The use of cardiovascular risk factor information in practice databases: making the best of patient data.
BACKGROUND
Primary care teams record cardiovascular risk factor data on their patients to help them identify and treat patients eligible for prevention. However, it is not known to what extent this information is already available to clinicians, or the extent to which it is used.


OBJECTIVE
To assess the extent to which risk factor is recorded, and to determine the cost-effectiveness of using recorded risk factor information in order to identify and treat eligible patients.


METHODS
An Excel-based model of the incremental costs and benefits of assessment and treatment.


METHODS
Two general practices in the West Midlands.


METHODS
Untreated, non-diabetic patients, aged 35-74 years, were identified from each practice, and risk factor data was uploaded into an Excel spreadsheet. The completeness of risk factor data was assessed. The costs and benefits of assessing and treating patients, in descending order of estimated cardiovascular risk, were then modelled.


RESULTS
In each practice, 72.9% and 77.7% of patients had a record of their blood pressure, 26.9% and 25.7% were eligible for at least one treatment: aspirin was the most common treatment followed by antihypertensives. With patients systematically assessed in descending order of cardiovascular risk, 78% of eligible patients and 87% of preventable cardiovascular events are found in the first two deciles of the target population.


CONCLUSIONS
Lack of risk factor information is not the principal constraint on cardiovascular prevention. Practices have sufficient risk factor data to inform an efficient, targeted prevention strategy.
Marshall
Tom
T
Senior lecturer in public health, University of Birmingham, Birmingham, UK. T.P.Marshall@bham.ac.uk
D000328:Adult; D000368:Aged; D000959:Antihypertensive Agents / Q000191:economics / Q000627:therapeutic use; D001241:Aspirin / Q000191:economics / Q000627:therapeutic use; D001794:Blood Pressure; D002318:Cardiovascular Diseases / Q000191:economics / Q000517:prevention & control*; D003362:Cost-Benefit Analysis; D003625:Data Collection; D019992:Databases as Topic; D005194:Family Practice / Q000191:economics / Q000592:standards*; D006801:Humans; D008875:Middle Aged; D010865:Pilot Projects; D011322:Primary Prevention / Q000191:economics / Q000592:standards*; D012307:Risk Factors
D000959:Antihypertensive Agents; D001241:Aspirin