USE OF AN AUTOMATED PRESCRIPTION DATABASE TO IDENTIFY INDIVIDUALS WITH ASTHMA

We used medication-dispensing information for 4 years (1/1/87 through 12/31/90) to examine the utilization of anti-asthma medications among 175,562 members of a large health maintenance organization. A total of 297,863 anti-asthma medications was dispensed during the study period, over one-half of which (55%) were beta-agonists, followed by aminophylline preparations (23%) and inhaled corticosteroids (13%). Next, we compared the predictive value of three algorithms for identifying individuals with asthma: (1) two or more beta-agonist dispensings, (2) both a beta-agonist and an inhaled corticosteroid dispensing, and (3) five or more total anti-asthma dispensings. We performed chart reviews for 40 subjects aged 5-45 years in each of these three groups and made a clinical judgment, based on all available information in the chart, as to whether each patient had asthma. Two levels of certainty were used: ''any asthma'' and ''definite asthma.'' All 120 charts reviewed presented a clinical picture consistent with asthma. However, patients identified by the algorithm that included both a beta-agonist and an inhaled corticosteroid were more likely to meet our criteria for ''definite'' asthma and more likely to have moderate to severe asthma. These results demonstrate the feasibility of using an automated outpatient pharmacy database to identify patients with asthma.