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Related Experiment Video

Updated: Apr 19, 2026

Assessment of Dependence in Activities of Daily Living Among Older Patients in an Acute Care Unit
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Published on: September 30, 2020

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Care on demand in nursing homes: a queueing theoretic approach.

Karin van Eeden1, Dennis Moeke2,3, René Bekker1

  • 1Department of Mathematics, VU University Amsterdam, De Boelelaan 1081a, 1081 HV, Amsterdam, The Netherlands.

Health Care Management Science
|December 28, 2014
PubMed
Summary

This study introduces a quantitative model to optimize care worker staffing in nursing homes. It uses call button data to ensure residents receive timely care, proposing an 80/10 service level.

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Area of Science:

  • Healthcare Management
  • Operations Research
  • Geriatric Care

Background:

  • Nursing homes operate under strict healthcare budgets, necessitating increased efficiency in care processes.
  • Optimizing care worker allocation is crucial for resident well-being and managing labor costs.
  • Managers struggle with staffing decisions due to a lack of reliable data on resident needs.

Purpose of the Study:

  • To develop a quantitative model for the 'care on demand' process in nursing homes.
  • To assist nursing home managers in determining optimal care worker staffing levels.
  • To establish a measurable service level for responding to resident requests.

Main Methods:

  • Analysis of real-life 'call button' data from a Belgian nursing home.
  • Development of a queueing model based on the analyzed data.
  • Numerical experiments to determine appropriate service level parameters.

Main Results:

  • A quantitative queueing model for the 'care on demand' process was successfully developed.
  • An 80/10 service level was proposed: 80% of resident requests attended within 10 minutes.
  • The model provides a data-driven approach for staffing decisions in nursing homes.

Conclusions:

  • This study presents the first quantitative model for optimizing 'care on demand' in nursing homes.
  • The proposed model and service level can enhance efficiency and resident care quality.
  • Data-driven staffing decisions are essential for effective nursing home management.