If we are to achieve the aims of health insurance reform/PPACA, let alone eventual health delivery reform, the US needs coherent, comprehensive federal health IT policy. In late December, PCAST, the President’s Council of Advisors on Science and Technology, issued its perspective on how HITECH has (and hasn’t) moved the needle and where we need to go from here. PCAST is an influential group. It is chaired by Eric Lander, President, Broad Institute of Harvard and MIT and John P. Holdren, Assistant to the President for Science and Technology and Director of the Office of Science and Technology Policy. The council includes heavy hitters from the technology and business worlds including Eric Schmidt, Chairman of Google, Craig Mundie, Chief Research and Strategy Officer of Microsoft, and Christine Cassel, President and CEO of the American Board of Internal Medicine. PCAST’s report, entitled “Realizing the Full Potential of Health Information Technology to Improve Healthcare for Americans: The Path Forward” makes several important additions to the health IT policy conversation, but fails to hit the mark in two critical areas.
On the positive side, we agree with PCAST that IT can contribute to lower costs and higher quality in health care, and that current national HCIT programs, while an enormous improvement over the last forty years of neglect and disincentives, are insufficiently radical to fully realize that value.
We agree that separation of data from applications, liberating the data from the proprietary databases and applications that typically imprison it today is core to unleashing the power of healthcare information (think: free-text patient note vs. reportable and trend-able lab results). Doing so creates value by allowing the right information to be delivered to the right individuals, at the right time, in the right format for the relevant context (e.g. trending of A1c values over time for population health management). Furthermore, freeing data from specific applications would enable greater innovation than is available today and is critical to certain types of data uses such as population-level research, comparative effectiveness research, and biosurveillance.Continue reading…
