Toward Data-Driven Radiology Education-Early Experience Building Multi-Institutional Academic Trainee Interpretation Log Database (MATILDA)
| Autor: | Marc D. Kohli, Po-Hao Chen, Andrew B. Lemmon, Aaron P. Kamer, Thomas W. Loehfelm, Tessa S. Cook |
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| Rok vydání: | 2016 |
| Předmět: |
medicine.medical_specialty
Analytics Databases Factual Computer science Case log Big data education Clinical Sciences Graduate medical education computer.software_genre Article 030218 nuclear medicine & medical imaging Data-driven Accreditation Education Database 03 medical and health sciences Databases 0302 clinical medicine Schema (psychology) medicine Humans Radiology Nuclear Medicine and imaging Factual Radiological and Ultrasound Technology business.industry Internship and Residency Radiology training Data science United States Residency Computer Science Applications Centralized database Nuclear Medicine & Medical Imaging Radiology Information Systems Networking and Information Technology R&D (NITRD) 030220 oncology & carcinogenesis Informatics ACGME Biomedical Imaging Radiology business computer Program Evaluation |
| Zdroj: | Journal of digital imaging, vol 29, iss 6 |
| Popis: | The residency review committee of the Accreditation Council of Graduate Medical Education (ACGME) collects data on resident exam volume and sets minimum requirements. However, this data is not made readily available, and the ACGME does not share their tools or methodology. It is therefore difficult to assess the integrity of the data and determine if it truly reflects relevant aspects of the resident experience. This manuscript describes our experience creating a multi-institutional case log, incorporating data from three American diagnostic radiology residency programs. Each of the three sites independently established automated query pipelines from the various radiology information systems in their respective hospital groups, thereby creating a resident-specific database. Then, the three institutional resident case log databases were aggregated into a single centralized database schema. Three hundred thirty residents and 2,905,923 radiologic examinations over a 4-year span were catalogued using 11 ACGME categories. Our experience highlights big data challenges including internal data heterogeneity and external data discrepancies faced by informatics researchers. |
| Databáze: | OpenAIRE |
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