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• W2024400239 abstract "With continuing efforts to reduce medical reimbursements, many radiology service providers have reacted by increasing productivity to maintain revenue. This continuing push to increase speed carries the risk for diminished quality in the form of diagnostic accuracy. Data mining offers the potential to synergistically improve both productivity and quality, through the combined analysis of examination complexity, interpretation accuracy, and interpretation times specific to each individual radiologist. The resulting technology can in turn be used to create external pacers, which can be customized to the individual needs and preferences of each radiologist. The derived data can also be used to identify best-practice patterns and end-user performance, which can in turn be used by radiologists for individualized education and training. With continuing efforts to reduce medical reimbursements, many radiology service providers have reacted by increasing productivity to maintain revenue. This continuing push to increase speed carries the risk for diminished quality in the form of diagnostic accuracy. Data mining offers the potential to synergistically improve both productivity and quality, through the combined analysis of examination complexity, interpretation accuracy, and interpretation times specific to each individual radiologist. The resulting technology can in turn be used to create external pacers, which can be customized to the individual needs and preferences of each radiologist. The derived data can also be used to identify best-practice patterns and end-user performance, which can in turn be used by radiologists for individualized education and training." @default.
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• W2024400239 date "2011-01-01" @default.
• W2024400239 modified "2023-09-27" @default.
• W2024400239 title "New Strategies for Medical Data Mining, Part 2: The Customizable Productivity Pacer" @default.
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• W2024400239 doi "https://doi.org/10.1016/j.jacr.2010.06.018" @default.
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