Abstract
BackgroundThe inclusion of patient preferences (PP) in the medical product life cycle is a topic of growing interest to stakeholders such as academics, Health Technology Assessment (HTA) bodies, reimbursement agencies, industry, patients, physicians and regulators. This review aimed to understand the potential roles, reasons for using PP and the expectations, concerns and requirements associated with PP in industry processes, regulatory benefit-risk assessment (BRA) and marketing authorization (MA), and HTA and reimbursement decision-making.MethodsA systematic review of peer-reviewed and grey literature published between January 2011 and March 2018 was performed. Consulted databases were EconLit, Embase, Guidelines International Network, PsycINFO and PubMed. A two-step strategy was used to select literature. Literature was analyzed using NVivo (QSR international).ResultsFrom 1015 initially identified documents, 72 were included. Most were written from an academic perspective (61%) and focused on PP in BRA/MA and/or HTA/reimbursement (73%). Using PP to improve understanding of patients’ valuations of treatment outcomes, patients’ benefit-risk trade-offs and preference heterogeneity were roles identified in all three decision-making contexts. Reasons for using PP relate to the unique insights and position of patients and the positive effect of including PP on the quality of the decision-making process. Concerns shared across decision-making contexts included methodological questions concerning the validity, reliability and cognitive burden of preference methods. In order to use PP, general, operational and quality requirements were identified, including recognition of the importance of PP and ensuring patient understanding in PP studies.ConclusionsDespite the array of opportunities and added value of using PP throughout the different steps of the MPLC identified in this review, their inclusion in decision-making is hampered by methodological challenges and lack of specific guidance on how to tackle these challenges when undertaking PP studies. To support the development of such guidance, more best practice PP studies and PP studies investigating the methodological issues identified in this review are critically needed.
Highlights
The inclusion of patient preferences (PP) in the medical product life cycle is a topic of growing interest to stakeholders such as academics, Health Technology Assessment (HTA) bodies, reimbursement agencies, industry, patients, physicians and regulators
No unique definition exists for PP across research fields and disciplines [17,18,19,20], the Food and Drug Administration (FDA) refers to PP by defining patient preference information as “qualitative or quantitative assessments of the relative desirability or acceptability to patients of specified alternatives or choices among outcomes or other attributes1 that differ among alternative health interventions” [14]
Review questions and search strategy The review was guided by the following review questions, pertaining both to the preference method itself and the application of PP to decision-making: i) what roles do PP have to play in the Medical product life cycle (MPLC) and what are reasons to use them?, ii) what is expected to happen when PP are used in the MPLC?, iii) what concerns arise for the use of PP in the MPLC? and iv) what is needed in order to use PP in the MPLC?
Summary
The inclusion of patient preferences (PP) in the medical product life cycle is a topic of growing interest to stakeholders such as academics, Health Technology Assessment (HTA) bodies, reimbursement agencies, industry, patients, physicians and regulators. The patient's perspective is considered essential on all levels of decision-making throughout the lifecycle of drugs and medical devices (i.e. the medical product life cycle (MPLC)) [1, 2]. This is demonstrated by a growth of literature on the roles of patients’ perspectives in drug and medical device development [3,4,5], regulatory benefit-risk assessment (BRA), Health Technology Assessment (HTA) [6,7,8,9] and clinical practice guideline development [10, 11]. While qualitative methods (e.g. interviews) generate information about patient experiences and perspectives, quantitative methods (e.g. discrete choice experiments) collect numerical data [21]
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