Skip to main content

Adaptive Planning of Staffing Levels in Health Care Organisations

  • Conference paper
  • 1081 Accesses

Abstract

This paper presents a new technique to adaptively measure the current performance levels of a health system and based on these decide on optimal resource allocation strategies. Here we address the specific problem of staff scheduling in real-time in order to improve patient satisfaction by dynamically predicting and controlling waiting times by adjusting staffing levels. We consider the cost of operation (which comprises staff cost and penalties for patients waiting in the system) and aim to simultaneously minimise the accumulated cost over a finite time period. A considerable body of research has shown the usefulness of queueing theory in modelling processes and resources in real-world health care situations. This paper will develop a simple queueing model of patients arriving at an Accident and Emergency unit and show how this technique provides a dynamic staff scheduling strategy that optimises the cost of operating the facility.

This is a preview of subscription content, log in via an institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Darzi, A.W.: Ideas from Darzi:polyclinics. NHS Confederation Publications (2008)

    Google Scholar 

  2. Bazzoli, B.J., Chan, B., Shortell, S., D’ Aunno, T.: The financial performance of hospitals belonging to health networks and systems. Inquiry 37(3), 234–252 (2000)

    CAS  PubMed  Google Scholar 

  3. Smith-Daniels, V.L., Schweikhart, S.B., Smith-Daniels, D.E.: Capacity management in health care services: Review and future research directions. Decision Sciences 19, 889–918 (1988)

    Article  Google Scholar 

  4. Brailsford, S.C., Lattimer, V.A., Tamaras, P., Turnbull, J.C.: Emergency and on demand health care: modelling a large and complex system. Journal of the Operational Research Society 55, 34–42 (2004)

    Article  Google Scholar 

  5. Gorunescu, F., McClean, S.I., Millard, P.H.: A queueing model for bed occupancy management and planning of hospital. Journal of the Operational Research Society 53, 19–24 (2002)

    Article  Google Scholar 

  6. Riaño, G.: Transient behaviour of stochastic networks: Application to production planning with load dependent lead times, Ph.D. Thesis, Georgia Institute of Technology (2002)

    Google Scholar 

  7. Grassmann, W.K.: Finding the right number of servers in real-world queueing systems. Interfaces 2, 94–104 (1988)

    Article  Google Scholar 

  8. Bertsekas, D.P., Tsitsiklis, J.: Neuro-dynamic programming. Athena scientific, Belmont (1996)

    Google Scholar 

  9. Coats, T.J., Michalis, S.: Mathematical modelling of patient flow through an Accident and Emergency department. Emergency Medicine Journal 18, 190–192 (2001)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Mayhew, L., Carney-Jones, E.: Evaluating a new approach for improving care in an Accident and Emergency department: The NU-care project. Technical report, Cass Business School, City University (2003)

    Google Scholar 

  11. Mayhew, L., Smith, D.: Using queueing theory to analyse completion times in Accident and Emergency times in the light of the government 4-hour target. Technical report, Cass Business School, City University, Actuarial Research Paper No. 177 (2006)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2010 ICST Institute for Computer Science, Social Informatics and Telecommunications Engineering

About this paper

Cite this paper

Kulatunga, H., Knottenbelt, W.J., Kadirkamanathan, V. (2010). Adaptive Planning of Staffing Levels in Health Care Organisations. In: Kostkova, P. (eds) Electronic Healthcare. eHealth 2009. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 27. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-11745-9_14

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-11745-9_14

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-11744-2

  • Online ISBN: 978-3-642-11745-9

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics