quasi-experimental trials reporting CDSS uptake in any patient population or setting were included. The main outcome extracted was CDSS uptake, reported as a raw proportion, and representing the number of times the CDSS was used or accessed over the total number of times it could have been interacted with. We also extracted context, content, system, and implementation features that might influence uptake, for each CDSS. Overall weighted uptake was calculated using random-effects meta-analysis and determinants of uptake were investigated using multivariable meta-regression.

RESULTS:

Among 7995 citations screened, 55 studies involving 373,608 patients and 3607 providers met full inclusion criteria. Meta-analysis revealed that overall CDSS uptake was 34.2% (95% CI 23.2 to 47.1%). Uptake was only reported in 12.4% of studies that otherwise met inclusion criteria. Multivariable meta-regression revealed the following factors significantly associated with uptake (1) formally evaluating the availability and quality of the patient data needed to inform CDSS advice; and (2) identifying and addressing other barriers to the behaviour change targeted by the CDSS. CONCLUSIONS AND RELEVANCE System uptake was seldom reported in CDSS trials. When reported, uptake was low. This represents a major and potentially modifiable barrier to overall CDSS effectiveness. We found that features relating to CDSS context and implementation strategy best predicted uptake. Future studies should measure the impact of addressing these features as part of the CDSS implementation strategy. Uptake reporting must also become standard in future studies reporting CDSS intervention effects. REGISTRATION Pre-registered on PROSPERO, CRD42018092337.
Subject(s)

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Decision Support Systems, Clinical Type of study: Clinical_trials / Prognostic_studies / Systematic_reviews Aspects: Implementation_research Limits: Humans Language: En Journal: Implement Sci Year: 2022 Document type: Article Affiliation country: Canada

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Decision Support Systems, Clinical Type of study: Clinical_trials / Prognostic_studies / Systematic_reviews Aspects: Implementation_research Limits: Humans Language: En Journal: Implement Sci Year: 2022 Document type: Article Affiliation country: Canada