title: Quality of EHR data extractions for studies of preterm birth in a tertiary care center: guidelines for obtaining reliable data.
abstract: The use of Electronic Health Records (EHR) has increased significantly in the past 15 years. This study compares electronic vs. manual data abstractions from an EHR for accuracy. While the dataset is limited to preterm birth data, our work is generally applicable. We enumerate challenges to reliable extraction, and state guidelines to maximize reliability.
  
  
  
  An Epic™ EHR data extraction of structured data values from 1,772 neonatal records born between the years 2001-2011 was performed. The data were directly compared to a manually-abstracted database. Specific data values important to studies of perinatology were chosen to compare discrepancies between the two databases.
  
  
  
  Discrepancy rates between the EHR extraction and the manual database were calculated for gestational age in weeks (2.6 %), birthweight (9.7 %), first white blood cell count (3.2 %), initial hemoglobin (11.9 %), peak total and direct bilirubin (11.4 % and 4.9 %), and patent ductus arteriosus (PDA) diagnosis (12.8 %). Using the discrepancies, errors were quantified in both datasets using chart review. The EHR extraction errors were significantly fewer than manual abstraction errors for PDA and laboratory values excluding neonates transferred from outside hospitals, but significantly greater for birth weight. Reasons for the observed errors are discussed.
  
  
  
  We show that an EHR not modified specifically for research purposes had discrepancy ranges comparable to a manually created database. We offer guidelines to minimize EHR extraction errors in future study designs. As EHRs become more research-friendly, electronic chart extractions should be more efficient and have lower error rates compared to manual abstractions.
authors.affiliation: Department of Pediatrics, University of Iowa Hospitals and Clinics, 200 Hawkins Drive, 276 MRF, Iowa City, IA, 52240, USA.
authors.forename: Lindsey A
authors.initials: LA
authors.lastname: Knake
authors.affiliation: Institue for Clinical and Translational Science, University of Iowa, Iowa City, IA, USA.
authors.forename: Monika
authors.initials: M
authors.lastname: Ahuja
authors.affiliation: Department of Pediatrics, University of Iowa Hospitals and Clinics, 200 Hawkins Drive, 276 MRF, Iowa City, IA, 52240, USA.
authors.forename: Erin L
authors.initials: EL
authors.lastname: McDonald
authors.affiliation: Department of Epidemiology, University of Iowa, Iowa City, IA, USA.
authors.forename: Kelli K
authors.initials: KK
authors.lastname: Ryckman
authors.affiliation: Department of Pediatrics, University of Iowa Hospitals and Clinics, 200 Hawkins Drive, 276 MRF, Iowa City, IA, 52240, USA.
authors.forename: Nancy
authors.initials: N
authors.lastname: Weathers
authors.affiliation: Institue for Clinical and Translational Science, University of Iowa, Iowa City, IA, USA.
authors.forename: Todd
authors.initials: T
authors.lastname: Burstain
authors.affiliation: Department of Pediatrics, University of Iowa Hospitals and Clinics, 200 Hawkins Drive, 276 MRF, Iowa City, IA, 52240, USA.
authors.forename: John M
authors.initials: JM
authors.lastname: Dagle
authors.affiliation: Department of Pediatrics, University of Iowa Hospitals and Clinics, 200 Hawkins Drive, 276 MRF, Iowa City, IA, 52240, USA.
authors.forename: Jeffrey C
authors.initials: JC
authors.lastname: Murray
authors.affiliation: Institue for Clinical and Translational Science, University of Iowa, Iowa City, IA, USA. prakash-nadkarni@uiowa.edu.
authors.forename: Prakash
authors.initials: P
authors.lastname: Nadkarni
mesh_terms: D000068598:Data Accuracy; D016208:Databases, Factual / Q000592:standards*; D057286:Electronic Health Records / Q000592:standards*; D005260:Female; D006801:Humans; D007231:Infant, Newborn; D007234:Infant, Premature; D007235:Infant, Premature, Diseases / Q000175:diagnosis; D008297:Male; D011247:Pregnancy; D047928:Premature Birth; D062606:Tertiary Care Centers / Q000458:organization & administration
keywords: Bioinformatics; Data quality; EHR and manual chart abstraction comparison; EHR vs. Manual chart abstraction, and difference in data quality; Neonatology; PEDs data registry; Prematurity; Quality assurance