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Patients’ preferences in periodontal disease treatment elicited alongside an IQWiG benefit assessment: a feasibility study

BACKGROUND AND PURPOSE: The German Institute for Quality and Efficiency in Health Care (IQWiG) previously tested two preference elicitation methods in pilot projects and regarded them as generally feasible for prioritizing outcome-specific results of benefit assessment. The present study aimed to in...

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Detalles Bibliográficos
Autores principales: Vennedey, Vera, Derman, Sonja HM, Hiligsmann, Mickaël, Civello, Daniele, Schwalm, Anja, Seidl, Astrid, Scheibler, Fülöp, Stock, Stephanie, Noack, Michael J, Danner, Marion
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Dove Medical Press 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6248230/
https://www.ncbi.nlm.nih.gov/pubmed/30510407
http://dx.doi.org/10.2147/PPA.S176067
Descripción
Sumario:BACKGROUND AND PURPOSE: The German Institute for Quality and Efficiency in Health Care (IQWiG) previously tested two preference elicitation methods in pilot projects and regarded them as generally feasible for prioritizing outcome-specific results of benefit assessment. The present study aimed to investigate the feasibility of completing a discrete choice experiment (DCE) within 3 months and to determine the relative importance of attributes of periodontal disease and its treatment. PATIENTS AND METHODS: This preference elicitation was conducted alongside the IQWiG benefit assessment of systematic treatments of periodontal diseases. Attributes were defined based on the benefit assessment, literature review, and patients’ and periodontologists’ interviews. The DCE survey was completed by patients with a history of periodontal disease. Preferences were elicited for the attributes “tooth loss within next 10 years”, “own costs for treatment, follow-up visits, re-treatment”, “complaints and symptoms”, and “frequency of follow-up visits”. Patients completed a self-administered questionnaire including 12 choice tasks. Data were analyzed using a random parameters logit model. The relative attribute importance was calculated based on level ranges. RESULTS: Within 3 months, survey development, data collection among 267 patients, data analysis, and provision of a study report could be completed. The analysis showed that tooth loss (score 0.73) was the most important attribute in patients’ decisions, followed by complaints and symptoms (0.22), frequency of follow-up visits (0.02), and costs (0.03) (relative importance scores summing up to 1). CONCLUSION: A preference analysis performing a DCE can be generally feasible within 3 months; however, a good research infrastructure and access to patients is required. Outcomes used in benefit assessments might need to be adapted to be used in preference analyses.