Mohsen Yaghoubi1, Amin Adibi1, Zafar Zafari2, J Mark FitzGerald3, Shawn D Aaron4, Kate M Johnson1, Mohsen Sadatsafavi5. 1. Respiratory Evaluation Sciences Program, Collaboration for Outcomes Research and Evaluation, Faculty of Pharmaceutical Sciences, University of British Columbia, Vancouver, Canada. 2. Pharmaceutical Health Services Research at University of Maryland School of Pharmacy, Baltimore, Md. 3. Department of Medicine, University of British Columbia, Vancouver, Canada. 4. Ottawa Hospital Research Institute, University of Ottawa, Ottawa, Canada. 5. Respiratory Evaluation Sciences Program, Collaboration for Outcomes Research and Evaluation, Faculty of Pharmaceutical Sciences, University of British Columbia, Vancouver, Canada; Department of Medicine, University of British Columbia, Vancouver, Canada. Electronic address: msafavi@mail.ubc.ca.
Abstract
BACKGROUND: Asthma diagnosis in the community is often made without objective testing. OBJECTIVE: The aim of this study was to evaluate the cost-effectiveness of implementing a stepwise objective diagnostic verification algorithm among patients with community-diagnosed asthma in the United States. METHODS: We developed a probabilistic time-in-state cohort model that compared a stepwise asthma verification algorithm on the basis of spirometry testing and a methacholine challenge test against the current standard of care over 20 years. Model input parameters were informed from the literature and with original data analyses when required. The target population was US adults (≥15 years old) with physician-diagnosed asthma. The final outcomes were costs (in 2018 dollars) and quality-adjusted life years (QALYs), discounted at 3% annually. Deterministic and probabilistic analyses were undertaken to examine the effect of alternative assumptions and uncertainty in model parameters on the results. RESULTS: In a simulated cohort of 10,000 adults with diagnosed asthma, the stepwise algorithm resulted in removal of the diagnosis of 3,366. This was projected to be associated with savings of $36.26 million in direct costs and a gain of 4,049.28 QALYs over 20 years. Extrapolating these results to the US population indicated an undiscounted potential savings of $56.48 billion over 20 years. The results were robust against alternative assumptions and plausible changes in values of input parameters. CONCLUSION: Implementation of a simple diagnostic testing algorithm to verify asthma diagnosis might result in substantial savings and improvement in patients' quality of life.
BACKGROUND:Asthma diagnosis in the community is often made without objective testing. OBJECTIVE: The aim of this study was to evaluate the cost-effectiveness of implementing a stepwise objective diagnostic verification algorithm among patients with community-diagnosed asthma in the United States. METHODS: We developed a probabilistic time-in-state cohort model that compared a stepwise asthma verification algorithm on the basis of spirometry testing and a methacholine challenge test against the current standard of care over 20 years. Model input parameters were informed from the literature and with original data analyses when required. The target population was US adults (≥15 years old) with physician-diagnosed asthma. The final outcomes were costs (in 2018 dollars) and quality-adjusted life years (QALYs), discounted at 3% annually. Deterministic and probabilistic analyses were undertaken to examine the effect of alternative assumptions and uncertainty in model parameters on the results. RESULTS: In a simulated cohort of 10,000 adults with diagnosed asthma, the stepwise algorithm resulted in removal of the diagnosis of 3,366. This was projected to be associated with savings of $36.26 million in direct costs and a gain of 4,049.28 QALYs over 20 years. Extrapolating these results to the US population indicated an undiscounted potential savings of $56.48 billion over 20 years. The results were robust against alternative assumptions and plausible changes in values of input parameters. CONCLUSION: Implementation of a simple diagnostic testing algorithm to verify asthma diagnosis might result in substantial savings and improvement in patients' quality of life.