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Computational Technology for Effective Health Care: Immediate Steps and Strategic Directions
on specific clinical applications is likely to result in a premature “freezing” of inefficient workflows and processes and to impede iterative change.
In focusing on the goal to be achieved, namely better and/or less expensive health care, clinicians and other providers will appropriately be drawn to IT only if, where, and when it can be shown to enable them to do their jobs more effectively. Blanket promotion of IT adoption where benefits are not clear or are oversold—especially in a non-infrastructure context—will only waste resources and sour clinicians on the true potential of health care IT.
IT can be a fundamental enabler for both large-scale and small-scale improvement efforts. Because many health care groups have capacities for only a few large-scale improvement methods at a time, small-scale optimization is an important complement. An example of a small-scale optimization would be the use of a guideline alert system that enables individual physicians and/or their clinical teams to continually target areas of practice for self-improvement on guideline-concordant care. But for the most part, the health care IT available in today’s market is not well suited to support small-scale optimization, which requires applications that are rapidly customizable in the field by end users. Federally inspired or supported initiatives that incentivize health care organizations to achieve iterative small-scale optimization and subsequent translation of successes to a larger scale are likely to help stimulate the creation of a new market for these customizable applications.
This analysis leads to six important recommendations for the federal government:
Incentivize clinical performance gains rather than acquisition of IT per se.
Encourage initiatives to empower iterative process improvement and small-scale optimization.
Encourage development of standards and measures of health care IT performance related to cognitive support for health professionals and patients, adaptability to support iterative process improvement, and effective use to improve quality.
Encourage interdisciplinary research in three critical areas: (a) organizational systems-level research into the design of health care systems, processes, and workflow; (b) computable knowledge structures and models for medicine needed to make sense of available patient data including preferences, health behaviors, and so on; and (c) human-computer interaction in a clinical context.
Encourage (or at least do not impede) efforts by health care organizations and communities to aggregate data about health care people,