OBJECTIVES

: Growing interest in patient preference studies in drug development highlights the importance of understanding the extent to which such data are used by key decision makers. This study aimed to gain insight into how preference data are included in UK HTA appraisals.

METHODS

: A targeted review of HTA appraisals including preference data was conducted for three UK HTA agencies: The National Institute of Health and Care Excellence (NICE), Scottish Medicines Consortium (SMC) and All Wales Medicines Strategy Group (AWMSG). An a priori defined search strategy identified appraisals that included preference data. Data extraction included source and use of preference data, and agency response.

RESULTS

: The initial search elicited 286 hits: NICE=264, SMC=18, AWMSG=4. Of these, 120 appraisals were eligible. Overall, 43 appraisals published between 2002-2017 included preference data specifically referencing patient/caregiver/clinician treatment preference/choice. Of these, 12 appraisals referenced preference data from patients/patient experts only, 10 from clinicians/clinical experts only, and 19 from both combined (data source unspecified in 2 appraisals). Of the 77 appraisals that used preference data for estimating utilities only, 4 referenced the importance of patient/clinician treatment preferences, although data of this manner were not included. The preference data referenced in the appraisals were collected qualitatively, through existing literature, disease-specific and generic PROs, and preference studies.

CONCLUSIONS

: Preference data are valued by companies and UK HTA agencies in the HTA process, although they cite lack of robust preference study design as a limitation. Quantitative preference methodologies are used principally to elicit utilities for economic modelling, and less commonly to examine treatment preferences or alternative outcomes. Quantitative methods, such as DCEs, could be utilized to provide robust preference evidence from larger samples of patients and clinicians directly thereby complementing qualitative data (e.g. consideration of information from patient experts in HTA decisions) and aiding in the decision-making process for new technologies.