Automatic referral to cardiac rehabilitation

Med Care. 2004 Jul;42(7):661-9. doi: 10.1097/01.mlr.0000129901.05299.aa.


Objectives: Cardiac rehabilitation (CR) remains underused and inconsistently accessed, particularly for women and minorities. This study examined the factors associated with CR enrollment within the context of an automatic referral system through a retrospective chart review plus survey. Through the Behavioral Model of Health Services Utilization, it was postulated that enabling and perceived need factors, but not predisposing factors, would significantly predict patient enrollment.

Subjects: A random sample of all atherosclerotic heart disease (AHD) patients treated at a tertiary care center (Trillium Health Centre, Ontario, Canada) from April 2001 to May 2002 (n = 501) were mailed a survey using a modified Dillman method (71% response rate).

Measures: Predisposing measures consisted of sociodemographics such as age, sex, ethnocultural background, work status, level of education, and income. Enabling factors consisted of barriers and facilitators to CR attendance, exercise benefits and barriers (EBBS), and social support (MOS). Perceived need factors consisted of illness perceptions (IPQ) and body mass index.

Results: Of the 272 participants, 199 (73.2%) attended a CR assessment. Lower denial/minimization, fewer logistical barriers to CR (eg, distance, cost), and lower perceptions of AHD as cyclical or episodic reliably predicted CR enrollment among cardiac patients who were automatically referred.

Conclusion: Because none of the predisposing factors were significant in the final model, this suggests that factors associated with CR enrollment within the context of an automatic referral model relate to enabling factors and perceived need. A prospective controlled evaluation of automatic referral is warranted.

Publication types

  • Comparative Study
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Aged
  • Arteriosclerosis / rehabilitation*
  • Causality
  • Cross-Sectional Studies
  • Factor Analysis, Statistical
  • Female
  • Humans
  • Logistic Models
  • Male
  • Middle Aged
  • Models, Psychological
  • Ontario
  • Patient Acceptance of Health Care* / psychology
  • Referral and Consultation*
  • Socioeconomic Factors