Using an asthma control questionnaire and administrative data to predict health-care utilization

Chest. 2006 Apr;129(4):918-24. doi: 10.1378/chest.129.4.918.


Objective: To examine the merits of the Asthma Therapy Assessment Questionnaire (ATAQ) control index together with prior asthma health-care utilization from administrative data in predicting future acute asthma health-care utilization.

Design: Prospective cohort study.

Population: A total of 4,788 adult asthma patients aged 17 to 93 years who completed a baseline evaluation and had at least 6 months of follow-up data.

Statistical methods: Classification and regression tree methodology to predict future risk of acute health-care utilization events.

Results: These results show that the ATAQ control index and administrative data are jointly useful for predicting future health-care utilization. The utility of the ATAQ control index in the presence of information about prior health-care utilization is to further stratify risk among the subset of younger individuals who did not have any prior acute health-care utilization. While administrative health-care utilization data served as the strongest predictor of future health-care utilization, the ATAQ control index helped to identify 1% of individuals without recent acute care that had approximately a sixfold elevated risk (95% confidence interval, 4.2 to 8.4) of future acute health-care utilization. This is an important result since only a small fraction of individuals with acute events in a given year will have had acute events in the previous year.

Conclusion: These findings should assist the practicing clinician and organizations interested in population-based asthma disease management.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adolescent
  • Adult
  • Age Factors
  • Aged
  • Aged, 80 and over
  • Algorithms
  • Asthma / prevention & control*
  • Female
  • Follow-Up Studies
  • Health Services / statistics & numerical data*
  • Humans
  • Male
  • Middle Aged
  • Predictive Value of Tests
  • Prospective Studies
  • Regression Analysis
  • Surveys and Questionnaires*