title: Exploration of Temporal ICD Coding Bias Related to Acute Diabetic Conditions.
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.
authors.affiliation: Department of Biomedical Informatics, Columbia University, New York, NY, USA.
authors.forename: Mollie
authors.initials: M
authors.lastname: McKillop
authors.affiliation: Department of Biomedical Informatics, Columbia University, New York, NY, USA.
authors.forename: Fernanda
authors.initials: F
authors.lastname: Polubriaginof
authors.affiliation: Department of Biomedical Informatics, Columbia University, New York, NY, USA.
authors.forename: Chunhua
authors.initials: C
authors.lastname: Weng
mesh_terms: D015982:Bias; D001786:Blood Glucose; D003920:Diabetes Mellitus; D006801:Humans; D007004:Hypoglycemic Agents; D038801:International Classification of Diseases
chemical_list: D001786:Blood Glucose; D007004:Hypoglycemic Agents