Accuracy of Electronic Health Record Documentation of Parental Presence: A Data Validation and Quality Improvement

Abigail Shuman1, Karl Umble2, Dana B McCarty3

  • 1Medicine, Georgetown University School of Medicine, Washington DC, USA.

Cureus
|July 26, 2024
PubMed

Insights

Electronic health records (EHR) can accurately track parental presence in the neonatal intensive care unit (NICU). Documentation accuracy varies by shift and recording method, offering insights for improving data collection.

Area of Science:

  • Healthcare Informatics
  • Neonatal Medicine
  • Data Science

Background:

  • Parental presence in the neonatal intensive care unit (NICU) positively impacts infant health outcomes.
  • Electronic health records (EHR) offer potential for analyzing parental presence and sociodemographic factors.
  • Limited evidence exists on the accuracy of non-clinical data, such as parental presence, within EHRs.

Purpose of the Study:

  • To validate the accuracy of EHR documentation for parental presence in the NICU.
  • To compare EHR data with observational logs to assess agreement.
  • To identify factors influencing the accuracy of parental presence documentation in EHRs.

Main Methods:

  • A data validation study comparing an observational log of parental presence with EHR documentation.
  • Calculation of percentage agreement between the two data sources.
  • Stratification of accuracy by shift (day vs. night) and documentation type (flowsheet vs. plan of care notes).

Main Results:

  • High overall accuracy was observed when combining observational logs and EHR data.
  • Night shift documentation in EHRs was more accurate (76.3%) than day shift documentation (55.2%).
  • Flowsheet (FS) recordings (82.4%) demonstrated higher accuracy than free-text plan of care (POC) notes (75.1%).

Conclusions:

  • EHR documentation of non-clinical factors like parental presence can be accurate.
  • Documentation accuracy is influenced by the time of day and the specific EHR recording method used.
  • This study provides a methodological framework for future research utilizing EHR data for non-clinical variables.

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