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A Novel Digital Platform for a Monitored Home-based Cardiac Rehabilitation Program
04:24

A Novel Digital Platform for a Monitored Home-based Cardiac Rehabilitation Program

Published on: April 19, 2019

Automatic referral to cardiac rehabilitation

Sherry L Grace1, Alexandra Evindar, Tabitha N Kung

  • 1University Health Network Women's Health Program, Toronto, Ontario, Canada. sherry.grace@uhn.on.ca

Medical Care
|June 24, 2004
PubMed

Insights

Cardiac rehabilitation (CR) enrollment is predicted by fewer barriers and perceived need, not patient demographics, when using automatic referrals. This highlights the importance of addressing logistical challenges and patient perceptions for better access to cardiac care.

Area of Science:

  • Cardiology
  • Health Services Research
  • Behavioral Science

Background:

  • Cardiac rehabilitation (CR) is underutilized, especially among women and minorities.
  • Automatic referral systems aim to improve CR access.
  • The Behavioral Model of Health Services Utilization provides a framework for understanding healthcare access.

Purpose of the Study:

  • To examine factors influencing CR enrollment within an automatic referral system.
  • To test the hypothesis that enabling and perceived need factors predict enrollment, while predisposing factors do not.

Main Methods:

  • Retrospective chart review and survey of atherosclerotic heart disease (AHD) patients (n=501) at a tertiary care center.
  • Survey assessed sociodemographics, CR barriers/facilitators, exercise beliefs, social support, and illness perceptions.
  • Statistical analysis to identify predictors of CR enrollment.

Main Results:

  • 73.2% of referred patients (n=272) attended a CR assessment.
  • Lower denial/minimization, fewer logistical barriers (distance, cost), and lower perceptions of AHD as episodic predicted CR enrollment.
  • Predisposing factors (sociodemographics) were not significant predictors.

Conclusions:

  • Enabling factors and perceived need significantly predict CR enrollment in an automatic referral model.
  • Predisposing factors do not appear to influence enrollment within this system.
  • Further prospective studies evaluating automatic referral for CR are recommended.
Abstract

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