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The effect of data-entry template design and anesthesia provider workload on documentation accuracy, documentation

Bryan A Wilbanks1, Eta S Berner2, Gregory L Alexander3

  • 1School of Nursing, University of Alabama at Birmingham, Birmingham, AL, USA.

International Journal of Medical Informatics
|August 30, 2018
PubMed
Summary

Computer-assisted data entry improves documentation accuracy and efficiency for anesthesia providers, reducing workload compared to auto-filling or paper methods. Further study is recommended for this promising approach.

Keywords:
AnesthesiaAnesthesia information management systemDocumentation qualityNursing informaticsTemplate design

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Area of Science:

  • Anesthesiology
  • Health Informatics
  • Human Factors Engineering

Background:

  • Limited evidence-based guidelines exist for designing clinical data-entry templates.
  • Template design impacts usability, accuracy, and efficiency in healthcare documentation.
  • Anesthesia provider workload is a critical factor in documentation quality.

Purpose of the Study:

  • To explore the impact of data-entry template design on documentation accuracy, efficiency, and user satisfaction.
  • To identify optimal data-entry methods for future documentation interface design.
  • To assess the influence of anesthesia provider workload on documentation outcomes.

Main Methods:

  • Observational data collection and psychometric instruments were used.
  • Three data-entry methods were compared: auto-filling, computer-assisted selection, and paper-based.
  • Thirty nurse anesthetists across three hospitals participated in the study.

Main Results:

  • Auto-filling yielded the lowest documentation accuracy (61.2%).
  • Computer-assisted data entry demonstrated the highest accuracy (81.3%) and efficiency (9.65% time).
  • Paper-based documentation resulted in the highest perceived workload (M=288).

Conclusions:

  • Auto-filling with unstructured data should be used cautiously due to low accuracy.
  • Computer-assisted data entry with semi-structured data shows potential for improved accuracy, efficiency, and reduced workload.
  • Further research into computer-assisted data entry is warranted for optimizing perioperative documentation.