Address correspondence to Robert J. Prosser, M.A., Ph.D., Pharmaceutical Outcomes Programme, Children's and Women's Health Centre of British Columbia, University of British Columbia, 4480 Oak Street, Room B404, Vancouver, BC, Canada V6H 3V4. Bruce C. Carleton, B.Pharm., Pharm.D., is with the Pharmaceutical Outcomes Programme, Children's and Women's Health Centre of British Columbia, Child and Family Research Institute, University of British Columbia, Vancouver, BC. M. Anne Smith, B.Sc. (Pharm), M.Sc., is with the Pharmaceutical Outcomes Programme, Children's and Women's Health Centre of British Columbia, Vancouver, BC.
Identifying Persons with Treated Asthma Using Administrative Data via Latent Class Modelling
Article first published online: 10 SEP 2007
© Health Research and Educational Trust
Health Services Research
Volume 43, Issue 2, pages 733–754, April 2008
How to Cite
Prosser, R. J., Carleton, B. C. and Smith, M. A. (2008), Identifying Persons with Treated Asthma Using Administrative Data via Latent Class Modelling. Health Services Research, 43: 733–754. doi: 10.1111/j.1475-6773.2007.00775.x
- Issue published online: 10 SEP 2007
- Article first published online: 10 SEP 2007
- Administrative data;
- case definition;
- latent class analysis;
Objective. To develop a parsimonious model of the respiratory patient population in British Columbia (BC), Canada through latent class modelling (LCM), using administrative data records and to assess conventional case definitions for asthma in relation to model-based case selection.
Data Sources. 1996–2001 data from linked provincial databases containing fee-for-service physician billing records, hospital inpatient separation abstracts, and prescription drug purchase records for 1.9 million BC respiratory patients.
Study Design. This is a retrospective methodological/descriptive study that assesses case definitions for asthma in terms of sensitivity and specificity using a model fitted to seven physician, hospital and medication utilization markers in place of a conventional gold standard.
Data Collection. We computed values of the treatment markers for each of the 5 years for each patient aged 5–55 years who had had at least one occurrence of a respiratory diagnosis code.
Principal Findings. The marker for prescription of short-acting β agonists (SABAs) consistently had the highest sensitivity. Markers' specificities ranged from 0.97 to 1.0. The conventional case definitions' sensitivities were 0.41–0.87; specificities ranged from 0.98 to 0.997. Model-based estimates of asthma prevalence increased from 827/10,000 in 1996 to 992/10,000 in 2001. Conventional case definitions' estimates were consistently lower.
Conclusions. The linkage between utilization and case status is more complex than conventional case definitions allow for. LCM-based case classification was consistent over time and tends to lead to larger prevalence estimates than conventional definitions. The estimated increases in asthma prevalence are reliable. LCM provides health services planners with a useful probability-based approach for developing and assessing case definitions and estimating case prevalence.