Diagnosing asthma: the fit between survey and administrative database

Can Respir J. Nov-Dec 2002;9(6):407-12. doi: 10.1155/2002/921497.


Background: Standard methods for population studies of asthma include surveying population samples using questionnaires and examining people in laboratories. These procedures are extremely expensive. It would be helpful if, at least for some purposes, they could be replaced by cheaper techniques with adequate validity.

Objectives: To determine agreement between survey and database in regard to the prevalence of asthma.

Methods: Responses to survey questions about asthma symptoms in the past 12 months were linked to physician claims in the Manitoba Population Health Repository.

Results: The overall agreement was moderate (k=0.45 to 0.50) and increased if two years of physician claims were studied (k=0.55 to 0.59); studying additional years had no further effect on agreement. Sex and smoking did not significantly affect the kappa scores.

Conclusions: There were several plausible reasons for discrepancies. Symptoms recorded on the survey were intrinsically different from those recorded for physician visits. Physicians also used other respiratory codes instead of asthma, and survey participants did not see a physician every year for asthma. The estimates of prevalence derived from the survey and the administrative database included two overlapping groups of people. In each, the diagnosis of asthma seems justifiable, although the agreement between the two groups was only moderate to substantial. Both methods are useful, although they are useful for different purposes. Health care utilization estimates may be particularly useful for studying trends over time.

Publication types

  • Comparative Study
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adolescent
  • Adult
  • Age Distribution
  • Asthma / diagnosis*
  • Asthma / epidemiology*
  • Child
  • Child, Preschool
  • Cohort Studies
  • Databases as Topic
  • Female
  • Health Surveys
  • Humans
  • Male
  • Manitoba / epidemiology
  • Middle Aged
  • Observer Variation
  • Prevalence
  • Reproducibility of Results
  • Sensitivity and Specificity
  • Severity of Illness Index
  • Sex Distribution
  • Surveys and Questionnaires