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Computational Technology for Effective Health Care: Immediate Steps and Strategic Directions
work is involved. Collaborators from different disciplines must find and maintain common ground, such as agreeing on goals for a joint project, but must also respect one another’s separate priorities, such as having to publish in primary journals, present at particular conferences, or obtain tenure in their respective departments according to departmental criteria. Such cross-pressures and expectations from home departments and disciplinary colleagues remain even if the participants in a collaboration have similar goals for a project. (An example might be the Harvard-MIT program in health sciences and technology.)
Support educational and retraining efforts for computer science researchers who want to explore research opportunities in health care. Such efforts might be offered across a broad front and might span a range in several dimensions, including time and format (e.g., weeks to years; courses, workshops, degree programs, postdoctoral fellowships), content (i.e., different problems within health care), and target audience (i.e., undergraduates to fully tenured faculty).
6.3 HEALTH CARE ORGANIZATIONS
The senior management in health care organizations (including the chief executive officer, chief quality officer, chief medical informatics officer, chief information officer, and chief financial officer) and health care payers have often taken the lead in the deployment of IT for health care and are thus the primary audience to whom the following recommendations are directed.
Organize incentives, roles, workflow, processes, and supporting infrastructure to encourage, support, and respond to opportunities for clinical performance gains. Focus on identifying, prioritizing, and managing changes in process and workflow, and only after doing so support them by technology. Use the context of the organization’s quality improvement strategy to guide and correct IT decisions.
Balance the institution’s IT portfolio among the four domains of automation, connectivity, decision support, and data-mining capabilities.
Develop the necessary data infrastructure for health care improvement byaggregating data regarding people, processes, and outcomes from all sources.
Insist that vendors supply IT that permits the separation of data fromapplications and facilitates data transfers to and from other non-vendor applications in shareable and generally useful formats.
Seek IT solutions that yield incremental gains from incremental efforts. Efforts that make progress in many small steps build support and consensus from the grass roots. One example of such an approach might