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Qualitative and Quantitative Validation of Tools with Rating Scales Aimed at Assessing the Quality of University Service-Learning
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Methodological challenges of validating a clinical decision-making tool in the practice environment.

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  • 1National Institutes of Health Clinical Center, Bethesda, MD, USA caitlin.brennan@nih.gov.

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|June 21, 2014
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Summary

Validating the Oncology Acuity Tool for clinical decision-making presented unique challenges. Balancing psychometric rigor with clinical relevance requires research-practice partnerships and continuous end-user feedback.

Keywords:
acuityacute careinstrument developmentnurse staffingoncology

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Area of Science:

  • Nursing Practice
  • Healthcare Management
  • Clinical Informatics

Background:

  • Validating measurement tools in practice settings differs from research settings.
  • Clinical decision-making tools require specific validation approaches.
  • The Oncology Acuity Tool aids nurses in shift-based staffing decisions.

Purpose of the Study:

  • To describe methodological challenges in validating a clinical decision-making tool.
  • To address issues encountered during the validation of the Oncology Acuity Tool.
  • To inform best practices for developing and validating practice-based measurement tools.

Main Methods:

  • Utilized data from a larger validation study of the Oncology Acuity Tool.
  • Incorporated iterative feedback cycles with end-users for tool revision.
  • Employed two approaches for inter-rater reliability assessment due to unknown "true" patient acuity.
  • Documented discordant perspectives between experts and end-users.

Main Results:

  • Iterative revisions and end-user feedback were crucial before validation.
  • Inter-rater reliability assessment faced challenges due to the subjective nature of patient acuity.
  • Discrepancies were observed between expert and end-user viewpoints.
  • The validation process highlighted the need to balance statistical rigor with clinical applicability.

Conclusions:

  • Establishing research-practice partnerships is key for balancing psychometric rigor and clinical relevance.
  • Continuous end-user engagement is vital throughout the validation process.
  • Practical considerations and end-user feedback should complement traditional statistical measures in tool validation.