Identification of Asthmatic Children Using Prescription Data and Diagnosis

Eur J Clin Pharmacol. 2007 Jun;63(6):605-11. doi: 10.1007/s00228-007-0286-4. Epub 2007 Mar 27.


Objective: The aim of the study was to develop and validate a method for identifying asthmatic children between 6 and 14 years of age based on prescription data on anti-asthmatic drugs and diagnostic data.

Methods: A register-based study of 125,907 Danish children aged 6-14 years identified 9695 children who had redeemed at least one anti-asthmatic drug prescription in 2002. The asthma diagnosis in these children was validated by discharge information and by a questionnaire completed by general practitioners. Models based on combinations of different types of drugs were tested to find the best model that would include as many children as possible with a validated diagnosis and exclude as many false positives as possible. Different time windows were tested in terms of detecting the children and the observation period of refilling prescriptions.

Results: The highest specificity of 0.86 [95% confidence interval (95% CI): 0.84-0.87] together with a sensitivity of 0.63 (95% CI: 0.62-0.65) were found in the model that included children who had redeemed a prescription for any anti-asthmatic drug - with the exception of prescriptions for beta2-agonists as liquid, one prescription only of inhaled beta2-agonist or an inhaled steroid - during a 12-month period. Lengthening the observation time by 6 months did not significantly improve the specificity (0.87; 95% CI: 0.85-0.88), but it did result in a statistically significantly lower sensitivity (0.59; 95% CI: 0.58-0.60).

Conclusion: Register-based data on redeemed prescriptions can be utilised to identify asthmatic school children. This method will be useful in health services research and in the proactive care of asthmatic children.

Publication types

  • Validation Study

MeSH terms

  • Adolescent
  • Anti-Asthmatic Agents / therapeutic use*
  • Asthma* / diagnosis
  • Asthma* / drug therapy
  • Child
  • Cross-Sectional Studies
  • Databases, Factual
  • Denmark / epidemiology
  • Drug Information Services
  • Drug Prescriptions / statistics & numerical data*
  • Family Practice / statistics & numerical data
  • Female
  • Humans
  • Male
  • Medical Records Systems, Computerized*
  • Practice Patterns, Physicians'*
  • Registries


  • Anti-Asthmatic Agents