Searching multiple clinical information systems for longer time periods found more prevalent cases of asthma.
OBJECTIVE
The development of a reliable asthma registry is an important first step for conducting population-based asthma disease management. This study developed a computerized algorithm for defining prevalent asthma, identified operational difficulties, and summarized data on asthma prevalence in the study population.


METHODS
As part of a study of the incidence of occupational asthma, we used the electronic databases of a large health maintenance organization to develop a computerized algorithm for defining prevalent asthma and validated it against chart review. The predictive values of eight health care utilization profiles were validated by chart review to establish the algorithm.


RESULTS
The 1-year treated prevalence of asthma was 4.1% among members aged 15-55; the pharmacy database identified 61% of cases, and the outpatient care database 66%. Extending the outpatient care window from 1 year to 2 years increased estimated prevalence to 5.3%, with 81% now found in the outpatient care database.


CONCLUSIONS
This analysis illustrates the benefit of using multiple databases for more accurate enumeration of cases and the impact of extending the search in time. These results are useful for researchers who can use such databases in selecting algorithms to define and identify asthma for their own purposes.
Vollmer
William M
WM
Center for Health Research, 3800 N. Interstate Avenue, Portland, OR 97227-110, USA. william.vollmer@kpchr.org
O'Connor
Elizabeth A
EA
Heumann
Michael
M
Frazier
E Ann
EA
Breen
Victor
V
Villnave
Jacqueline
J
Buist
A Sonia
AS
D000293:Adolescent; D000328:Adult; D017677:Age Distribution; D000465:Algorithms; D001249:Asthma / Q000453:epidemiology*; D016208:Databases, Factual; D011307:Drug Prescriptions / Q000706:statistics & numerical data; D005260:Female; D006296:Health Services / Q000706:statistics & numerical data; D006801:Humans; D008297:Male; D016347:Medical Records Systems, Computerized / Q000706:statistics & numerical data; D008875:Middle Aged; D009784:Occupational Diseases / Q000453:epidemiology*; D009922:Oregon / Q000453:epidemiology; D015995:Prevalence; D012042:Registries; D015203:Reproducibility of Results; D017678:Sex Distribution