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Related Concept Videos

Data Validation01:03

Data Validation

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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Formulating and Validating Nursing Diagnosis II

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Related Experiment Videos

Validating a knowledge transfer framework in health services.

Doug Orendorff1, Alex Ramirez, Elayne Coakes

  • 1Sprott School of Business, Carleton University and Westminster Business School, Westminster University. doug.orendorff@rogers.com

Studies in Health Technology and Informatics
|June 19, 2008
PubMed
Summary

This study identifies ten key determinants for successful horizontal knowledge transfer (KT) in healthcare. Nine determinants were supported, offering managers tools to improve KT success rates.

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Area of Science:

  • Health Services Management
  • Organizational Behavior
  • Knowledge Management

Background:

  • Knowledge transfer (KT) research has progressed independently in health services and business.
  • This creates an opportunity for cross-disciplinary synergy and knowledge sharing.
  • Existing KT frameworks require extension to encompass diverse transfer determinants.

Purpose of the Study:

  • To identify key determinants of horizontal knowledge transfer success.
  • To develop and validate a novel KT Framework integrating determinants, transfer flows, and outcomes.
  • To provide practical tools for managers to assess and enhance KT.

Main Methods:

  • Survey of 32 empirical KT studies to identify 96 unique determinants.
  • Development of a new KT Framework based on identified determinants and transfer flows.
  • Validation of the KT Framework via a case study of clinical practice guideline transfer in Ontario hospitals.

Main Results:

  • Ten unique determinants for horizontal KT success were identified.
  • Eight of ten determinants were supported in successful transfer hospitals.
  • Nine of ten determinants showed aggregate support, with 'Knowledge Complexity' being the exception.
  • Tacit knowledge transfer was linked to explicit knowledge transfer, even without direct interaction.

Conclusions:

  • The proposed KT Framework is substantially supported by empirical evidence.
  • Nine key determinants can guide managers in improving knowledge transfer processes.
  • Understanding the relationship between explicit and tacit knowledge transfer is crucial for effective KT.