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Computational Technology for Effective Health Care: Immediate Steps and Strategic Directions
will require greater emphasis on the goal of improving health care by providing cognitive support for health care providers and even for patients and family caregivers on the part of computer science and health/biomedical informatics researchers. Vendors, health care organizations, and government, too, will also have to pay greater attention to cognitive support. This point is the central conclusion articulated in this report.
So that the nation can cross the health care IT chasm, the committee advocates re-balancing the portfolio of investments in health care IT; adhering to proven principles for success; and accelerating research in computer science, social sciences, and health/biomedical informatics (and concomitant education about each field for practitioners in the others).
Motivated by a presentation from Intermountain Healthcare’s Marc Probst, the committee found it useful to categorize health care IT into four domains: automation, connectivity, decision support, and data-mining capabilities. See Box 3.1.
The majority of today’s health care IT is designed to support automation, with some investment in supporting connectivity, and little in support of data mining or decision support. Yet the IOM’s vision for 21st century health care expects health care IT that is capable of supporting cognitive activities and a learning health care system. These activities are much more about connectivity, decision support, and data mining than they are about automation. The health care IT investment portfolio must be re-balanced to address this mismatch.