Background: Computerized decision support systems (CDSSs) integrated into electronic health records are intended to support continuous use of evidence in clinical decision-making, tailored to individual patients. We aimed to update a previous systematic review on the effectiveness of CDSSs linked with patient-data via electronic health records (EHRs) published in 2014. Methods: We updated the searches on MEDLINE, Embase, and Cochrane Central Register of Controlled Trials databases from 2013 up to January 2023. We included randomized controlled trials (RCTs) that evaluated as intervention CDSSs featuring rule- or algorithm-based software integrated with EHRs and evidence-based knowledge compared with usual care, CDSSs without advice, or non-evidence-based CDSSs in any professional healthcare setting. Two independent reviewers extracted relevant data from the included RCTs and assessed the certainty of evidence using the Grading of Recommendations, Assessment, Development, and Evaluations approach. Meta-analyses with fixed- and random-effects models were performed for two primary outcomes: mortality and morbidity. Results: We included 47 RCTs, incorporating data from 29 new RCTs in this update. Compared with controls, CDSS use may result in little to no reduction in mortality (38 trials, 127,623 patients; fixed-effects model risk ratio [RR] = 0.98; 95 % confidence interval [CI] 0.93 to 1.02; I2 = 0 %; moderate certainty). The meta-analysis on morbidity reached nominal statistical significance: CDSS use may have trivial or small benefits with respect to morbidity (34 RCTs; 133,504 patients; fixed-effects model RR = 0.92, 95 % CI 0.90–0.97; random-effects model RR = 0.93, 95 % CI 0.87–0.99; I2 = 48 %; high certainty). Our meta-analysis did not highlight substantial effects on mortality while tiny reductions in morbidity are possible. In specific therapeutic areas, such as cardiovascular, a small effect may be present. Nevertheless, CDSSs could improve care processes and clinician behavior, potentially influencing long-term health outcome. Registration CRD42014007177.
Biffi, A., Castellini, G., Castillo, G., Nard, F., Vismara, C., Cabitza, F., et al. (2026). Effectiveness of computerized decision support systems linked to electronic health records: An updated systematic review with meta-analysis. INTERNATIONAL JOURNAL OF MEDICAL INFORMATICS, 207(1 March 2026) [10.1016/j.ijmedinf.2025.106220].
Effectiveness of computerized decision support systems linked to electronic health records: An updated systematic review with meta-analysis
Cabitza F.;Corrao G.;
2026
Abstract
Background: Computerized decision support systems (CDSSs) integrated into electronic health records are intended to support continuous use of evidence in clinical decision-making, tailored to individual patients. We aimed to update a previous systematic review on the effectiveness of CDSSs linked with patient-data via electronic health records (EHRs) published in 2014. Methods: We updated the searches on MEDLINE, Embase, and Cochrane Central Register of Controlled Trials databases from 2013 up to January 2023. We included randomized controlled trials (RCTs) that evaluated as intervention CDSSs featuring rule- or algorithm-based software integrated with EHRs and evidence-based knowledge compared with usual care, CDSSs without advice, or non-evidence-based CDSSs in any professional healthcare setting. Two independent reviewers extracted relevant data from the included RCTs and assessed the certainty of evidence using the Grading of Recommendations, Assessment, Development, and Evaluations approach. Meta-analyses with fixed- and random-effects models were performed for two primary outcomes: mortality and morbidity. Results: We included 47 RCTs, incorporating data from 29 new RCTs in this update. Compared with controls, CDSS use may result in little to no reduction in mortality (38 trials, 127,623 patients; fixed-effects model risk ratio [RR] = 0.98; 95 % confidence interval [CI] 0.93 to 1.02; I2 = 0 %; moderate certainty). The meta-analysis on morbidity reached nominal statistical significance: CDSS use may have trivial or small benefits with respect to morbidity (34 RCTs; 133,504 patients; fixed-effects model RR = 0.92, 95 % CI 0.90–0.97; random-effects model RR = 0.93, 95 % CI 0.87–0.99; I2 = 48 %; high certainty). Our meta-analysis did not highlight substantial effects on mortality while tiny reductions in morbidity are possible. In specific therapeutic areas, such as cardiovascular, a small effect may be present. Nevertheless, CDSSs could improve care processes and clinician behavior, potentially influencing long-term health outcome. Registration CRD42014007177.| File | Dimensione | Formato | |
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