A FRAMEWORK FOR DEVELOPING A FLEXIBLE CONTROL-BASED ASTHMA POLICY MODEL

Author(s)

Jonathan D Campbell, MS, PhD, Senior Post-Doctoral Fellow1, Ryan N Hansen, PharmD, Senior Fellow1, Andrew Briggs, DPhil, Professor2, Sean D Sullivan, PhD, RPh, Professor of Pharmacy and Public Health and Director11University of Washington, Seattle, WA, USA; 2 University of Glasgow, Glasgow, United Kingdom

OBJECTIVES: The goal of asthma management is to gain and maintain control. Several validated patient-reported measures are available to assess the degree of control: Asthma Control Questionnaire (ACQ), Asthma Control Test (ACT), and the Asthma Therapy and Assessment Questionnaire (ATAQ). We propose a flexible and transparent model structure that represents disease variability through exacerbation rates and any one of the three control instruments. METHODS: We developed a Markov model to simulate cohorts transitioning among six health states: an asthma control continuum state (variability in control is tracked using one of the three control instruments), three severity levels of asthma exacerbation, and asthma and non-asthma related death. To estimate the cost and outcome weights for the control continuum state, we explored the relationship between the ATAQ (higher ATAQ = less control) and management costs (including absenteeism costs) and utilities using a large asthma registry of exacerbation-free patients. A hypothetical asthma intervention added to standard-of-care was compared to standard-of-care alone as summarized by the following product profile: a 50% reduction in asthma exacerbation rates, a 0.5 absolute improvement in the ATAQ score, and an additional $10,000 per annum intervention cost. RESULTS: The estimated change in bi-weekly asthma management costs for a one unit increase in the ATAQ score was $36.12 (robust SE = $3.95) and for utilities was -0.05 (robust SE = 0.0041). Assuming a five year time horizon, the hypothetical intervention plus standard-of-care had an incremental mean cost of $25,800 (95% interval $10,600, $41,000), quality adjusted life year (QALY) of 0.257 (0.106, 0.435), and cost per QALY of $100,500/QALY ($13,700, $199,800). CONCLUSIONS: As relationships emerge between any of the instruments of control and costs and utilities, this versatile model can forecast: long-term burden of disease, value of existing and emerging interventions, and inputs that yield the highest return from further study.

Conference/Value in Health Info

2009-05, ISPOR 2009, Orlando, FL, USA

Value in Health, Vol. 12, No. 3 (May 2009)

Code

PMC4

Topic

Clinical Outcomes, Methodological & Statistical Research

Topic Subcategory

Clinical Outcomes Assessment, Modeling and simulation

Disease

Multiple Diseases, Respiratory-Related Disorders

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