Surgery
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Automated data extraction from the electronic medical record is fast, scalable, and inexpensive compared with manual abstraction. However, concerns regarding data quality and control for underlying patient variation when performing retrospective analyses exist. This study assesses the ability of summary electronic medical record metrics to control for patient-level variation in cost outcomes in pancreaticoduodenectomy. ⋯ Summary electronic medical record perioperative risk metrics predict patient-level cost variation as effectively as individual comorbidities in the pancreaticoduodenectomy population. Automated electronic medical record data extraction can expand the patient population available for retrospective analysis without the associated increase in human and fiscal resources that manual data abstraction requires.