Clare J Lee1, G Craig Wood2, Nicole Bressler2, Tombra Govina2, Mariana Lazo3, Todd T Brown4, Jeanne M Clark3, Christopher Still2, Peter Benotti2. 1. Division of Endocrinology, Diabetes & Metabolism, Department of Medicine, The Johns Hopkins University, 1830 E. Monument St., Baltimore, MD, 21287, USA. clee158@jhmi.edu. 2. Geisinger Obesity Research Institute, Geisinger Clinic, Danville, PA, USA. 3. Division of General Internal Medicine, Department of Medicine, The Johns Hopkins University, Baltimore, MD, USA. 4. Division of Endocrinology, Diabetes & Metabolism, Department of Medicine, The Johns Hopkins University, 1830 E. Monument St., Baltimore, MD, 21287, USA.
Abstract
OBJECTIVE: We sought to validate an algorithm designed to identify patients with post-gastric bypass hypoglycemia (PGBH) using clinician chart review. METHODS: We conducted a chart review study of non-diabetic patients who underwent Roux-en-Y gastric bypass (RYGB) at our institution from 2004 to 2013. The electronic medical record (EMR) algorithm was based on any post-operative glucose <60 mg/dl, diagnosis of hypoglycemia, or medication use for treatment of PGBH and identified 158 charts as PGBH and 1048 charts without PGBH. Two clinicians independently reviewed a random selection of 80 cases and 80 control charts and determined the presence or absence of PGBH by searching the chart using keywords and reviewing laboratory results, medications, and clinic notes. RESULTS: Of the 160 charts reviewed, the EMR algorithm agreed with the chart review for 130 (accuracy = 80%, 95% CI = 75-87%) with sensitivity of 89% (95% CI = 83-96%) and specificity of 86% (95% CI = 78-93%). We improved the algorithm's accuracy to 90% by limiting the search to data obtained 3 months or more following RYGB. CONCLUSION: The EMR algorithm has high sensitivity, specificity, and accuracy to identify post-gastric bypass hypoglycemia within our patient cohort. The use EMR-based algorithms may be a useful tool for future research to improve our understanding of epidemiology and risk factors for post-bariatric surgery hypoglycemia.
OBJECTIVE: We sought to validate an algorithm designed to identify patients with post-gastric bypass hypoglycemia (PGBH) using clinician chart review. METHODS: We conducted a chart review study of non-diabeticpatients who underwent Roux-en-Y gastric bypass (RYGB) at our institution from 2004 to 2013. The electronic medical record (EMR) algorithm was based on any post-operative glucose <60 mg/dl, diagnosis of hypoglycemia, or medication use for treatment of PGBH and identified 158 charts as PGBH and 1048 charts without PGBH. Two clinicians independently reviewed a random selection of 80 cases and 80 control charts and determined the presence or absence of PGBH by searching the chart using keywords and reviewing laboratory results, medications, and clinic notes. RESULTS: Of the 160 charts reviewed, the EMR algorithm agreed with the chart review for 130 (accuracy = 80%, 95% CI = 75-87%) with sensitivity of 89% (95% CI = 83-96%) and specificity of 86% (95% CI = 78-93%). We improved the algorithm's accuracy to 90% by limiting the search to data obtained 3 months or more following RYGB. CONCLUSION: The EMR algorithm has high sensitivity, specificity, and accuracy to identify post-gastric bypass hypoglycemia within our patient cohort. The use EMR-based algorithms may be a useful tool for future research to improve our understanding of epidemiology and risk factors for post-bariatric surgery hypoglycemia.
Entities:
Keywords:
Bariatric surgery; Electronic medical record; Hypoglycemia; Validation
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