Abstract:
BACKGROUND:Cause of death is often not available in administrative claims data. OBJECTIVE:To develop claims-based algorithms to identify deaths due to fatal cardiovascular disease (CVD; ie, fatal coronary heart disease [CHD] or stroke), CHD, and stroke. METHODS:Reasons for Geographic and Racial Differences in Stroke (REGARDS) study data were linked with Medicare claims to develop the algorithms. Events adjudicated by REGARDS study investigators were used as the gold standard. Stepwise selection was used to choose predictors from Medicare data for inclusion in the algorithms. C-index, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were used to assess algorithm performance. Net reclassification index (NRI) was used to compare the algorithms with an approach of classifying all deaths within 28 days following hospitalization for myocardial infarction and stroke to be fatal CVD. RESULTS:Data from 2,685 REGARDS participants with linkage to Medicare, who died between 2003 and 2013, were analyzed. The C-index for discriminating fatal CVD from other causes of death was 0.87. Using a cut-point that provided the closest observed-to-predicted number of fatal CVD events, the sensitivity was 0.64, specificity 0.90, PPV 0.65, and NPV 0.90. The algorithms resulted in positive NRIs compared with using deaths within 28 days following hospitalization for myocardial infarction and stroke. Claims-based algorithms for discriminating fatal CHD and fatal stroke performed similarly to fatal CVD. CONCLUSION:The claims-based algorithms developed to discriminate fatal CVD events from other causes of death performed better than the method of using hospital discharge diagnosis codes.
journal_name
Pharmacoepidemiol Drug Safjournal_title
Pharmacoepidemiology and drug safetyauthors
Xie F,Colantonio LD,Curtis JR,Kilgore ML,Levitan EB,Monda KL,Safford MM,Taylor B,Woodward M,Muntner Pdoi
10.1002/pds.4421subject
Has Abstractpub_date
2018-07-01 00:00:00pages
740-750issue
7eissn
1053-8569issn
1099-1557journal_volume
27pub_type
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