Implementation of a Clinical Decision Support Tool to Improve Cardiac Rehabilitation Referral

J Cardiopulm Rehabil Prev. 2025 Jan 1;45(1):29-36. doi: 10.1097/HCR.0000000000000902. Epub 2024 Nov 26.

Abstract

Purpose: Inadequate referral to cardiac rehabilitation (CR) is a major barrier to CR participation. We investigated the implementation of a clinical decision support (CDS) tool on improving CR referral for patients hospitalized with acute myocardial infarction (AMI) at an academic medical center.

Methods: We developed a CDS tool that identified patients admitted with AMI and reminded physicians to refer patients to CR. We used multivariable-adjusted logistic regression to evaluate predictors of CR referral prior to the CDS tool. We then conducted an interrupted time series (ITS) analysis on CR referral rates before and after intervention.

Results: A total of 1985 patients admitted with acute MI from December 2014 through March 2023 were included. Prior to CDS implementation, 1218 of 1657 patients (74%) were referred to CR. Multivariable-adjusted logistic regression demonstrated that ST-segment elevation myocardial infarction on arrival (OR = 1.70: 95% CI, 1.29-2.23, P < .001) and percutaneous coronary intervention during the hospitalization (OR = 2.25: 95% CI, 1.60-3.15, P < .001) were associated with a higher odds of CR referral. After implementation of the CDS tool, 308 of 328 patients (94%) received CR referrals. An ITS analysis demonstrated that the increase in CR referral from 74-94% after the CDS tool was highly significant (P < .01).

Conclusions: The implementation of a CDS tool reminding physicians to refer patients with AMI to CR markedly improved CR referral rates at our institution. These findings are important for institutions seeking to improve outcomes in patients with AMI.

MeSH terms

  • Aged
  • Cardiac Rehabilitation* / methods
  • Decision Support Systems, Clinical*
  • Female
  • Humans
  • Interrupted Time Series Analysis
  • Male
  • Middle Aged
  • Myocardial Infarction / rehabilitation
  • Referral and Consultation* / statistics & numerical data