| Literature DB >> 26958300 |
Mollie McKillop1, Fernanda Polubriaginof1, Chunhua Weng1.
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.Entities:
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Year: 2015 PMID: 26958300 PMCID: PMC4765601
Source DB: PubMed Journal: AMIA Annu Symp Proc ISSN: 1559-4076