­The effects of clinical decision support system for prescribing medication on patient outcomes and physician practice performance: a systematic review and meta-analysis

Abstract

Background: The clinical decision support systems (CDSSs) for prescribing is one of the technologies aimed at improving physician practice performance and patient outcomes by reducing medication prescription errors. This study, thus, was conducted to investigate the effect of various CDSSs on physician practice performance and patient outcomes.Methods: This systematic review was conducted by searching in PubMed, EMBASE, Web of Science, Scopus, and Cochrane Library from 2005 to 2019. Two researchers independently evaluated the studies. Any discrepancies over the eligibility of the studies between the two researchers were then resolved by consulting a third researcher. Finally, we extracted data from the articles. Then, we conducted a meta-analysis based on medication subgroups, CDSS type subgroups, and outcome categories. Also, we presented a narrative form of the findings. In the meantime, we applied random-effects model to estimate the effects of CDSS on patient outcomes and physician practice performance with 95% confidence interval. Q statistics and I2 were then used to measure heterogeneity.Results: Based on the inclusion criteria, 45 studies were considered eligible for the analysis in this review. The CDSS for prescribing medications/COPE were used for various diseases such as cardiovascular diseases, hypertension, diabetes, gastrointestinal and respiratory diseases, AIDS, appendicitis, kidney disease, malaria, high blood potassium, and mental diseases. Meanwhile, other cases such as the concurrent prescription of multiple drugs for patients and its effects on the above-mentioned outcomes were evaluated. The analysis shows that in some cases the application of CDSS provides positive effects on patient outcomes and physician practice performance (std diff in means = 0.114, 95% CI: 0.090 to 0.138). Also, it was statistically significant for outcome groups such as those showing improved outcomes on physician practice performance and patient outcome or both. However, no significant difference was observed between some other cases and conventional methods. We think that this could be due to the disease type, the quantity, and the type of CDSS requirements that influenced the comparison. Overall, all types of CDSSs have positive effects on outcomes including combinational types and other types that only cause messages when appropriate and necessary.Conclusions: Our findings suggest that positive effects of the CDSS can be attributed to factors such as user-friendliness, compliance with clinical guidelines, patient and physician cooperation, integration of electronic health records, CDSS and pharmaceutical systems, consideration of the views of physicians in assessing the importance of CDSS alerts, and the real-time alerts in the prescription.