Preferred provider organization claims showed high predictive value but missed substantial proportion of adults with high-risk conditions

J Clin Epidemiol. 2005 Jun;58(6):624-8. doi: 10.1016/j.jclinepi.2004.11.020.

Abstract

Background and objective: We assessed the validity and utility of a claims-based ICD-9-CM algorithm for identifying preferred provider organization (PPO) enrollees ages 18-64 years at high risk for influenza complications.

Methods: PPO enrollees with >/= 2 encounters in an ambulatory setting or >/= 1 encounters in an inpatient or emergency room setting with ICD-9-CM diagnosis codes for the high-risk conditions were considered algorithm positive. Stratified random sampling was used to select 1,001 algorithm-positive and 330 algorithm-negative enrollees for medical chart abstractions.

Results: The prevalence of high-risk conditions using claims data was 2.5% compared to 18.2% according to medical records. The algorithm had a sensitivity of 12% and a specificity of 99%. Positive and negative predictive values were 87 and 84%, respectively. Sensitivity was twofold higher among adults aged 50-64 years than among younger adults (17 vs. 9%). Applying an algorithm definition of >/= 1 encounters in any setting resulted in an increased sensitivity, but captured a higher proportion of false positives.

Conclusion: A claims-positive record was highly indicative of the presence of high-risk conditions, but such claims missed a large proportion of PPO enrollees with high-risk conditions. It is important to assess the validity of administrative data in different age groups.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, U.S. Gov't, P.H.S.
  • Validation Study

MeSH terms

  • Adolescent
  • Adult
  • Age Factors
  • Algorithms*
  • Blue Cross Blue Shield Insurance Plans
  • Cardiovascular Diseases / epidemiology
  • Hemoglobinopathies / epidemiology
  • Humans
  • Immunocompromised Host
  • Influenza Vaccines / administration & dosage
  • Influenza, Human / complications*
  • Influenza, Human / prevention & control
  • Insurance Claim Review / statistics & numerical data*
  • International Classification of Diseases / statistics & numerical data*
  • Kidney Diseases / epidemiology
  • Lung Diseases / epidemiology
  • Middle Aged
  • Preferred Provider Organizations*
  • Reproducibility of Results

Substances

  • Influenza Vaccines