ASSESSMENT OF ASTHMA USING AUTOMATED AND FULL-TEXT MEDICAL RECORDS

Automated medical records systems are used to study clinical outcomes and quality of care, but this requires accurate disease identification and assessment of severity. We sought to determine the reliability of identifying asthmatics through automated medical and pharmacy records , and the adequacy of such data for severity assessment. All adult hea lth maintenance organization (HMO) members who received at least one a sthma drug and an asthma diagnosis between April 1988 and September 19 91 were identified. Records of a random sam pie were reviewed to valid ate the diagnosis and extract clinical information. Asthma drugs were dispensed to 15,491 individuals; 7583 (49%) also received an asthma di agnosis. Asthma drug use was three times greater for persons with diag nosed asthma compared to those with no diagnosis. Record review reveal ed that a coded asthma diagnosis had a positive predictive value of 86 %. Nearly 4000 ambulatory encounters were reviewed, 10% of which were for asthma; the median number of encounters was two. Asthma symptoms w ere mentioned in 9% of all encounters; wheezing was most common. Peak flow and spirometry were measured in 4% and 1% of encounters, respecti vely. Records from recipients of asthma drugs who racked an asthma dia gnosis showed that 79% did not have asthma. Automated medical and phar macy records from an HMO were relatively accurate when used to identif y individuals with asthma. Similarly, most asthma drug recipients who lacked a coded diagnosis of asthma did not have asthma. However, conve ntion al full-text records usually do not con ta in sufficient informa tion to assess asthma severity, limiting the utility of such records f or research and quality improvement.