Quantifying the importance of inhaler attributes corresponding to items in the patient satisfaction and preference questionnaire in patients using Combivent Respimat.

Abstract

BACKGROUND: Physicians consider ease of use, satisfaction, and preferences when prescribing an inhaler device. These factors may impact appropriate usage and compliance. METHODS: The objectives were to quantify the relative importance of inhaler attributes in patients currently using Combivent Respimat by eliciting preferences for performance and convenience attributes assessed by items in the Patient Satisfaction and Preference Questionnaire (PASAPQ). Using a pharmacy database, 19,964 adults in the United States who filled ≥2 Combivent Respimat prescriptions were identified. Of those, 8150 patients were randomly selected to receive invitation letters. The online cross-sectional survey included the PASAPQ and best-worst scaling (BWS) questions. The PASAPQ measures satisfaction with medication attributes across two domains: performance and convenience. BWS questions asked participants to select the most and least important device attributes. A descriptive statistics analysis of the PASAPQ and a random-parameters logit model of BWS responses were conducted. RESULTS: The survey was completed by 503 participants. Most were female (57.3%), white (88.5%), and 51-70 years old (67.6%). Approximately 47% reported a chronic obstructive pulmonary disease diagnosis, 21.9% asthma, 8.2% other lung disease, and 23.1% more than one lung disease. PASAPQ scores indicated that the majority were satisfied or very satisfied; up to 20% reported being dissatisfied with Combivent Respimat. The three most important inhaler attributes were Feeling that your medicine gets into your lungs, Inhaler works reliably, and Inhaler makes inhaling your medicine easy. The most important attributes corresponded to six of seven items in the PASAPQ performance domain. CONCLUSIONS: Most participants reported satisfaction with Combivent Respimat. Performance attributes were more important than convenience attributes.

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Published Version (Please cite this version)

10.1186/s12955-017-0780-z

Publication Info

Davis, Kimberly H, Jun Su, Juan Marcos González, Jeremiah J Trudeau, Lauren M Nelson, Brett Hauber and Kelly A Hollis (2017). Quantifying the importance of inhaler attributes corresponding to items in the patient satisfaction and preference questionnaire in patients using Combivent Respimat. Health Qual Life Outcomes, 15(1). p. 201. 10.1186/s12955-017-0780-z Retrieved from https://hdl.handle.net/10161/15760.

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Gonzalez

Juan Marcos Gonzalez

Associate Professor in Population Health Sciences

Dr. Gonzalez is an Associate Professor in the Department of Population Health Sciences. He is an expert in the design of stated-preference survey instruments and the use of advanced statistical tools to analyze stated-preference data. His research has focused on the transparency in benefit-risk evaluations of medical interventions, and the elicitation of health preferences from multiple stakeholders to support shared decision making.

Dr. Gonzalez co-led the first FDA-sponsored preference study which was highlighted in FDA’s recent precedent-setting guidance for submitting patient-preference evidence to inform regulatory benefit-risk evaluations of new medical devices. More recently, Dr. Gonzalez collaborated with the Medical Devices Innovation Consortium (MDIC) to prepare the first catalog of preference-elicitation methods (part of the Patient-Centered Benefit-Risk Assessment Framework) suitable for benefit-risk assessments of medical devices. As a core group member of the International Society for Pharmacoeconomics and Outcomes Research (ISPOR) Conjoint Analysis Task Force, Dr. Gonzalez helped draft good-practice recommendations for statistical analysis, interpretation, and reporting of health preference data. Currently, he is working with the Center for Devices and Radiological Health at FDA to support the Center’s capabilities for the review of stated-preference data in regulatory decisions.

Areas of expertise: Clinical Decision Sciences and Health Measurement

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