Can Electronic Clinical Decision Support Systems Improve the Diagnosis of Urinary Tract Infections? : A Systematic Review and Meta-Analysis


 
 
 Urinary tract infection (UTI) is a commonly misdiagnosed infectious syndrome. Diagnostic stewardship interventions can reduce rates of asymptomatic bacteriuria treatment but are often labor intensive, and thus an automated means of reducing unnecessary urine testing is preferred. In this systematic review and meta-analysis, we sought to identify studies describing interventions utilizing clinical decision support (CDS) to optimize UTI diagnosis and to characterize the effectiveness of these interventions.
 
 
 
 We conducted a comprehensive electronic search and manual reference list review for peer-reviewed articles published before July 2, 2021. Publications describing an intervention intending to enhance UTI diagnosis via CDS were included. The primary outcome was urine culture test rate.
 
 
 
 The electronic search identified 5,013 studies for screening. After screening and full-text review, 9 studies met criteria for inclusion, and manual reference list review identified 5 additional studies, yielding a total of 14 studies included in the systematic review. The most common CDS intervention was urinalysis with reflex to urine culture based on pre-specified urinalysis parameters. All 9 studies which provided statistical comparisons reported a decreased urine culture rate post-intervention, 8 of which were statistically significant. A meta-analysis including 4 studies identified a pooled urine culture incidence rate ratio of 0.56 (95% CI 0.52, 0.60) favoring the post-intervention versus pre-intervention group.
 
 
 
 In this systematic review and meta-analysis, CDS appeared to be effective in decreasing urine culture rates. Prospective trials are needed to confirm these findings and to evaluate their impact on antimicrobial prescribing, patient-relevant outcomes, and potential adverse effects.
