Identification of patients for clinical risk assessment by prediction of cardiovascular risk using default risk factor values

2008

Identifying High-Risk Patients for Cardiovascular Assessment

Sample size: 4834 publication 10 minutes Evidence: high

Author Information

Author(s): Tom Marshall

Primary Institution: Department of Public Health & Epidemiology, University of Birmingham

Hypothesis

Can default risk factor values from electronic medical records effectively identify high-risk patients for cardiovascular disease assessment?

Conclusion

Using routine data from primary care databases can effectively identify a population at high risk of cardiovascular disease.

Supporting Evidence

The area under the curve for the prior estimate of cardiovascular risk was significantly greater than for age-based strategies.
Using minimum data, the model identified 15.5% of patients at greater than 20% ten-year cardiovascular risk.
The study demonstrated that prior estimates of cardiovascular risk can effectively prioritize patients for assessment.

Takeaway

Doctors can use existing patient data to find people at risk of heart problems, even if they don't have all the test results yet.

Methodology

The study used electronic medical records to derive prior estimates of cardiovascular risk and validated these estimates against a reference standard.