Comparing methods for identifying patients with heart failure using electronic data sources

Abstract

BackgroundAccurately 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.MethodsIn 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.ResultsOf 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.ConclusionClaim 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.

Validity of Heart Failure Diagnoses in Administrative Databases: A Systematic Review and Meta-Analysis

“…Cardiac disease registries were used in two studies [53], [54], while a specific set of diagnostic criteria were incorporated in the reference standards of the seven remaining studies [17], [34], [42], [44], [45], [55], [56].…”

Association of Antidiabetic Medications Targeting the Glucagon-Like Peptide 1 Pathway and Heart Failure Events in Patients With Diabetes

“…Hospitalization for HF was the first inpatient admission with a primary discharge diagnosis of HF during the period of observation. A primary hospital discharge diagnosis of HF has been shown by our group and others to be a highly specific claim signature for HF (specificity 95–100%)(16, 17). Secondary endpoints included all-cause hospitalization and all-cause mortality.…”

“…Finally, the information used in this study was primarily sourced from administrative and claims data. Although these sources have some potential for misclassification, we have previously shown that hospital discharge diagnoses for HF are highly specific (16) and that pharmacy claims produce consistently predictive measures of drug exposure (35). …”

Development of administrative data algorithms to identify patients with critical limb ischemia

“…Prior reports of the use of administrative data to identify various patient populations have shown sensitivities of 67% (urinary tract infections), 36-69% (heart failure), 76% (acute myocardial infarction), 83% (diabetes mellitus), 65% (hypertension), and 29% (PAD). [20][21][22] Hebert et al 9 applied a similar Medicare databased approach to identify diabetic patients using different algorithms, and reported sensitivity values ranging from 5% to 79%. The sensitivity of our algorithms ranged from 29% to 92%.…”