Literature DB >> 19472861

Understanding diagnostic reasoning in TCM practice: tongue diagnosis.

Joyce K Anastasi1, Leanne M Currie, Gee H Kim.   

Abstract

BACKGROUND: Traditional Chinese medicine (TCM) diagnosis is a complex multifaceted process that often yields multiple differential diagnoses and subdiagnoses.
OBJECTIVES: The aims of this study were to (1) understand cognitive strategies and diagnostic reasoning processes of TCM practitioners engaged in tongue diagnosis and (2) investigate TCM practitioners' diagnostic accuracy. Clinical decision making and problem solving frameworks served as a basis for this study.
METHODS: Nine TCM practitioners verbalized their thinking processes via think-aloud protocols and were audiotaped while engaged in the cognitive task of tongue diagnosis. Protocol analysis was used to identify TCM diagnostic reasoning patterns. Diagnostic accuracy was assessed by participant self-report and via independent TCM expert judges.
RESULTS: Protocol analysis revealed that TCM practitioners use systematic processes to arrive at diagnoses and that there were differences between novices and experts in both pre- and post-adjustments after viewing case histories. Novices tended to use more descriptors and come to the diagnoses earlier. Experts tended to use higher-level intellectual processes when coming to their diagnoses and tended to use these terms earlier in the process. Correlations between practitioner self-assessment and judges' ratings of diagnostic accuracy were noted and corollary case history information improved diagnostic accuracies.
CONCLUSION: TCM practitioners use systematic reasoning patterns to determine diagnoses associated with evaluation of tongues. These processes are congruent with those observed in Western medicine whereby clinician reasoning involves a combination of analytical reasoning of domain knowledge and the use of exemplar patterns. An explicit understanding of TCM reasoning processes can inform clinical practice and education and will facilitate the development of supporting technologies and identification of best practices.

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Mesh:

Year:  2009        PMID: 19472861

Source DB:  PubMed          Journal:  Altern Ther Health Med        ISSN: 1078-6791            Impact factor:   1.305


  20 in total

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