Effects of clinical decision-support systems on practitioner performance and patient outcomes: a synthesis of high-quality systematic review findings

• Published in: Journal of the American Medical Informatics Association : JAMIA Vol. 18; no. 3; pp. 327 - 334
• Main Authors: Jaspers, Monique W M, Smeulers, Marian, Vermeulen, Hester, Peute, Linda W
• Format: Journal Article
• Language: English
• Published: England BMJ Group 01.05.2011
• Subjects: Clinical Competence; Decision Support Systems, Clinical; Electronic Prescribing; Humans; Medical Order Entry Systems; Outcome Assessment (Health Care); Reminder Systems; Review; Therapy, Computer-Assisted
• ISSN: 1067-5027; 1527-974X
• DOI: 10.1136/amiajnl-2011-000094

To synthesize the literature on clinical decision-support systems' (CDSS) impact on healthcare practitioner performance and patient outcomes. Literature search on Medline, Embase, Inspec, Cinahl, Cochrane/Dare and analysis of high-quality systematic reviews (SRs) on CDSS in hospital settings. Two-stage inclusion procedure: (1) selection of publications on predefined inclusion criteria; (2) independent methodological assessment of preincluded SRs by the 11-item measurement tool, AMSTAR. Inclusion of SRs with AMSTAR score 9 or above. SRs were thereafter rated on level of evidence. Each stage was performed by two independent reviewers. 17 out of 35 preincluded SRs were of high methodological quality and further analyzed. Evidence that CDSS significantly impacted practitioner performance was found in 52 out of 91 unique studies of the 16 SRs examining this effect (57%). Only 25 out of 82 unique studies of the 16 SRs reported evidence that CDSS positively impacted patient outcomes (30%). Few studies have found any benefits on patient outcomes, though many of these have been too small in sample size or too short in time to reveal clinically important effects. There is significant evidence that CDSS can positively impact healthcare providers' performance with drug ordering and preventive care reminder systems as most clear examples. These outcomes may be explained by the fact that these types of CDSS require a minimum of patient data that are largely available before the advice is (to be) generated: at the time clinicians make the decisions.