Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Videos

Can you depend on your patient classification system?

D L Hlusko1, B S Nichols

  • 1Children's Hospital of The King's Daughters, Norfolk, Virginia, USA.

The Journal of Nursing Administration
|April 1, 1996
PubMed
Summary
This summary is machine-generated.

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Essential skills and knowledge of applicants.

AANA journal·1999
Same author

Cut training costs with computer-based tutorials.

Nursing management·1999
Same author

Reconceptualization of community health nursing clinicals for undergraduate students.

Public health nursing (Boston, Mass.)·1998
Same author

Hospital readmissions for rural elderly. 1992-1993.

The Journal of nursing administration·1996
Same author

An exploration of the nursing diagnosis terminal syndrome.

Nursing diagnosis : ND : the official journal of the North American Nursing Diagnosis Association·1996
Same author

Cancer detection: how effective is public education?

Cancer nursing·1996
Same journal

The CNO-CFO Dyad: A Strategic Driver of Organizational Performance.

The Journal of nursing administration·2026
Same journal

Elements of Effective Professional Governance: An Integrative Review.

The Journal of nursing administration·2026
Same journal

New Nurse Well-Being: Implications for Retention, Job Satisfaction, and Patient Safety.

The Journal of nursing administration·2026
Same journal

Virtual Nursing Programs in Acute Care Settings: A Scoping Review of Patient, Nurse, and System-Level Outcomes.

The Journal of nursing administration·2026
Same journal

Occupational Fatigue and Cognitive Performance Among Front-Line Nurse Leaders: The Interplay of Personal and Work Factors.

The Journal of nursing administration·2026
Same journal

Enhancing Resilience and Well-Being Among Nurse Leaders: A Randomized Controlled Trial of Mindfulness and Narrative Interventions.

The Journal of nursing administration·2026
See all related articles

Patient classification models may underestimate patient care needs, leading to significant staffing shortages. This study found that predicted scores were lower than actual scores, impacting nurse staffing levels.

Area of Science:

  • Healthcare Management
  • Nursing Administration
  • Health Services Research

Background:

  • Accurate patient classification is crucial for effective nurse staffing and resource allocation.
  • Existing patient classification models are widely used but their accuracy in reflecting actual patient care needs requires ongoing evaluation.

Purpose of the Study:

  • To evaluate the reliability of a patient classification model in predicting actual patient care needs.
  • To determine the impact of model inaccuracies on nurse staffing levels and resource allocation.

Main Methods:

  • A comparative analysis was conducted between predicted patient classification scores and actual patient care scores.
  • Patient care needs were quantified in minutes per patient day.

Related Experiment Videos

Main Results:

  • Patient care needs were consistently underrated by the model, with underestimations ranging from 8 to 33 minutes per patient day.
  • This underestimation translated into a deficit of 0.24 to 2.99 full-time equivalent employees.

Conclusions:

  • The patient classification model used may not accurately reflect the true intensity of patient care needs.
  • Relying solely on this model for staff allocation can lead to significant understaffing and impact the quality of nursing services.