Literature DB >> 3331579

Knowledge coupling, medical education and patient care.

L L Weed1.   

Abstract

Medical education and the acquisition of professional credentials do not guarantee that medical knowledge (information that is taught, apart from the reality of practice, or gleaned from the literature) will be coupled rigorously to the decision-making process of everyday clinical practice. The limitations of the unaided human mind in a memory-based educational system must be forthrightly acknowledged by those who would be responsible for curriculum reform, so the need for new premises and new tools will be recognized and implemented. Because of their knowledge of the many variables that are unique to them, the patients themselves must be given a much more central role in the process of medical care and medical education. Weaknesses of specialization and credentialing in the present obsolete system are analyzed. The behavior of a well-defined system of education and medical care, and the function of the performers within it, are described. Causes of resistance to curricular reform founded on new premises and use of new tools, such as computers, are considered. New computer tools, as components of a problem-solving decision support system (knowledge couplers, knowledge networks, the coupler editor and documentation system, and the computerized patient record), are described. How these might be incorporated into a new type of medical education curriculum is presented. Finally, new goals, within the context of the new premises being implemented into a new system of education and medical care, are outlined.

Entities:  

Mesh:

Year:  1986        PMID: 3331579

Source DB:  PubMed          Journal:  Crit Rev Med Inform        ISSN: 0882-0503


  4 in total

1.  Informatics Workup.

Authors:  F Naeymi-Rad; D Trace; K Shoults; J Suico; M O'Brien; M Evens; L Carmony; R Roberts; R Zelanski
Journal:  Proc Annu Symp Comput Appl Med Care       Date:  1992

2.  The Problem Knowledge Couplertrade mark as an Information Management and Information Processing Tool.

Authors:  P A Bushby
Journal:  Can Vet J       Date:  1988-03       Impact factor: 1.008

3.  A method and knowledge base for automated inference of patient problems from structured data in an electronic medical record.

Authors:  Adam Wright; Justine Pang; Joshua C Feblowitz; Francine L Maloney; Allison R Wilcox; Harley Z Ramelson; Louise I Schneider; David W Bates
Journal:  J Am Med Inform Assoc       Date:  2011-05-25       Impact factor: 4.497

4.  Technology, cognition and error.

Authors:  Enrico Coiera
Journal:  BMJ Qual Saf       Date:  2015-07       Impact factor: 7.035

  4 in total

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