Data electronically extracted from the electronic health record require validation

Objectivesdetermine sources of error in electronically extracted data from electronic health records.study designcategorical and continuous variables related to early-onset neonatal hypoglycemia were preselected and electronically extracted from records of 100 randomly selected neonates within 3479 births with laboratory-proven early-onset hypoglycemia. extraction language was written by an information technologist and data validated by blinded manual chart review. kappa coefficient assessed categorical variables and percent validity continuous variables.results8/23 (35%) categorical variables had acceptable κappa (1–0.81); 5/23 (22%) had fair-slight agreement, κappa < 0.40. notably, “hypoglycemia” had poor agreement, κappa 0.16. in contrast, 6/8 continuous variables had validity ≥ 94%. after correcting extraction language, 6/9 variables were corrected and inter-rater validation improved. however, “hypoglycemia” was not corrected, remaining an issue.conclusionsdata extraction without validation procedures, especially categorical variables using international classification of diseases-9 (icd-9) codes, often results in incorrect data identification. electronically extracted data must incorporate built-in validating processes.