Comparing methods for identifying patients with heart failure using electronic data sources
- Equal contributors
1 Henry Ford Heart and Vascular Institute, Henry Ford Hospital, 2799 W. Grand Blvd., Detroit, MI 48202 USA
2 Center for Health Services Research, Henry Ford Hospital, One Ford Place, Detroit, MI 48202 USA
3 Biostatistics and Research Epidemiology, Henry Ford Hospital, One Ford Place, Detroit, MI 48202 USA
BMC Health Services Research 2009, 9:237 doi:10.1186/1472-6963-9-237Published: 18 December 2009
Accurately indentifying heart failure (HF) patients from administrative claims data is useful for both research and quality of care efforts. Yet, there are few comparisons of the various claims data criteria (also known as claims signatures) for identifying HF patients. We compared various HF claim signatures to assess their relative accuracy.
In this retrospective study, we identified 4174 patients who received care from a large health system in southeast Michigan and who had ≥1 HF encounter between January 1, 2004 and December 31, 2005. Four hundred patients were chosen at random and a detailed chart review was performed to assess which met the Framingham HF criteria. The sample was divided into 300 subjects for derivation and 100 subjects for validation. Sensitivity, specificity,, and area under the curve (AUC) were determined for the various claim signatures. The criteria with the highest AUC were retested in the validation set.
Of the 400 patients sampled, 65% met Framingham HF criteria, and 56% had at least one B-type Natriuretic Peptide (BNP) measurement. There was substantial variation between claims signatures in terms of sensitivity (range 15%-77%) and specificity (range 69%-100%). The best performing criteria in the derivation set was if patients met any one of the following: ≥2 HF encounters, any hospital discharge diagnosis of HF, or a BNP ≥200 pg/ml. These criteria showed a sensitivity of 76%, specificity of 75%, and AUC of 0.754 for meeting the Framingham HF criteria. This claims signature performed similarly in the validation set.
Claim signatures for HF vary greatly in their relative sensitivity and specificity. These findings may facilitate efforts to identify HF patients for research and quality improvement efforts.