Next Article in Journal
Biomarker-Guided Non-Adaptive Trial Designs in Phase II and Phase III: A Methodological Review
Previous Article in Journal
IDICAP: A Novel Tool for Integrating Drug Intervention Based on Cancer Panel
Article Menu

Export Article

Open AccessConcept Paper
J. Pers. Med. 2016, 6(4), 20; doi:10.3390/jpm6040020

Precision Health Economics and Outcomes Research to Support Precision Medicine: Big Data Meets Patient Heterogeneity on the Road to Value

1
Medical, Pfizer Investment Co. Ltd., Beijing 100010, China
2
Department of Pharmacy, University of Washington, Seattle, WA 98195, USA
3
Elysia Group, LLC, New York, NY 10016, USA
4
IBM Research, Beijing 100010, China
*
Author to whom correspondence should be addressed.
Academic Editor: Stephen B. Liggett
Received: 25 August 2016 / Revised: 22 October 2016 / Accepted: 22 October 2016 / Published: 2 November 2016
View Full-Text   |   Download PDF [694 KB, uploaded 2 November 2016]   |  

Abstract

The “big data” era represents an exciting opportunity to utilize powerful new sources of information to reduce clinical and health economic uncertainty on an individual patient level. In turn, health economic outcomes research (HEOR) practices will need to evolve to accommodate individual patient–level HEOR analyses. We propose the concept of “precision HEOR”, which utilizes a combination of costs and outcomes derived from big data to inform healthcare decision-making that is tailored to highly specific patient clusters or individuals. To explore this concept, we discuss the current and future roles of HEOR in health sector decision-making, big data and predictive analytics, and several key HEOR contexts in which big data and predictive analytics might transform traditional HEOR into precision HEOR. The guidance document addresses issues related to the transition from traditional to precision HEOR practices, the evaluation of patient similarity analysis and its appropriateness for precision HEOR analysis, and future challenges to precision HEOR adoption. Precision HEOR should make precision medicine more realizable by aiding and adapting healthcare resource allocation. The combined hopes for precision medicine and precision HEOR are that individual patients receive the best possible medical care while overall healthcare costs remain manageable or become more cost-efficient. View Full-Text
Keywords: big data; precision health economics; precision medicine big data; precision health economics; precision medicine
Figures

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

Scifeed alert for new publications

Never miss any articles matching your research from any publisher
  • Get alerts for new papers matching your research
  • Find out the new papers from selected authors
  • Updated daily for 49'000+ journals and 6000+ publishers
  • Define your Scifeed now

SciFeed Share & Cite This Article

MDPI and ACS Style

Chen, Y.; Guzauskas, G.F.; Gu, C.; Wang, B.C.M.; Furnback, W.E.; Xie, G.; Dong, P.; Garrison, L.P. Precision Health Economics and Outcomes Research to Support Precision Medicine: Big Data Meets Patient Heterogeneity on the Road to Value. J. Pers. Med. 2016, 6, 20.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
J. Pers. Med. EISSN 2075-4426 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top