OBJECTIVES: To describe the relationships between persistent asthma defined by administrative versus survey data and their stability over time. STUDY DESIGN: Longitudinal survey and retrospective administrative database. METHODS: Administrative data were used to identify patients meeting the Healthcare Effectiveness Data and Information Set (HEDIS) criteria for persistent asthma in year 1 (2006). At the end of year 2 and on 3 occasions during year 3, patients were mailed a survey to define persistent asthma based on symptoms and medication use in the prior month and exacerbations in the prior 12 months. Administrative data were also used to define medical utilization for asthma in year 3. RESULTS: Of 13,833 eligible patients, 2895 (20.9%) returned the survey; 2751 of these respondents reported physician-diagnosed asthma, of whom 2517 (91.5%) had survey-defined persistent asthma. Patients having survey-defined persistent asthma (68.0%) were more likely to requalify as having HEDIS-defined persistent asthma in year 2 than patients not having survey-defined persistent asthma (22.2%). However, 81.6% of survey respondents who did not requalify as having HEDIS-defined persistent asthma in year 2 had survey-defined persistent asthma. Patients with survey-defined persistent asthma in year 2 had significantly more medical utilization for asthma in year 3 than patients without survey-defined persistent asthma. Approximately 82% of the 799 patients completing all 4 surveys had persistent asthma on all surveys. CONCLUSIONS: HEDIS-defined persistent asthma is generally consistent with survey-defined persistent asthma. Persistent asthma usually remains persistent over a 3-year period, indicating that it is a stable characteristic of asthma for most patients. The low survey response rate suggests that further population-based studies will be necessary to confirm the validity and generalizability of our study findings regarding persistent asthma.
OBJECTIVES: To describe the relationships between persistent asthma defined by administrative versus survey data and their stability over time. STUDY DESIGN: Longitudinal survey and retrospective administrative database. METHODS: Administrative data were used to identify patients meeting the Healthcare Effectiveness Data and Information Set (HEDIS) criteria for persistent asthma in year 1 (2006). At the end of year 2 and on 3 occasions during year 3, patients were mailed a survey to define persistent asthma based on symptoms and medication use in the prior month and exacerbations in the prior 12 months. Administrative data were also used to define medical utilization for asthma in year 3. RESULTS: Of 13,833 eligible patients, 2895 (20.9%) returned the survey; 2751 of these respondents reported physician-diagnosed asthma, of whom 2517 (91.5%) had survey-defined persistent asthma. Patients having survey-defined persistent asthma (68.0%) were more likely to requalify as having HEDIS-defined persistent asthma in year 2 than patients not having survey-defined persistent asthma (22.2%). However, 81.6% of survey respondents who did not requalify as having HEDIS-defined persistent asthma in year 2 had survey-defined persistent asthma. Patients with survey-defined persistent asthma in year 2 had significantly more medical utilization for asthma in year 3 than patients without survey-defined persistent asthma. Approximately 82% of the 799 patients completing all 4 surveys had persistent asthma on all surveys. CONCLUSIONS: HEDIS-defined persistent asthma is generally consistent with survey-defined persistent asthma. Persistent asthma usually remains persistent over a 3-year period, indicating that it is a stable characteristic of asthma for most patients. The low survey response rate suggests that further population-based studies will be necessary to confirm the validity and generalizability of our study findings regarding persistent asthma.
Authors: Andrew C Pool; Jennifer L Kraschnewski; Jennifer M Poger; Joshua Smyth; Heather L Stuckey; Timothy J Craig; Erik B Lehman; Chengwu Yang; Christopher N Sciamanna Journal: PLoS One Date: 2017-02-03 Impact factor: 3.240
Authors: M P Dizon; A M Yu; R K Singh; J Wan; M-M Chren; C Flohr; J I Silverberg; D J Margolis; S M Langan; K Abuabara Journal: Br J Dermatol Date: 2018-04-25 Impact factor: 9.302
Authors: Patrick W Sullivan; Vahram H Ghushchyan; David P Skoner; Jason LeCocq; Siyeon Park; Robert S Zeiger Journal: J Allergy Clin Immunol Pract Date: 2020-12-05