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Background: Health inequalities can be partially addressed through the range of treatments funded by health systems. Nevertheless, although health technology assessment agencies assess the overall balance of health benefits and costs, no quantitative assessment of health inequality impact is consistently undertaken., Objectives: To assess the inequality impact of technologies recommended under the NICE single technology appraisal process from 2012 to 2014 using an aggregate distributional cost-effectiveness framework., Methods: Data on health benefits, costs, and patient populations were extracted from the NICE website. Benefits for each technology were distributed to social groups using the observed socioeconomic distribution of hospital utilization for the targeted disease. Inequality measures and estimates of cost-effectiveness were compared using the health inequality impact plane and combined using social welfare indices., Results: Twenty-seven interventions were evaluated. Fourteen interventions were estimated to increase population health and reduce health inequality, 8 to reduce population health and increase health inequality, and 5 to increase health and increase health inequality. Among the latter 5, social welfare analysis, using inequality aversion parameters reflecting high concern for inequality, indicated that the health gain outweighs the negative health inequality impact., Conclusions: The methods proposed offer a way of estimating the health inequality impacts of new health technologies. The methods do not allow for differences in technology-specific utilization and health benefits, but require less resources and data than conducting full distributional cost-effectiveness analysis. They can provide useful quantitative information to help policy makers consider how far new technologies are likely to reduce or increase health inequalities., (Copyright © 2019 ISPOR–The Professional Society for Health Economics and Outcomes Research. Published by Elsevier Inc. All rights reserved.)

Objective: Precision medicine allows healthcare interventions to be tailored to groups of patients based on their disease susceptibility, diagnostic or prognostic information, or treatment response. We analysed what developments are expected in precision medicine over the next decade and considered the implications for health technology assessment (HTA) agencies., Methods: We performed a pragmatic literature search to account for the large size and wide scope of the precision medicine literature. We refined and enriched these results with a series of expert interviews up to 1 h in length, including representatives from HTA agencies, research councils and researchers designed to cover a wide spectrum of precision medicine applications and research., Results: We identified 31 relevant papers and interviewed 13 experts. We found that three types of precision medicine are expected to emerge in clinical practice: complex algorithms, digital health applications and 'omics'-based tests. These are expected to impact upon each stage of the HTA process, from scoping and modelling through to decision-making and review. The complex and uncertain treatment pathways associated with patient stratification and fast-paced technological innovation are central to these effects., Discussion: Innovation in precision medicine promises substantial benefits but will change the way in which some health services are delivered and evaluated. The shelf life of guidance may decrease, structural uncertainty may increase and new equity considerations will emerge. As biomarker discovery accelerates and artificial intelligence-based technologies emerge, refinements to the methods and processes of evidence assessments will help to adapt and maintain the objective of investing in healthcare that is value for money.