The Future of Precision Medicine: Potential Impacts for Health Technology Assessment

James Love-Koh (), Alison Peel, Juan Carlos Rejon-Parrilla, Kate Ennis, Rosemary Lovett, Andrea Manca, Anastasia Chalkidou, Hannah Wood and Matthew Taylor
Additional contact information
James Love-Koh: University of York
Alison Peel: University of York
Juan Carlos Rejon-Parrilla: National Institute for Health and Care Excellence
Kate Ennis: University of York
Rosemary Lovett: National Institute for Health and Care Excellence
Andrea Manca: University of York
Anastasia Chalkidou: Kings Technology Evaluation Centre
Hannah Wood: University of York
Matthew Taylor: University of York

PharmacoEconomics, 2018, vol. 36, issue 12, No 6, 1439-1451

Abstract: Abstract 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.

Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

Downloads: (external link)
http://link.springer.com/10.1007/s40273-018-0686-6 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:pharme:v:36:y:2018:i:12:d:10.1007_s40273-018-0686-6

Ordering information: This journal article can be ordered from
http://www.springer.com/economics/journal/40273

DOI: 10.1007/s40273-018-0686-6

Access Statistics for this article

PharmacoEconomics is currently edited by Timothy Wrightson and Christopher I. Carswell

More articles in PharmacoEconomics from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().