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Training As An Intervention To Decrease Medical Record Abstraction Errors Multicenter Studies., Meredith Nahm Zozus, Leslie W. Young, Alan E. Simon, Maryam Garza, Lora Lawrence, Songthip T. Ounpraseuth, Megan Bledsoe, Sarah Newman-Norlund, J Dean Jarvis, Mary Mcnally, Kimberly R. Harris, Russell Mcculloh, Rachel Aikman, Sara Cox, Lacy Malloch, Anita Walden, Jessica Snowden, Irene Mangan Chedjieu, Chester A. Wicker, Lauren Atkins, Lori A. Devlin

Manuscripts, Articles, Book Chapters and Other Papers

Studies often rely on medical record abstraction as a major source of data. However, data quality from medical record abstraction has long been questioned. Electronic Health Records (EHRs) potentially add variability to the abstraction process due to the complexity of navigating and locating study data within these systems. We report training for and initial quality assessment of medical record abstraction for a clinical study conducted by the IDeA States Pediatric Clinical Trials Network (ISPCTN) and the Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD) Neonatal Research Network (NRN) using medical record abstraction as the primary data …