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Exploration of Temporal ICD Coding Bias Related to Acute Diabetic Conditions
Mollie McKillop1, Fernanda Polubriaginof1, Chunhua Weng1
1Department of Biomedical Informatics, Columbia University, New York, NY, USA.
Abstract:
Electronic Health Records (EHRs) hold great promise for secondary data reuse but have been reported to contain severe biases. The temporal characteristics of coding biases remain unclear. This study used a survival analysis approach to reveal temporal bias trends for coding acute diabetic conditions among 268 diabetes patients. For glucose-controlled ketoacidosis patients we found it took an average of 7.5 months for the incorrect code to be removed, while for glucose-controlled hypoglycemic patients it took an average of 9 months. We also examined blood glucose lab values and performed a case review to confirm the validity of our findings. We discuss the implications of our findings and propose future work.
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