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Related Experiment Videos

Adaptive double data entry: a probabilistic tool for choosing which forms to reenter.

K Kleinman1

  • 1Harvard Medical School and Harvard Pilgrim Health Care, Department of Ambulatory Care and Prevention, Boston, MA 02115, USA. ken_kleinman@hphc.org

Controlled Clinical Trials
|February 13, 2001
PubMed
Summary
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This study introduces an adaptive method for double data entry in clinical trials, reducing costs by selectively reentering forms based on error probability. This approach maintains data quality while optimizing resource allocation for quality assurance.

Area of Science:

  • Clinical Trials Data Management
  • Health Informatics
  • Biostatistics

Background:

  • Debate exists on the cost-effectiveness of double data entry in clinical trials.
  • Low error rates in controlled trials question the necessity of full double data entry.
  • Current practices may allocate resources away from more productive quality assurance tools.

Purpose of the Study:

  • To propose an alternative cost-effective method for maintaining data quality in clinical trials.
  • To introduce a formal, adaptive approach for selecting forms for double data entry.
  • To optimize resource allocation in clinical data management.

Main Methods:

  • Developed a form-by-form adaptive method for deciding on double data entry.
  • Utilized an estimated probability of error for each form as a guideline.

Related Experiment Videos

  • The method dynamically adjusts to individual data entry personnel and their accuracy over time.
  • Error probability estimation is based on a recent history of double-entered forms.

    • Main Results:

    • Simulations indicate significant reduction in data reentry while effectively detecting errors.
    • A practical data example confirmed the procedure's effectiveness.
    • The adaptive method demonstrated potential for cost savings in clinical trials.

    Conclusions:

    • The proposed adaptive double data entry method offers a viable alternative to traditional full reentry.
    • This technique balances cost reduction with robust data quality assurance in clinical trials.
    • Selective reentry based on error probability is an efficient strategy for data management.