Can computerized risk profiles help patients improve their coronary risk? The results of the Coronary Health Assessment Study (CHAS)

Prev Med. Sep-Oct 1998;27(5 Pt 1):730-7. doi: 10.1006/pmed.1998.0351.

Abstract

Background: The Coronary Health Assessment Study (CHAS) was developed to determine the feasibility of using patient-specific, multifactorial computerized coronary risk profiles as a clinical decision aid to support primary prevention of CHD.

Methods: Study participants included 253 community based physicians, randomized into profile and control groups, and 958 of their patients. The profile group physicians received coronary risk profiles for their patients within 10 working days after the baseline patient assessment providing early feedback. The control group received their profiles only if the patient was clinically reevaluated during a 3-month follow-up visit. Patients' coronary risk factors were evaluated at baseline and at follow-up.

Results: The profile group had a significantly higher (P < 0.05) ratio of high-risk/low-risk patients who returned for a follow-up visit compared to the control group (1.23 vs 0.77). The patients in the profile group also had significantly (P < 0.05) greater mean reductions in total cholesterol (-0.5 vs -0.1 mmol/L), LDL cholesterol (-0.4 vs 0.0 mmol/L), the total cholesterol/ HDL ratio (-0.6 vs -0.2), and the predicted 8-year coronary risk (-1.8 vs -0.3%).

Conclusions: Computer-generated coronary risk profiles can be effective in assisting physicians to identify high-risk patients. Their use is also associated with significantly greater improvements in the serum lipid profiles and the overall coronary risk of these patients.

Publication types

  • Clinical Trial
  • Randomized Controlled Trial
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Coronary Disease / etiology
  • Coronary Disease / prevention & control*
  • Decision Making, Computer-Assisted*
  • Decision Support Techniques*
  • Family Practice / education
  • Family Practice / methods*
  • Feasibility Studies
  • Female
  • Health Status Indicators*
  • Humans
  • Likelihood Functions
  • Male
  • Middle Aged
  • Primary Prevention / methods*
  • Risk Factors