Using Patient Preferences in Health Technology Assessment: Evaluating Quality-Adjusted Survival Equivalents (QASE) for the Quantification of Non-health Benefits.

Interest in using patient preference (PP) data alongside traditional economic models in health technology assessment (HTA) is growing, including using PP data to quantify non-health benefits. However, this is limited by a lack of standardised methods. In this article, we describe a method for using discrete choice experiment (DCE) data to estimate the value of non-health benefits in terms of quality-adjusted survival equivalence (QASE), which is consistent with the concept of value prevalent among HTA agencies.

Treatment preferences of adults and adolescents with alopecia areata: A discrete choice experiment.

PRODUCTS with janus kinase (JAK) inhibition have been shown to promote hair regrowth in patients with alopecia areata (AA). To guide drug-approval and treatment decisions, it is important to understand patients' willingness to accept the potential risks of JAK inhibition in exchange for potential benefits. We quantified the treatment preferences of adult (≥18 years) and adolescent patients (12-17 years) with AA in the US and Europe to determine the trade-offs they are willing to make between benefits and risks.

Multimethod quantitative benefit-risk assessment of treatments for moderate-to-severe osteoarthritis.

Objective: Demonstrate how benefit-risk profiles of systemic treatments for moderate-to-severe osteoarthritis (OA) can be compared using a quantitative approach accounting for patient preference.

Study Design And Setting: This study used a multimethod benefit-risk modelling approach to quantifiably compare treatments of moderate-to-severe OA. In total four treatments and placebo were compared.

An overview of critical decision-points in the medical product lifecycle: Where to include patient preference information in the decision-making process?

Background: Patient preference (PP) information is not effectively integrated in decision-making throughout the medical product lifecycle (MPLC), despite having the potential to improve patients' healthcare options. A first step requires an understanding of existing processes and decision-points to know how to incorporate PP information in order to improve patient-centric decision-making.

Objectives: The aims were to: 1) identify the decision-making processes and decision-points throughout the MPLC for industry, regulatory authorities, and reimbursement/HTA, and 2) determine which decision-points can potentially include PP information.