COVID-19 Diagnostic Clinical Decision Support: a Pre-Post Implementation Study of CORAL (COvid Risk cALculator)

Clin Infect Dis. 2021 Feb 10;ciab111. doi: 10.1093/cid/ciab111. Online ahead of print.

Abstract

Background: Isolation of hospitalized persons under investigation (PUIs) for COVID-19 reduces nosocomial transmission risk. Efficient PUI evaluation is needed to preserve scarce healthcare resources. We describe the development, implementation, and outcomes of an inpatient diagnostic algorithm and clinical decision support system (CDSS) to evaluate PUIs.

Methods: We conducted a pre-post study of CORAL (COvid Risk cALculator), a CDSS that guides frontline clinicians through a risk-stratified COVID-19 diagnostic workup, removes transmission-based precautions when workup is complete and negative, and triages complex cases to Infectious Diseases (ID) physician review. Pre-CORAL, ID physicians reviewed all PUI records to guide workup and precautions. Post-CORAL, frontline clinicians evaluated PUIs directly using CORAL. We compared pre- and post-CORAL frequency of repeat SARS-CoV-2 nucleic acid amplification tests (NAATs), time from NAAT result to PUI status discontinuation, total duration of PUI status, and ID physician work-hours, using linear and logistic regression, adjusted for COVID-19 incidence.

Results: Fewer PUIs underwent repeat testing after an initial negative NAAT post-CORAL than pre-CORAL (54% vs. 67%; aOR 0.53, 95% CI: 0.44-0.63, p<0.01). CORAL significantly reduced average time to PUI status discontinuation (adjusted difference: -7.4 [SE 0.8] hours/patient; p<0.01), total duration of PUI status (adjusted difference: -19.5 [SE 1.9] hours/patient; p<0.01), and average ID physician work-hours (adjusted difference: -57.4 [SE 2.0] hours/day; p<0.01). No patients had a positive NAAT within 7 days after discontinuation of precautions via CORAL.

Conclusions: CORAL is an efficient and effective CDSS to guide frontline clinicians through the diagnostic evaluation of PUIs and safe discontinuation of precautions.

Keywords: COVID-19 diagnosis; clinical decision support system; diagnostic algorithm; electronic health record.