Impact of nonintrusive clinical decision support systems on laboratory test utilization in a large academic centre

J Eval Clin Pract. 2018 Jun;24(3):474-479. doi: 10.1111/jep.12890. Epub 2018 Feb 15.

Abstract

Background: The near-universal prevalence of electronic health records (EHRs) has made the utilization of clinical decision support systems (CDSS) an integral strategy for improving the value of laboratory ordering. Few studies have examined the effectiveness of nonintrusive CDSS on inpatient laboratory utilization in large academic centres.

Methods: Red blood cell folate, hepatitis C virus viral loads and genotypes, and type and screens were selected for study. We incorporated the appropriate indications for these labs into text that accompanied the laboratory orders in our hospital's EHR. Providers could proceed with the order without additional clicks. An interrupted time-series analysis was performed, and the primary outcome was the rate of tests ordered on all inpatient medicine floors.

Results: The rate of folate tests ordered per monthly admissions showed no significant level change at the time of the intervention with only a slight decrease in rate of 0.0109 (P = .07). There was a 43% decrease in the rate of hepatitis C virus tests per monthly admissions immediately after the intervention with a decrease of 0.0135 tests per monthly admissions (P = .02). The rate of type and screens orders per patient days each month had a significant downward trend by 0.114 before the intervention (P = .04) but no significant level change at the time of the intervention or significant change in rate after the intervention.

Discussion: Our study suggests that nonintrusive CDSS should be evaluated for individual laboratory tests to ensure only effective alerts continue to be used so as to avoid increasing EHR fatigue.

Keywords: computer-decision support tools; high-value care; laboratory testing.

MeSH terms

  • Academic Medical Centers*
  • Adolescent
  • Adult
  • Aged
  • Aged, 80 and over
  • Decision Support Systems, Clinical*
  • Diagnostic Tests, Routine / statistics & numerical data*
  • Electronic Health Records
  • Female
  • Humans
  • Male
  • Medical Order Entry Systems
  • Middle Aged
  • Practice Patterns, Physicians'
  • Young Adult