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Knowledge and the Electronic Health Record. Health Informatics Tends to talk about knowledge in the context of ontologies and guideline formalisms Tends.

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Presentation on theme: "Knowledge and the Electronic Health Record. Health Informatics Tends to talk about knowledge in the context of ontologies and guideline formalisms Tends."— Presentation transcript:

1 Knowledge and the Electronic Health Record

2 Health Informatics Tends to talk about knowledge in the context of ontologies and guideline formalisms Tends to focus on clinician decision support at the time of patient care (diagnostic support, guideline support) –See www.openclinical.orgwww.openclinical.org Remarkably unsuccesful

3 Knowledge management Learning Negotiation

4 Learning Meta-cognition Experience Individuality Culture –Professional –Sociological

5 Negotiation Knowledge exchange –Team, inter-professional,organisational inter-dependence Contextual Priorities –Agendas Choice Decisions –Iteration, decision inter-dependence

6 Domains of Knowledge and Patient Care Clinical knowledge –Disease evolution –Diagnosis, treatment, outcome Contributing knowledge –Physiology, engineering, etc Organisational knowledge –Work flow, planning

7 Why distinguish domains of knowledge Natural knowledge growth –Recognised specialisation, specific journals Knowledge closest to main decision making needs Knowledge domains have their own characteristics and dynamic Articulates where knowledge can be shared between domains

8 Knowledge representation of the clinical domain Syntax Semantics

9 Syntax

10 ENV13606 a practical generic EHCR Standard Are types of 1 contains 1..* Are types of 1..* EHCR original component complex record component link item data item folder composition headed section cluster Various specialised types of data item

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14 Semantic Care strategies –According to clinical problem(s) –Diagnosis – therapy – outcome –Problem definition, risk analysis, treatment selection

15 2 papers comparison of guideline formalisms Approaches for creating computer-interpretable guidelines that facilitate decision support –Paul A. de Clercq, Johannes A. Blomb, Hendrikus H.M. Korsten, Arie Hasmana –Artificial Intelligence in Medicine (2004) 31, 1—27 Comparing Computer-interpretable Guideline Models:A Case- study Approach –MOR PELEG, PHD, SAMSON TU, MS, JONATHAN BURY, MBCHB,PAOLO CICCARESE, MSC, JOHN FOX, PHD, ROBERT A. GREENES, MD, PHD, RICHARD HALL, MSC, PETER D. JOHNSON, MBBS, NEILL JONES, MBBS,, ANAND KUMAR, MBBS, SILVIA MIKSCH, PHD, SILVANA QUAGLINI, PHD, ANDREAS SEYFANG, MSC, EDWARD H. SHORTLIFFE, MD, PHD,MARIO STEFANELLI, PHD –J Am Med Inform Assoc. 2003;10:52–68

16 Computer based clinical guidelines Redundancy and overlap Little standardisation to facilitate sharing

17 Formalisms reviewed by De Clercq et al The Arden Syntax GLIF –Guideline interchange format PROforma Asbru EON

18 Critique of Guideline formalisms and current application aims Do not adequately address guideline root knowledge –Tend to relate to existing guidelines and their current inherent variation rather than guideline knowledge sources Do not well take into account different characteristics of different domain knowledge –Clinical versus organisational Do not take into account basic requirements of knowledge management –Contextual learning and decision making


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