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Developing and testing a Korean patient classification system for general wards based on nursing intensity.

Yukyung Ko1, Bohyun Park2, Hanju Lee3

  • 1Department of Nursing, College of Medicine, Wonkwang University, Iksan, South Korea.

Nursing Open
|March 10, 2021
PubMed
Summary

A new patient classification tool was developed to assess nursing intensity in general wards, considering clinical status and indirect care needs. This validated tool categorizes patients into four levels, improving nursing resource allocation.

Keywords:
Koreageneral wardnursing intensitypatient classification system

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Area of Science:

  • Nursing
  • Healthcare Management
  • Clinical Informatics

Background:

  • Accurate patient classification is crucial for effective nursing resource allocation in general wards.
  • Existing tools may not fully capture the complexity of nursing intensity, including indirect care activities.
  • Developing a refined patient classification system is essential for optimizing patient care and staff management.

Purpose of the Study:

  • To develop and validate a novel patient classification tool for general wards based on nursing intensity.
  • The tool aims to reflect patients' clinical characteristics and indirect nursing activities.
  • To establish a reliable and valid system for categorizing patients according to their nursing care requirements.

Main Methods:

  • A cross-sectional methodological study was conducted.
  • Content validity was established through expert review (13 experts).
  • Inter-rater reliability was assessed, and K-group cluster analysis identified score ranges for four patient groups.

Main Results:

  • The developed tool comprises 8 domains, 24 subdomains, 66 nursing activities, and 124 criteria.
  • Validated content and demonstrated high inter-rater reliability.
  • Four distinct patient groups based on nursing intensity were identified using cluster analysis.

Conclusions:

  • The newly developed patient classification tool effectively measures nursing intensity in general wards.
  • The tool's comprehensive domains and validated reliability support its use in practice.
  • This system can enhance the accuracy of patient classification and inform nursing resource allocation.