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Bridging the Gaps in Personalized Medicine Value Assessment: A Review of the Need for Outcome Metrics across Stakeholders and Scientific Disciplines
Author(s) -
William S. Bush,
Jessica N. Cooke Bailey,
Mark Beno,
Dana C. Crawford
Publication year - 2019
Publication title -
public health genomics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.701
H-Index - 51
eISSN - 1662-8063
pISSN - 1662-4246
DOI - 10.1159/000501974
Subject(s) - health care , personalized medicine , precision medicine , stakeholder , blueprint , value (mathematics) , population , population health , workflow , medicine , data science , computer science , bioinformatics , public relations , political science , engineering , mechanical engineering , environmental health , pathology , machine learning , law , biology , database
Despite monumental advances in genomics, relatively few health care provider organizations in the United States offer personalized or precision medicine as part of the routine clinical workflow. The gaps between research and applied genomic medicine may be a result of a cultural gap across various stakeholders representing scientists, clinicians, patients, policy makers, and third party payers. Scientists are trained to assess the health care value of genomics by either quantifying population-scale effects, or through the narrow lens of clinical trials where the standard of care is compared with the predictive power of a single or handful of genetic variants. While these metrics are an essential first step in assessing and documenting the clinical utility of genomics, they are rarely followed up with other assessments of health care value that are critical to stakeholders who use different measures to define value. The limited value assessment in both the research and implementation science of precision medicine is likely due to necessary logistical constraints of these teams; engaging bioethicists, health care economists, and individual patient belief systems is incredibly daunting for geneticists and informaticians conducting research. In this narrative review, we concisely describe several definitions of value through various stakeholder viewpoints. We highlight the existing gaps that prevent clinical translation of scientific findings generally as well as more specifically using two present-day, extreme scenarios: (1) genetically guided warfarin dosing representing a handful of genetic markers and more than 10 years of basic and translational research, and (2) next-generation sequencing representing genome-dense data lacking substantial evidence for implementation. These contemporary scenarios highlight the need for various stakeholders to broadly adopt frameworks designed to define and collect multiple value measures across different disciplines to ultimately impact more universal acceptance of and reimbursement for genomic medicine.

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