The effect of electronic audits and feedback in primary care and factors that contribute to their effectiveness: a systematic review

Purpose: The aim of this systematic review was (i) to assess whether electronic audit and feedback (A&F) is effective in primary care and (ii) to evaluate important features concerning content and delivery of the feedback in primary care, including the use of benchmarks, the frequency of feedback, the cognitive load of feedback and the evidence-based aspects of the feedback. Data sources: The MEDLINE, Embase, CINAHL and CENTRAL databases were searched for articles published since 2010 by replicating the search strategy used in the last Cochrane review on A&F. Study selection: Two independent reviewers assessed the records for their eligibility, performed the data extraction and evaluated the risk of bias. Our search resulted in 8744 records, including the 140 randomized controlled trials (RCTs) from the last Cochrane Review. The full texts of 431 articles were assessed to determine their eligibility. Finally, 29 articles were included. Data extraction: Two independent reviewers extracted standard data, data on the effectiveness and outcomes of the interventions, data on the kind of electronic feedback (static versus interactive) and data on the aforementioned feedback features. Results of data synthesis: Twenty-two studies (76%) showed that electronic A&F was effective. All interventions targeting medication safety, preventive medicine, cholesterol management and depression showed an effect. Approximately 70% of the included studies used benchmarks and high-quality evidence in the content of the feedback. In almost half of the studies, the cognitive load of feedback was not reported. Due to high heterogeneity in the results, no meta-analysis was performed. Conclusion: This systematic review included 29 articles examining electronic A&F interventions in primary care, and 76% of the interventions were effective. Our findings suggest electronic A&F is effective in primary care for different conditions such as medication safety and preventive medicine. Some of the benefits of electronic A&F include its scalability and the potential to be cost effective. The use of benchmarks as comparators and feedback based on high-quality evidence are widely used and important features of electronic feedback in primary care. However, other important features such as the cognitive load of feedback and the frequency of feedback provision are poorly described in the design of many electronic A&F intervention, indicating that a better description or implementation of these features is needed. Developing a framework or methodology for automated A&F interventions in primary care could be useful for future research.