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Diagnosis Degree of concurrency among experts in data collection and diagnostic hypothesis generation during clinical encounters.

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Title: Diagnosis Degree of concurrency among experts in data collection and diagnostic hypothesis generation during clinical encounters.
Authors: Nendaz, Mathieu R (AUTHOR), Gut, Anne M (AUTHOR), Perrier, Arnaud (AUTHOR), Reuille, Olivier (AUTHOR), Louis‐Simonet, Martine (AUTHOR), Junod, Alain F (AUTHOR), Vu, Nu V (AUTHOR)
Source: Medical Education. Jan2004, Vol. 38 Issue 1, p25-31. 7p.
Subjects: Medical education, Education, Research, Medicine, Patients
Abstract: Given that there are variations in clinicians' reasoning, methods to elaborate scoring checklists for standardised patient-based assessment need to be valid. The use of data elicited by experts solving problems independently has been advocated as a method of setting performance standards. To determine the degree of concurrence and common characteristics among items independently elicited by doctors during patient encounters and to assess the number of experts needed to derive reliable performance standards. Six experienced internists worked-up the same 7 chief complaints with standardised patients (SPs). A stimulated recall of the recorded encounter was then performed. The degree of concurrence of the collected history and physical examination information and the generated diagnostic hypotheses was computed. Reliability was derived from generalisability analyses. By case, experts elicited a mean of 114 information items (SD = 15) and generated 30 diagnostic hypotheses (SD = 6). A high concurrence (80–100%) was observed for a mean of 22 information items (20%; SD = 6) and 7 diagnostic hypotheses (24%; SD = 2). More than a third of the 153 highly concurrent information items were clarification questions. At least 3 doctors were needed to obtain a reliability of 0.80 or higher when deriving the scoring checklists. The limited concurrency in data elicited by clinicians during a patient encounter supports the use of high-fidelity methods to develop performance checklists used in SP-based assessment. It also suggests that relying only on information collected to assess clinical competence may not be sufficient. Additional criteria, such as structure and style of work-up, should be further explored. [ABSTRACT FROM AUTHOR]
Copyright of Medical Education is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Psychology and Behavioral Sciences Collection
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  Data: Diagnosis Degree of concurrency among experts in data collection and diagnostic hypothesis generation during clinical encounters.
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  Data: Given that there are variations in clinicians' reasoning, methods to elaborate scoring checklists for standardised patient-based assessment need to be valid. The use of data elicited by experts solving problems independently has been advocated as a method of setting performance standards. To determine the degree of concurrence and common characteristics among items independently elicited by doctors during patient encounters and to assess the number of experts needed to derive reliable performance standards. Six experienced internists worked-up the same 7 chief complaints with standardised patients (SPs). A stimulated recall of the recorded encounter was then performed. The degree of concurrence of the collected history and physical examination information and the generated diagnostic hypotheses was computed. Reliability was derived from generalisability analyses. By case, experts elicited a mean of 114 information items (SD = 15) and generated 30 diagnostic hypotheses (SD = 6). A high concurrence (80–100%) was observed for a mean of 22 information items (20%; SD = 6) and 7 diagnostic hypotheses (24%; SD = 2). More than a third of the 153 highly concurrent information items were clarification questions. At least 3 doctors were needed to obtain a reliability of 0.80 or higher when deriving the scoring checklists. The limited concurrency in data elicited by clinicians during a patient encounter supports the use of high-fidelity methods to develop performance checklists used in SP-based assessment. It also suggests that relying only on information collected to assess clinical competence may not be sufficient. Additional criteria, such as structure and style of work-up, should be further explored. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Medical Education is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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