Effectiveness of clinical dashboards as audit and feedback or clinical decision support tools on medication use and test ordering: a systematic review of randomized controlled trials

Abstract

Background: Clinical dashboards used as audit and feedback (A&F) or clinical decision support systems (CDSS) are increasingly adopted in healthcare. However, their effectiveness in changing the behavior of clinicians or patients is still unclear. This systematic review aims to investigate the effectiveness of clinical dashboards used as CDSS or A&F tools (as a standalone intervention or part of a multifaceted intervention) in primary care or hospital settings on medication prescription/adherence and test ordering.

Methods: Seven major databases were searched for relevant studies, from inception to August 2021. Two authors independently extracted data, assessed the risk of bias using the Cochrane RoB II scale, and evaluated the certainty of evidence using GRADE. Data on trial characteristics and intervention effect sizes were extracted. A narrative synthesis was performed to summarize the findings of the included trials.

Results: Eleven randomized trials were included. Eight trials evaluated clinical dashboards as standalone interventions and provided conflicting evidence on changes in antibiotic prescribing and no effects on statin prescribing compared to usual care. Dashboards increased medication adherence in patients with inflammatory arthritis but not in kidney transplant recipients. Three trials investigated dashboards as part of multicomponent interventions revealing decreased use of opioids for low back pain, increased proportion of patients receiving cardiovascular risk screening, and reduced antibiotic prescribing for upper respiratory tract infections.

Conclusion: There is limited evidence that dashboards integrated into electronic medical record systems and used as feedback or decision support tools may be associated with improvements in medication use and test ordering.

Keywords: audit and feedback; clinical decision support; dashboard; review.

Figure 1.

PRISMA flow diagram. The PRIMSA flow diagram presents the systematic search and selection process in this review, detailing the number of records included and excluded at different stages and showing the final number of included studies.

Figure 2.

The risk of bias for individual trials. D1: Bias arising from the randomization process. D1a (for cluster-randomized designs): Bias arising from the randomization process. D1b (for cluster-randomized designs): Bias arising from the timing of identification or recruitment of participants. D2: Bias due to deviations from intended intervention. D3: Bias due to missing outcome data. D4: Bias in measurement of the outcome. D5: Bias in selection of the reported result. (X) high risk of bias; (−) some concerns; (+) low risk of bias.