EMR Strategy

I was sent this 119 page pre-publication report on EMR strategies.  Below are some elements I found to be important:

• Computer science as a discipline does not subsume health/biomedical informatics, although computer scientists can and do make major contributions to that field.  Health/biomedical informatics is more than medical computer science, drawing also on the decision, cognitive, and information sciences as well as engineering, organizational theory, and sociology with a health and biomedical emphasis that is largely lacking in the world of computer science research.

• Specialists in health/biomedical informatics can serve a bridging function between the computer science community and the world of biomedicine with which computer science researchers are largely unfamiliar

• In the future, health care providers will need to rely increasingly on information technology (IT) to acquire, manage, analyze, and disseminate health care information and knowledge.

• Any systematic effort to change the medical and health information management paradigm from one based on paper to one based on IT must address two basic challenges:

• using the best technology available today to build and deploy systems in the short term and

• identifying the gaps between the best of today’s technology and what is ultimately needed to improve health care.

Principles for Evolutionary Change

1. Focus on improvements in care —technology is secondary.
2. Seek incremental gain from incremental effort.
3. Record available data so that today’s biomedical knowledge can be used to interpret the data to drive care, process improvement, and research.
4. Design for human and organizational factors so that social and institutional processes will not pose barriers to appropriately taking advantage of technology.
5. Support the cognitive functions of all caregivers, including health professionals, patients, and their families.

Principles for Radical Change

1. Architect information and workflow systems to accommodate disruptive change.
2. Archive data for subsequent re-interpretation, that is, in anticipation of future advances in biomedical knowledge that may change today’s interpretation of data and advances in computer science that may provide new ways of extracting meaningful and useful knowledge from existing data stores.
3. Seek and develop technologies that identify and eliminate ineffective work processes.
4. Seek and develop technologies that clarify the context of data.

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 institutions and communities to aggregate data about health care people, processes, and outcomes from all sources subject to appropriate protection of privacy and confidentiality.
  

• Support additional education and training efforts at the intersection of health care, computer science, and health/biomedical informatics. Current programs of the National Library of Medicine and other institutes of the National Institutes of Health are exemplars of such support.

The senior management in health care institutions and health care payers have often taken the lead in the deployment of IT for health care. They should:

• Organize incentives, roles, workflow, processes, and supporting infrastructure
  to encourage, support, and respond to opportunities for clinical performance
  gains.
• Balance the institution’s IT portfolio among automation, connectivity, decision
  support, and data-mining capabilities.
• Develop the necessary data infrastructure for health care improvement by
  aggregating data regarding people, processes, and outcomes from all sources.
• Insist that vendors supply IT that permits the separation of data from
  applications and facilitates data transfers to and from other non-vendor
  applications in sharable and generally useful formats.
• Seek IT solutions that yield incremental gains from incremental efforts.

 

Let me know what you think of this report!

Thanks!
Andrew

Computational Technology for Effective Health
Care: Immediate Steps and Strategic Directions
Willam W. Stead and Herbert S. Lin, editors;
Committee on Engaging the Computer Science Research
Community in Health Care Informatics;
National Research Council

This free PDF was downloaded from:
http://www.nap.edu/catalog/12572.html