David A Katz1, Christine Hamlin2, Mark W Vander Weg3, Kathleen M Grant4, Kenda R Stewart Steffensmeier2, Monica Paez2, Sarah T Hawley5, Gary Gaeth6. 1. Comprehensive Access & Delivery Research and Evaluation (CADRE) Center, VA Iowa City Health Care System (152), Iowa City, IA 52246-2208, USA; Department of Medicine, University of Iowa, Iowa City, IA, USA; Department of Epidemiology, College of Public Health, University of Iowa, Iowa City, IA, USA. Electronic address: david-katz@uiowa.edu. 2. Comprehensive Access & Delivery Research and Evaluation (CADRE) Center, VA Iowa City Health Care System (152), Iowa City, IA 52246-2208, USA. 3. Comprehensive Access & Delivery Research and Evaluation (CADRE) Center, VA Iowa City Health Care System (152), Iowa City, IA 52246-2208, USA; Department of Medicine, University of Iowa, Iowa City, IA, USA; Department of Psychological and Brain Sciences, University of Iowa, Iowa City, IA, USA. 4. VA Nebraska-Western Iowa Health Care System and the Department of Internal Medicine, University of Nebraska Medical Center, Omaha, NE, USA. 5. Ann Arbor Veterans Administration (VA) Healthcare System, University of Michigan, Ann Arbor, MI, USA; Department of Health Management and Policy, University of Michigan, Ann Arbor, MI, USA. 6. Tippie School of Business, University of Iowa, Iowa City, IA, USA.
Abstract
OBJECTIVE: To evaluate US veterans' preferences for smoking cessation counseling and pharmacotherapy. METHODS: A discrete choice experiment (DCE) was conducted in 123 Veterans Health Administration primary care outpatients who planned to quit smoking within 6 months. Key attributes of tobacco cessation treatment were based on literature review and expert opinion. We used a hierarchical Bayesian approach with a logit model to estimate the part-worth utility of each attribute level and used latent class logit models to explore preference heterogeneity. RESULTS: In the aggregate, participants valued counseling options with the following attributes: higher quit rate at 1 year, emphasis on autonomy, familiarity of the counselor, counselor's communication skills, and inclusion of printed materials on smoking cessation. Participants valued pharmacotherapy options with the following attributes: higher quit rate at 1 year, lower risk of physical side effects, zero copayment, monthly check-in calls, and less weight gain. Latent class analysis revealed distinct clusters of patients with a unique preference "phenotype." CONCLUSIONS: Veterans have distinct preferences for attributes of cessation counseling and pharmacotherapy. PRACTICE IMPLICATIONS: Identifying patients' preferences provides an opportunity for clinicians to offer tailored treatment options that better engage veterans in their own care and boost adherence to guideline-recommended counseling and pharmacotherapy. Published by Elsevier B.V.
OBJECTIVE: To evaluate US veterans' preferences for smoking cessation counseling and pharmacotherapy. METHODS: A discrete choice experiment (DCE) was conducted in 123 Veterans Health Administration primary care outpatients who planned to quit smoking within 6 months. Key attributes of tobacco cessation treatment were based on literature review and expert opinion. We used a hierarchical Bayesian approach with a logit model to estimate the part-worth utility of each attribute level and used latent class logit models to explore preference heterogeneity. RESULTS: In the aggregate, participants valued counseling options with the following attributes: higher quit rate at 1 year, emphasis on autonomy, familiarity of the counselor, counselor's communication skills, and inclusion of printed materials on smoking cessation. Participants valued pharmacotherapy options with the following attributes: higher quit rate at 1 year, lower risk of physical side effects, zero copayment, monthly check-in calls, and less weight gain. Latent class analysis revealed distinct clusters of patients with a unique preference "phenotype." CONCLUSIONS: Veterans have distinct preferences for attributes of cessation counseling and pharmacotherapy. PRACTICE IMPLICATIONS: Identifying patients' preferences provides an opportunity for clinicians to offer tailored treatment options that better engage veterans in their own care and boost adherence to guideline-recommended counseling and pharmacotherapy. Published by Elsevier B.V.