Audit and feedback to change diagnostic image ordering practices: A systematic review and meta-analysis

Up to 30% of diagnostic imaging (DI) tests may be unnecessary, leading to increased healthcare costs and the possibility of patient harm. The primary objective of this systematic review was to assess the effect of audit and feedback (AF) interventions directed at healthcare providers on reducing image ordering. The secondary objective was to examine the effect of AF on the appropriateness of DI ordering.

Studies were identified using MEDLINE, EMBASE, CINAHL, Cochrane Central Register of Controlled Trials and ClinicalTrials.gov registry on December 22nd, 2022. Studies were included if they were randomized control trials (RCTs), targeted healthcare professionals, and studied AF as the sole intervention or as the core component of a multi-faceted intervention. Risk of bias for each study was evaluated using the Cochrane risk of bias tool. Meta-analyses were completed using RevMan software and results were displayed in forest plots.

Eleven RCTs enrolling 4311 clinicians or practices were included. AF interventions resulted in 1.5 fewer image test orders per 1000 patients seen than control interventions (95% confidence interval (CI) for the difference -2.6 to -0.4, p-value = 0.009). The effect of AF on appropriateness was not statistically significant, with a 3.2% (95% CI -1.5 to 7.7%, p-value = 0.18) greater likelihood of test orders being considered appropriate with AF vs control interventions. The strength of evidence was rated as moderate for the primary objective but was very low for the appropriateness outcome because of risk of bias, inconsistency in findings, indirectness, and imprecision.

AF interventions are associated with a modest reduction in total DI ordering with moderate certainty, suggesting some benefit of AF. Individual studies document effects of AF on image order appropriateness ranging from a non-significant trend toward worsening to a highly significant improvement, but the weighted average effect size from the meta-analysis is not statistically significant with very low certainty.