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British Journal of Medicine and Medical Research, ISSN: 2231-0614,Vol.: 18, Issue.: 4

Original-research-article

A Simple Method to Forecast Future Bed Requirements: A Pragmatic Alternative to Queuing Theory

 

Neeraj Beeknoo1* and Rodney P. Jones2

1King’s College University Hospital, London, UK.

2Healthcare Analysis & Forecasting, Worcester, UK.

Article Information
Editor(s):
(1) Rui Yu, Environmental Sciences & Engineering, Gillings School of Global Public Health, The University of North Carolina at Chapel Hill, USA.
Reviewers:
(1) Kurubaran Ganasegeran, Clinical Research Centre, Seberang Jaya Hospital Penang, Malaysia.
(2) Sanjay Kumar Gupta, Peoples University, Bhopal, India.
Complete Peer review History: http://www.sciencedomain.org/review-history/16580

Abstracts

Aims: To review the current state of hospital bed planning, and to develop a simple tool to estimate short-term future bed requirements using historical bed occupancy data.

Study Design: Analysis of daily bed occupancy between January 2008 and October 2015. Synthesis of trends into a method for forecasting bed numbers for each day of the year.

Place and Duration of Study: Daily occupied bed statistics for King’s College University Hospital, a large London Teaching Hospital having 1,600 beds.

Methodology: An eight-year time-series of daily midnight bed occupancy covering elective, emergency and transfer admissions has been used to estimate the number of beds required to deliver a delay-free hospital.

Results: In this large 1,600 bed hospital it is estimated that 100 extra beds (a 6.3% increase) are required to deliver delay free admissions, i.e. no delays to admission from the emergency department or delays due to cancelled elective operations.

Conclusion: The analysis reveals that far higher flexibility is required in staffing levels than is currently available. Potential strategies are discussed to address this issue.

Keywords :

Hospital bed modelling; optimum occupancy; trend analysis; health policy; queuing theory; delay to admission; staffing.

Full Article - PDF    Page 1-20

DOI : 10.9734/BJMMR/2016/29518

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