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Related Experiment Videos

Verifying keyed medical research data

B A Blumenstein1

  • 1Fred Hutchinson Cancer Research Center, Seattle, WA 98104.

Statistics in Medicine
|September 15, 1993
PubMed
Summary
This summary is machine-generated.

Double keying for medical data verification is declining. New methods like direct data entry with quality reviews or automated checks offer alternatives, but require robust quality assurance in other systems.

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Area of Science:

  • Medical Informatics
  • Data Management
  • Health Research

Background:

  • Double keying, a traditional method for verifying keyed medical research data, is being used less frequently.
  • There is a lack of published data evaluating replacements for double keying.
  • Visual comparison is an inadequate substitute due to human variability.

Purpose of the Study:

  • To assess the efficacy of alternatives to double keying for medical data verification.
  • To explore system design innovations that can maintain or improve data quality assurance without traditional double keying.
  • To highlight the increased reliance on other quality assurance mechanisms when double keying is eliminated.

Main Methods:

  • Evaluation of system design innovations that replace transcription and verification steps.

Related Experiment Videos

  • Analysis of direct keying from source documents with enhanced quality reviews.
  • Assessment of direct database input with automated consistency checking and immediate analytic use.

    • Main Results:

    • System design innovations can provide equivalent or superior data quality assurance opportunities compared to double keying.
    • Direct keying with quality reviews and direct database input with automated checks are viable alternatives.
    • Eliminating double keying shifts the data quality assurance burden to other subsystems.

    Conclusions:

    • While double keying is diminishing, effective alternatives exist through innovative system designs.
    • New technologies like tablet computers and voice input necessitate careful consideration for data quality assurance.
    • Robust quality review and automated checks are crucial for maintaining data integrity in the absence of double keying.