Elsevier

Value in Health

Volume 25, Issue 8, August 2022, Pages 1371-1380
Value in Health

Health Policy Analysis
Defining a Core Data Set for the Economic Evaluation of Precision Oncology

https://doi.org/10.1016/j.jval.2022.01.005Get rights and content
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open access

Highlights

  • Current data and evidence are unable to facilitate comprehensive economic evaluations of precision oncology that account for the spectrum of patient-important outcomes and health system impacts.

  • We applied a multistage process to develop a core data set to enable comprehensive economic evaluation of precision oncology.

  • Implementation and uptake of the core data set will enhance the quality of future economic evaluations of precision oncology to provide robust evidence supporting reimbursement decisions.

Abstract

Objectives

Precision oncology is generating vast amounts of multiomic data to improve human health and accelerate research. Existing clinical study designs and attendant data are unable to provide comparative evidence for economic evaluations. This lack of evidence can cause inconsistent and inappropriate reimbursement. Our study defines a core data set to facilitate economic evaluations of precision oncology.

Methods

We conducted a literature review of economic evaluations of next-generation sequencing technologies, a common application of precision oncology, published between 2005 and 2018 and indexed in PubMed (MEDLINE). Based on this review, we developed a preliminary core data set for informal expert feedback. We then used a modified-Delphi approach with individuals involved in implementation and evaluation of precision medicine, including 2 survey rounds followed by a final voting conference to refine the data set.

Results

Two authors determined that variation in published data elements was reached after abstraction of 20 economic evaluations. Expert consultation refined the data set to 83 unique data elements, and a multidisciplinary sample of 46 experts participated in the modified-Delphi process. A total of 68 elements (81%) were selected as required, spanning demographics and clinical characteristics, genomic data, cancer treatment, health and quality of life outcomes, and resource use.

Conclusions

Cost-effectiveness analyses will fail to reflect the real-world impacts of precision oncology without data to accurately characterize patient care trajectories and outcomes. Data collection in accordance with the proposed core data set will promote standardization and enable the generation of decision-grade evidence to inform reimbursement.

Keywords

core data set
economic evaluation
precision medicine
precision oncology

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