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Regular papers

A queueing model for the capacity planning of a multi-phase human services process

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Pages 156-167 | Received 29 Jun 2014, Accepted 02 Feb 2015, Published online: 17 Mar 2015
 

Abstract

The increasing availability of data concerning service demand and service provision has enabled the application of queueing models in new domains. In this paper, we present a case study involving a queueing model of the multi-phase statutory child protection services process in the State of Victoria, Australia. The model, which has been calibrated using field data, supports the exploration of alternative scenarios of client types and loads, and of staffing levels. The model is intended as a tool for managers to examine and provide an insight into the process and enables a quantitative analysis of the process, to assist in resource analysis and capacity planning. It provides for calibration at the caseworker level, including the requirement for a caseworker to handle multiple cases simultaneously. Closed form analysis of the model, a network of processor sharing queues, is not feasible. We describe three methods that support performance analysis of the process at different levels, drawing on mathematical results from the literature and using both analytic and simulation techniques.

Acknowledgements

This work was conducted at the Department of Human Services, Victoria. We would like to thank Stuart Lindner, the Specialist Intervention Team and EMR for their support and also wish to thank the reviewers for their advice in improving the presentation of the paper which led to significant improvements. We also note that in December 2012 DHS underwent divisional changes which included a new operating model. EMR has been restructured into the East Division and there are new types of case carrying staff.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

P.G. Taylor would like to thank the Australian Research Council [Linkage grant LP0349153], [Discovery grant DP110101663] for supporting this work.

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