Methods for Analysing Patient-Level Utility Data: Insights from the Literature Review and Recent NICE Technology Appraisals.

objectivesThis study examines how patient-level utility data are analysed within NICE Technology Appraisals (TAs) and assesses the extent to which current practice aligns with methodological guidance identified in the published literature. Patient-level utility analysis is critical for estimating health-state utility values used in cost-utility modelling; however, no NICE Technical Support Document currently provides guidance on its appropriate implementation.

methodsThree complementary reviews were undertaken. A landscape review of the published literature identified recommended methods for analysing patient-level utility data. A targeted review was undertaken to supplement the findings of the landscape review. A review of recent NICE TAs assessed how utility data were collected and analysed, including the methods used, and issues raised by External Assessment Groups (EAGs) and NICE Committees.

resultsTwenty studies met inclusion criteria for the literature review, providing recommendations on core analytical methods but limited guidance on addressing complex data features. Targeted literature searches identified 32 studies, and two further seminal papers were added through expert knowledge. They provided recommendations on approaches to handling repeated measures, missing data, model specification and covariate selection. The TA review included 125 appraisals. Although mixed-effects models were the most common analytical approach, substantial heterogeneity in methods remained.

conclusionsWhile some best practices have been adopted in NICE submissions, variation and limited transparency persist in the analysis of patient-level utility data. The three methodological challenges most frequently identified as issues were capturing sub-response treatment benefits, modelling the long-term evolution of utility beyond progression or treatment discontinuation and capturing acute disease or treatment features. They are also among the areas least well covered by existing methodological guidance. The development of best-practice guidance for patient-level utility analysis should therefore prioritise these three areas to support more consistent and robust utility estimation for economic evaluation.