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Some assembly required: tracing the interpretative work of Clinical Competency Committees
Author(s) -
Pack Rachael,
Lingard Lorelei,
Watling Christopher J,
Chahine Saad,
Cristancho Sayra M
Publication year - 2019
Publication title -
medical education
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.776
H-Index - 138
eISSN - 1365-2923
pISSN - 0308-0110
DOI - 10.1111/medu.13884
Subject(s) - tracing , work (physics) , medical education , psychology , engineering ethics , medicine , computer science , engineering , mechanical engineering , operating system
Objectives This qualitative study describes the social processes of evidence interpretation employed by Clinical Competency Committees ( CCC s), explicating how they interpret, grapple with and weigh assessment data. Methods Over 8 months, two researchers observed 10 CCC meetings across four postgraduate programmes at a Canadian medical school, spanning over 25 hours and 100 individual decisions. After each CCC meeting, a semi‐structured interview was conducted with one member. Following constructivist grounded theory methodology, data collection and inductive analysis were conducted iteratively. Results Members of the CCC s held an assumption that they would be presented with high‐quality assessment data that would enable them to make systematic and transparent decisions. This assumption was frequently challenged by the discovery of what we have termed ‘problematic evidence’ (evidence that CCC members struggled to meaningful interpret) within the catalogue of learner data. When CCC s were confronted with ‘problematic evidence’, they engaged in lengthy, effortful discussions aided by contextual data in order to make meaning of the evidence in question. This process of effortful discussion enabled CCC s to arrive at progression decisions that were informed by, rather than ignored, problematic evidence. Conclusions Small groups involved in the review of trainee assessment data should be prepared to encounter evidence that is uncertain, absent, incomplete, or otherwise difficult to interpret, and should openly discuss strategies for addressing these challenges. The answer to the problem of effortful processes of data interpretation and problematic evidence is not as simple as generating more data with strong psychometric properties. Rather, it involves grappling with the discrepancies between our interpretive frameworks and the inescapably subjective nature of assessment data and judgement.