Misclassification of incident hospitalized and outpatient heart failure in administrative claims data: the Atherosclerosis Risk in Communities (ARIC) study

Pharmacoepidemiol Drug Saf. 2017 Apr;26(4):421-428. doi: 10.1002/pds.4162. Epub 2017 Jan 25.

Abstract

Purpose: The aim of this study was to quantify the influence of the length of the look-back period on misclassification of heart failure (HF) incidence in Medicare claims available for participants of a population-based cohort.

Methods: Atherosclerosis Risk in Communities participants with ≥3 years of continuous fee-for-service Medicare enrollment from 2000 to 2012 was assigned an index date 36 months after enrollment separating the time-in-observation period into the look-back and the incidence periods. Incident HF events were identified using ICD-9-CM code algorithms as the first observed hospitalization claim or the second of two HF outpatient claims occurring within 12 months. Using 36 months as a referent, the look-back period was reduced by 6-month increments. For each look-back period, we calculated the incidence rate, percent of prevalent HF events misclassified as incident, and loss in sample size.

Results: We identified 9568 Atherosclerosis Risk in Communities participants at risk for HF. For hospitalized and outpatient HF, the number of events misclassified as incident increased, and the total number of incident events decreased with increased length of the look-back period. The incident rate (per 1000 person years) decreased with increased length of the look-back period from 6 to 36 months and had a greater impact on outpatient HF; for example, from 11.2 to 10.6 for ICD-9-CM 428.xx hospitalization in the primary position and 10.5 to 7.9 for outpatient HF.

Conclusion: Our estimates can be used to optimize trade-offs between the degree of misclassification and number of events in the estimation of incident HF from administrative claims data, as pertinent to different study questions. Copyright © 2017 John Wiley & Sons, Ltd.

Keywords: administrative claims; heart failure; hospitalizations; misclassification; outpatient.

MeSH terms

  • Aged
  • Algorithms
  • Cohort Studies
  • Databases, Factual / standards
  • Databases, Factual / statistics & numerical data*
  • Female
  • Heart Failure / diagnosis
  • Heart Failure / epidemiology*
  • Hospitalization / statistics & numerical data*
  • Humans
  • Incidence
  • International Classification of Diseases
  • Male
  • Medicare
  • Outpatients / statistics & numerical data*
  • Prospective Studies
  • Sample Size
  • Time Factors
  • United States