Can computerized risk profiles help patients improve their coronary risk? The results of the Coronary Health Assessment Study (CHAS).
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.
Lowensteyn
I
I
Centre for the Analysis of Cost-Effective Care and the Divisions of General Internal Medicine and Clinical Epidemiology, The Montreal General Hospital, Quebec, Vanada, H3G 1A4.
Joseph
L
L
Levinton
C
C
Abrahamowicz
M
M
Steinert
Y
Y
Grover
S
S
D000328:Adult; D003327:Coronary Disease / Q000209:etiology / Q000517:prevention & control*; D003658:Decision Making, Computer-Assisted; D003661:Decision Support Techniques; D005194:Family Practice / Q000193:education / Q000379:methods*; D005240:Feasibility Studies; D005260:Female; D006305:Health Status Indicators; D006801:Humans; D016013:Likelihood Functions; D008297:Male; D008875:Middle Aged; D011322:Primary Prevention / Q000379:methods*; D012307:Risk Factors