Email updates

Keep up to date with the latest news and content from BMC Health Services Research and BioMed Central.

Open Access Research article

Claims-based algorithms for identifying Medicare beneficiaries at high estimated risk for coronary heart disease events: a cross-sectional study

Evan L Thacker12, Paul Muntner1, Hong Zhao1, Monika M Safford3, Jeffrey R Curtis3, Elizabeth Delzell1, Vera Bittner3, Todd M Brown3 and Emily B Levitan1*

Author Affiliations

1 Department of Epidemiology, University of Alabama at Birmingham, Birmingham, AL 35294-0022, USA

2 Department of Health Science, Brigham Young University, Provo, UT, USA

3 Department of Medicine, University of Alabama at Birmingham, Birmingham, AL, USA

For all author emails, please log on.

BMC Health Services Research 2014, 14:195  doi:10.1186/1472-6963-14-195

Published: 29 April 2014

Abstract

Background

Databases of medical claims can be valuable resources for cardiovascular research, such as comparative effectiveness and pharmacovigilance studies of cardiovascular medications. However, claims data do not include all of the factors used for risk stratification in clinical care. We sought to develop claims-based algorithms to identify individuals at high estimated risk for coronary heart disease (CHD) events, and to identify uncontrolled low-density lipoprotein (LDL) cholesterol among statin users at high risk for CHD events.

Methods

We conducted a cross-sectional analysis of 6,615 participants ≥66 years old using data from the REasons for Geographic And Racial Differences in Stroke (REGARDS) study baseline visit in 2003–2007 linked to Medicare claims data. Using REGARDS data we defined high risk for CHD events as having a history of CHD, at least 1 risk equivalent, or Framingham CHD risk score >20%. Among statin users at high risk for CHD events we defined uncontrolled LDL cholesterol as LDL cholesterol ≥100 mg/dL. Using Medicare claims-based variables for diagnoses, procedures, and healthcare utilization, we developed algorithms for high CHD event risk and uncontrolled LDL cholesterol.

Results

REGARDS data indicated that 49% of participants were at high risk for CHD events. A claims-based algorithm identified high risk for CHD events with a positive predictive value of 87% (95% CI: 85%, 88%), sensitivity of 69% (95% CI: 67%, 70%), and specificity of 90% (95% CI: 89%, 91%). Among statin users at high risk for CHD events, 30% had LDL cholesterol ≥100 mg/dL. A claims-based algorithm identified LDL cholesterol ≥100 mg/dL with a positive predictive value of 43% (95% CI: 38%, 49%), sensitivity of 19% (95% CI: 15%, 22%), and specificity of 89% (95% CI: 86%, 90%).

Conclusions

Although the sensitivity was low, the high positive predictive value of our algorithm for high risk for CHD events supports the use of claims to identify Medicare beneficiaries at high risk for CHD events.

Keywords:
High risk; Coronary heart disease; Risk stratification; Medicare claims