Computational Technology for Effective Health Care Immediate Steps and Strategic Directions (2009) / Chapter Skim
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Summary
Pages 1-12
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to acquire, manage, analyze, and disseminate health care information and knowledge. Many studies have identified deficiencies in the current health care system, including inadequate care, superfluous or incorrect care, immense inefficiencies and hence high costs, and inequities in access to care.
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These multiple sources of evidence -- viewed from the committee's perspective -- suggest that current efforts aimed at the nationwide deployment of health care IT will not be sufficient to achieve the vision of 21st century health care, and may even set back the cause if these efforts continue wholly without change from their present course. Specifically, success in this regard will require greater emphasis on providing cognitive support for health care providers and for patients and family caregivers on the part of computer science and health/biomedical informatics researchers.
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These persistent problems do not reflect incompetence on the part of health care professionals -- rather, they are a consequence of the inherent intellectual complexity of health care taken as a whole and a medical care environment that has not been adequately structured to help clinicians avoid mistakes or to systematically improve their decision making and practice. Administrative and organizational fragmentation, together with complex, distributed, and unclear authority and responsibility, further complicates the health care environment.
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As a result, health care processes will become more complex and more time-constrained, and the demands placed on care providers will become more intense. A Vision for 21st Century Health Care and Wellness The IOM defines health care quality as "the degree to which health services for individuals and populations increase the likelihood of desired health outcomes and are consistent with current professional knowledge," and in recent years, a broad consensus has emerged on the future health care environment.
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Care providers spent a great deal of time in electronically documenting what they did for patients, but these providers often said that they were entering the information to comply with regulations or to defend against lawsuits, rather than because they expected someone to use it to improve clinical care. Health care IT implementation time lines were often measured in decades, and most systems were poorly or incompletely integrated into practice. Although the use of health care IT is an integral element of health care in the 21st century, the current focus of the health care IT efforts that the committee observed is not sufficient to drive the kind of change in health care that is truly needed.
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Any approach to health care IT should enable and anticipate both types of change since they work together over time. The committee identified five principles related to evolutionary change and four related to radical change to guide successful use of health care IT to support a 21st century vision of health care.
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During the committee's discussions, patient-centered cognitive support emerged as an overarching grand research challenge to focus healthrelated efforts of the computer science research community, which can play an important role in helping to cross the health care IT chasm. An Overarching Research Grand Challenge: Patient-Centered Cognitive Support Much of health care is transactional -- admitting a patient, encountering a patient at the bedside or clinic, ordering a drug, interpreting a report, or handing off a patient.
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The use of these models to establish clinical context would free the clinician from having to make direct sense of raw data, and thus he or she would have a much easier time defining, testing, and exploring his/her own working theory. What links the raw data to the abstract models might be called medical logic -- that is, computer-based tools that examine raw data relevant to a specific patient and suggest their clinical implications given the context of the models and abstractions.
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In addition to the research challenges related to modeling the virtual patient and biomedical knowledge, there are challenges in modeling and supporting multiplayer decision making (e.g., involving family, patient, primary care provider, specialist, payer, and so on)
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Research challenges in this area involve data integration systems that are fundamentally easier to use, data integration methodologies that can proceed incrementally while remaining compatible with previous versions, and more flexible architectures for data sharing and integration. • Data management at scale.
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• 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)
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• Develop institutional mechanisms within academia for rewarding work at the health care/computer science interface. • Support educational and retraining efforts for computer science researchers who want to explore research opportunities in health care.
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