Measuring and controlling medical record abstraction (MRA) error rates in an observational study

Maryam Y. Garza, Tremaine Williams, Sahiti Myneni, Susan H. Fenton, Songthip Ounpraseuth, Zhuopei Hu, Jeannette Lee, Jessica Snowden, Meredith N. Zozus, Anita C. Walden, Alan E. Simon, Barbara McClaskey, Sarah G. Sanders, Sandra S. Beauman, Sara R. Ford, Lacy Malloch, Amy Wilson, Lori A. Devlin, Leslie W. Young

Resultado de la investigación: Articlerevisión exhaustiva


Background: Studies have shown that data collection by medical record abstraction (MRA) is a significant source of error in clinical research studies relying on secondary use data. Yet, the quality of data collected using MRA is seldom assessed. We employed a novel, theory-based framework for data quality assurance and quality control of MRA. The objective of this work is to determine the potential impact of formalized MRA training and continuous quality control (QC) processes on data quality over time. Methods: We conducted a retrospective analysis of QC data collected during a cross-sectional medical record review of mother-infant dyads with Neonatal Opioid Withdrawal Syndrome. A confidence interval approach was used to calculate crude (Wald’s method) and adjusted (generalized estimating equation) error rates over time. We calculated error rates using the number of errors divided by total fields (“all-field” error rate) and populated fields (“populated-field” error rate) as the denominators, to provide both an optimistic and a conservative measurement, respectively. Results: On average, the ACT NOW CE Study maintained an error rate between 1% (optimistic) and 3% (conservative). Additionally, we observed a decrease of 0.51 percentage points with each additional QC Event conducted. Conclusions: Formalized MRA training and continuous QC resulted in lower error rates than have been found in previous literature and a decrease in error rates over time. This study newly demonstrates the importance of continuous process controls for MRA within the context of a multi-site clinical research study.

Idioma originalEnglish (US)
Número de artículo227
PublicaciónBMC Medical Research Methodology
EstadoPublished - dic 2022

ASJC Scopus subject areas

  • Epidemiology
  • Health Informatics


Profundice en los temas de investigación de 'Measuring and controlling medical record abstraction (MRA) error rates in an observational study'. En conjunto forman una huella única.

Citar esto