Sustained Effect of Clinical Decision Support for Heart Failure: A Natural Experiment Using Implementation Science

Appl Clin Inform. 2023 Oct;14(5):822-832. doi: 10.1055/s-0043-1775566. Epub 2023 Oct 18.

Abstract

Objectives: In a randomized controlled trial, we found that applying implementation science (IS) methods and best practices in clinical decision support (CDS) design to create a locally customized, "enhanced" CDS significantly improved evidence-based prescribing of β blockers (BB) for heart failure compared with an unmodified commercially available CDS. At trial conclusion, the enhanced CDS was expanded to all sites. The purpose of this study was to evaluate the real-world sustained effect of the enhanced CDS compared with the commercial CDS.

Methods: In this natural experiment of 28 primary care clinics, we compared clinics exposed to the commercial CDS (preperiod) to clinics exposed to the enhanced CDS (both periods). The primary effectiveness outcome was the proportion of alerts resulting in a BB prescription. Secondary outcomes included patient reach and clinician adoption (dismissals).

Results: There were 367 alerts for 183 unique patients and 171 unique clinicians (pre: March 2019-August 2019; post: October 2019-March 2020). The enhanced CDS increased prescribing by 26.1% compared with the commercial (95% confidence interval [CI]: 17.0-35.1%), which is consistent with the 24% increase in the previous study. The odds of adopting the enhanced CDS was 81% compared with 29% with the commercial (odds ratio: 4.17, 95% CI: 1.96-8.85). The enhanced CDS adoption and effectiveness rates were 62 and 14% in the preperiod and 92 and 10% in the postperiod.

Conclusion: Applying IS methods with CDS best practices was associated with improved and sustained clinician adoption and effectiveness compared with a commercially available CDS tool.

Publication types

  • Multicenter Study
  • Research Support, N.I.H., Extramural

MeSH terms

  • Decision Support Systems, Clinical*
  • Heart Failure* / drug therapy
  • Humans
  • Implementation Science