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Data Validation

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Data validation is an essential part of a comprehensive assessment. Validation is confirming or verifying and opening the door to gathering more assessment data as it clarifies vague or unclear data. The process of checking and verifying the collected information is called data validation. The primary purpose of data validation is to ensure data is as free from error, bias, and misinterpretation as possible.
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The emergency department trigger tool: Multicenter trigger query validation.

Richard T Griffey1, Ryan M Schneider1, Keith E Kocher2

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This summary is machine-generated.

The Emergency Department Trigger Tool (EDTT) automated screening accurately identifies potential adverse events (AEs), performing well against manual review. This validates its use for AE detection in multicenter studies.

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Area of Science:

  • Healthcare quality improvement
  • Patient safety research
  • Clinical informatics

Background:

  • Adverse events (AEs) are a significant concern in healthcare.
  • The Emergency Department Trigger Tool (EDTT) was developed for AE detection.
  • Previous validation of the EDTT was established.

Purpose of the Study:

  • To validate the computerized EDTT screening against manual review as a first step in a multicenter study.
  • To establish the automated process for selecting records for AE review.

Main Methods:

  • Retrospective observational study of 912 patient visits across three urban academic EDs over 18 months.
  • Comparison of automated trigger query results with manual screening by two independent reviewers per site.
  • Calculation of positive predictive values (PPVs) and negative predictive values (NPVs) to assess accuracy.

Main Results:

  • The EDTT query demonstrated high accuracy with an overall PPV of 95.4% and NPV of 99.2%.
  • Individual trigger PPVs exceeded 90% for most triggers across sites.
  • Manual review findings were amended in only 1.5% of cases discordant with the automated query.

Conclusions:

  • The EDTT trigger query performs effectively compared to manual review.
  • Findings demonstrate the feasibility and generalizability of implementing the EDTT query across different sites.
  • This validates the EDTT's utility for AE detection and provides a foundation for further research.