There is a need for additional research regarding diagnostic image interpretation in clinical decision making. Educational avenues such as procedural shadowing and lengthy training programs have not lowered a presently high diagnostic error rate that exists within the healthcare community. Past research has introduced schematic approaches to act as a universal model of diagnostic reasoning. We apply the Applied Cognitive Task Analysis (ACTA) methodology to establish additional insight on diagnostic imagery analysis, to guide development of training procedures for bone defect detection. Results indicate how a balance of stained color pattern recognition and functional knowledge of histology proved vital to image interpretation when tasked with finding distinct measurements of bone defects within model images.
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