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Related Experiment Videos

Handheld computers for data entry: high tech has its problems too.

Tania M Shelby-James1, Amy P Abernethy, Andrew McAlindon

  • 1Department of Palliative and Supportive Services, Flinders University, Bedford Park, South Australia, Australia. tania.shelby-james@rgh.sa.gov.au

Trials
|February 21, 2007
PubMed
Summary
This summary is machine-generated.

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Handheld computer data capture in clinical settings showed significantly higher error rates than traditional paper methods. Further training and monitoring are essential for accurate electronic data collection in healthcare.

Area of Science:

  • Medical Informatics
  • Clinical Data Management
  • Health Information Technology

Background:

  • The adoption of handheld computers in clinical practice has surged, yet their data accuracy compared to paper methods remains largely untested.
  • This study addresses the assumption of electronic data capture superiority by comparing handheld device accuracy against paper-based systems.

Purpose of the Study:

  • To evaluate and compare the accuracy of patient information collected via handheld computers versus traditional paper forms.
  • To identify potential discrepancies and error rates associated with electronic data capture in a clinical trial setting.

Main Methods:

  • Clinical nurses concurrently recorded patient data using both handheld computers and paper forms during a randomized controlled trial.
  • Data from both methods were entered into an Access database for a direct comparison of discrepancies.

Related Experiment Videos

Main Results:

  • Handheld computers exhibited an error rate of 67.5 per 1000 fields, substantially exceeding the benchmark for paper-based double data entry (10 per 10,000 fields).
  • Error rates were particularly elevated in fields that included pre-populated default values.

Conclusions:

  • Despite staff preference, handheld computers demonstrated unacceptably high error rates for clinical data collection.
  • Implementing handheld computers effectively requires comprehensive training and continuous oversight to ensure data integrity.