Electronic Healthcare. Second International ICST Conference, eHealth 2009, Istanbul, Turkey, September 23-15, 2009, Revised Selected Papers

Research Article

Adaptive Planning of Staffing Levels in Health Care Organisations

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  • @INPROCEEDINGS{10.1007/978-3-642-11745-9_14,
        author={Harini Kulatunga and W. Knottenbelt and V. Kadirkamanathan},
        title={Adaptive Planning of Staffing Levels in Health Care Organisations},
        proceedings={Electronic Healthcare. Second International ICST Conference, eHealth 2009, Istanbul, Turkey, September 23-15, 2009, Revised Selected Papers},
        proceedings_a={E-HEALTH},
        year={2012},
        month={5},
        keywords={Adaptive staff scheduling staffing cost minimisation integrated health care systems},
        doi={10.1007/978-3-642-11745-9_14}
    }
    
  • Harini Kulatunga
    W. Knottenbelt
    V. Kadirkamanathan
    Year: 2012
    Adaptive Planning of Staffing Levels in Health Care Organisations
    E-HEALTH
    Springer
    DOI: 10.1007/978-3-642-11745-9_14
Harini Kulatunga1,*, W. Knottenbelt1,*, V. Kadirkamanathan2,*
  • 1: Imperial College London
  • 2: University of Sheffield
*Contact email: hkulatun@doc.ic.ac.uk, wjk@doc.ic.ac.uk, visakan@sheffield.ac.uk

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.