To illustrate how a collaborative mechanism to develop, synthesize, and disseminate credible information could benefit various stakeholders, consider a hypothetical commercial genetic test proposed for use by health care providers—a panel of genetic markers to aid selection of drug choice and dosing for the management of type 2 diabetes. Currently, this type of test would probably emerge from data amassed by investigator-driven GWAS, then be packaged as a test by a laboratory or pharmaceutical company, and marketed to health care providers and consumers. At the time the test enters the market, minimal evidence might be available to stakeholders regarding the test’s analytic and clinical validity, and it is probable that no clinical utility information would be available. Although the laboratory offering the test may be Clinical Laboratory Improvement Act approved, the test itself may not have undergone Food and Drug Administration (FDA) approval (because this is a laboratory developed test). Unfortunately, the test could reach the market long before research has been conducted to assess the test’s clinical utility, and comparative effectiveness vis-à-vis other existing approaches that do not use genetic testing. The hypothetical diabetes test could thus meet with substantial skepticism by researchers, provider groups, insurers, public health institutions, and policymakers. This would limit its potential for reimbursement, uptake, and, ultimately, public health benefit. On the other hand, consumer interest in the test could also create a supply-demand chain that propels the test into clinical use before adequate evidence has been established.
A collaborative model for facilitating and coordinating the translation of genomic applications into health care and population health could dramatically improve the process for all groups. Returning to the example of the hypothetical diabetes test, one can envision several key functions that a coordinated system for translation might provide. First, all stakeholders could benefit from an unbiased initial assessment of the proposed test. Based on preliminary data, the assessment could define analytic validity, clinical validity, and potential clinical utility of the test to various stakeholders, and identify gaps in the knowledge base required for downstream acceptance and/or reimbursement by the public, care providers, and insurers. This type of early premarket assessment would permit stakeholders to develop priorities for funding, and potentially spur private investment in clinical utility studies required for reimbursement by third party payers. Second, all stakeholders could benefit from an enhanced means for communication among and within groups. A means to align priorities and coordinate translation efforts could substantially reduce duplicative spending and time delay, and create an “evidence match” between the evidence generation process and the priorities of insurers, health care providers, and policy makers. Finally, all stakeholders could benefit from a structured means for coordinating evidence synthesis, dissemination, and educational efforts (for both health care providers and the public) in the immediate premarket and postmarket phase of test development and deployment. Currently, even the most promising applications may not reach a wide audience because of a lack of effective migration of evidence into national health care guidelines and the inefficient application and uptake of those guidelines in the health care sector. Coordination of these activities is critical to realizing the benefit of any new technology and has been recognized as a major stumbling point in the translational continuum.8,9