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Tuesday, 1st February 2011

Enabling Personalized Medicine through Health Information Technology: Advancing the Integration of Information

Enabling Personalized Medicine through Health Information Technology: Advancing the Integration of Information

Source:  Brookings Institution

With federal officials pursuing the goal of a personal human genome map under $1,000 in five years (White House, 2010), it is possible to envision a future where treatments are tailored to individuals’ genetic structures, prescriptions are analyzed in advance for likely effectiveness, and researchers study clinical data in real-time to learn what works. Implementation of these regimens creates a situation where treatments are better targeted, health systems save money by identifying therapies not likely to be effective for particular people, and researchers have a better understanding of comparative effectiveness (President’s Council of Advisors on Science and Technology, 2010).

Yet despite these benefits, consumer and system-wide gains remain limited by an outmoded policy regime.  Federal regulations were developed years before recent advances in gene sequencing, electronic health records, and information technology.  With scientific innovation running far ahead of public policy, physicians, researchers, and patients are not receiving the full advantage of latest developments.  Current policies should leverage new advances in genomics and personalized medicine in order to individualize diagnosis and treatment.  Similarly, policies creating incentives for the adoption of health information technology should ensure that the invested infrastructure is one that supports new-care paradigms as opposed to automating yesterday’s health care practices.

To determine what needs to be done, a number of key leaders from government, academia, non-profit organizations, and business were interviewed about ways to promote a better use of health information technology to enable personalized medicine.  The interviews focused on policy and operational issues surrounding interoperability, standards, data sharing protocols, privacy, predictive modeling, and rapid learning feedback models.

This paper outlines the challenges of enabling personalized medicine, as well as the policy and operational changes that would facilitate connectivity, integration, reimbursement reform, and analysis of information.   Our health system requires a seamless and rapid flow of digital information, including genomic, clinical outcome, and claims data.  Research derived from clinical care must feed back into assessment in order to advance care quality for consumers.  There currently are discrete data on diagnosis, treatment, medical claims, and health outcomes that exist in parts of the system, but it is hard to determine what works and how treatments differ across subgroups.  Changes in reimbursement practices would better align incentives with effective health care practices. 

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