(A) Identification and Classification of Asthma Patients Using a Computerized Database - Data from a Large Israeli Health Maintenance Organization

Publication Number: 634

Background: Asthma is a common chronic disease that has an important effect on the quality of life. Asthma can be difficult to define when using computerized databases, since its diagnosis is based on non-specific respiratory symptoms and spirometry, that are not recorded routinely.

Objectives: To assess criteria for the identification of asthma patients and classification of its severity using computerized real-world clinical and administrative data.

Methods: A retrospective study using the computerized database of Maccabi Healthcare Services (MHS), a large health maintenance organization. Prevalent asthma patients on Dec 31 2018 (age ≥6 years) were defined according to asthma diagnoses, purchases of inhalers and other drugs indicated for asthma. Those diagnosed with COPD were excluded. Patients were classified into subgroups to represent disease severity, by their mean daily dose of inhaled corticosteroids (ICS) purchased during 2017-2018, as well as by purchases of second controller (long-acting beta agonist, LABA and/or leukotriene receptor antagonists) and short-acting beta agonists (SABA). The medical record of a sample of 200 patients was reviewed by pulmonologist for further validation. Patients were characterized according to socio-demographic variables and asthma related variables.

Results: We identified 143,813 asthma patients. The mean age on Dec 31 2018 was 40.01 (±19.43) and 73,441 (51.1%) were females. Diagnosis of asthma by a specialist was available for 58,205 (40.5%) patients. The proportion of past/current smokers was 14.2% among those age ≥18 years. The distribution of subgroups was (in order of decreased disease severity): High dose ICS n=4240 (2.9%); Medium dose ICS n=8027 (5.6%); low dose ICS n=13,118 (9.1%); very low dose ICS n=30,775 (21.4%); SABA only n=15,225 (10.6%); no treatment (did not purchase ICS/ LABA/SABA or did not purchase any drug for asthma) n=72,428 (50.4%). The results of the medical records review were consistent with the identification and classification criteria. Older age was associated with increased disease severity (no treatment 38.15 ±18.19 vs. high dose ICS 52.84 ±21.01, P< 0.001). The proportion of factors assessed in 2018, that may indicate of poor control of asthma also increased with disease severity: using ≥3 SABA inhalers; ≥2 courses of oral corticosteroids (OCS); chronic use of OCS; ≥1 hospitalization.

Conclusions: The current study offers criteria for the identification of asthma patients and classification of its severity. Identifying those with uncontrolled asthma will enable healthcare providers to offer them appropriate treatment and possibly prevent future exacerbations, hospitalization and improve the patients' quality of life.