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 Clinical Decision Support Systems (CDSSs) for Prescribing are one of the innovations designed to improve physician practice performance and patient outcomes by reducing prescription errors. This study was therefore conducted to examine the effects of various CDSSs on physician practice performance and patient outcomes. Methods This systematic review was carried out by searching PubMed, Embase, Web of Science, Scopus, and Cochrane Library from 2005 to 2019. The studies were independently reviewed by two researchers. Any discrepancies in the eligibility of the studies between the two researchers were then resolved by consulting the third researcher. In the next step, we performed a meta-analysis based on medication subgroups, CDSS-type subgroups, and outcome categories. Also, we provided the narrative style of the findings. In the meantime, we used a random-effects model to estimate the effects of CDSS on patient outcomes and physician practice performance with a 95% confidence interval. Q statistics and I2 were then used to calculate heterogeneity. Results On the basis of the inclusion criteria, 45 studies were qualified for analysis in this study. CDSS for prescription drugs/COPE has been 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. In the meantime, other cases such as concurrent prescribing of multiple medications for patients and their effects on the above-mentioned results have been analyzed. The study shows that in some cases the use of CDSS has beneficial effects on patient outcomes and physician practice performance (std diff in means = 0.084, 95% CI 0.067 to 0.102). It was also statistically significant for outcome categories such as those demonstrating better results for physician practice performance and patient outcomes or both. However, there was no significant difference between some other cases and traditional approaches. We assume that this may be due to the disease type, the quantity, and the type of CDSS criteria that affected the comparison. Overall, the results of this study show positive effects on performance for all forms of CDSSs. Conclusions Our results indicate that the positive effects of the CDSS can be due 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.

Perceived Facilitators of and Barriers to Implementation of a Decision Support Tool for Adolescent Depression and Suicidality Screening: Focus Group and Interview Study

“…Although the treatment decision algorithm was a major component of the initial SW tool, we concluded that the providers’, adolescents’, and parents’ discomfort with this portion of the report may preclude future implementation. Nonetheless, measurement-based care may improve depression outcomes [ 61 ] and is facilitated by computerized decision support, which may enhance compliance with clinical guidelines [ 62 ] and result in small to moderate improvements in quality of care [ 63 ]. Future iterations of SW will, instead of providing specific treatment recommendations (eg, refer for substance use treatment or follow-up in 6 weeks), gather and display information in a user-friendly way to the provider while highlighting the severity score of symptoms and discrepancies between adolescents and parents and providing reference to the current clinical guidelines to enhance clinical decision-making without being overly prescriptive.…”

Assessment of Prescriptions in Elderly Patients Hospitalized in Medicine Departments

“…Combining this with the development of clinical pharmaceutical activities, through visits by the pharmacist to the patients in their rooms, can also promote the re-evaluation of prescriptions, increase the acceptance of pharmaceutical interventions, and thus lead to better-adapted prescriptions for the elderly. However, the use of a computerized clinical decision support system could help us increase efficiency and relevance [34]. These new tools are currently being studied to be adapted to our practice.…”

Historia clínica y receta electrónica: riesgos y beneficios detectados desde su implantación. Diseño, despliegue y usos seguros

“…Un metaanálisis que evaluó la efectividad de la PE para reducir errores de medicación y eventos adversos de los medicamentos en el ámbito hospitalario encontró una reducción significativa de los errores de medicación y las reacciones adversas a los medicamentos 18 . En AP los estudios realizados han mostrado resultados comparables en la reducción de los errores de medicación 19 , 20 .…”