Improving Hospital Scheduling And Patient Flow

Journal of Theoretical and Applied Electronic Commerce Research ISSN 0718–1876 Electronic Version VOL 4 / ISSUE 2 / AUGUST 2009 / 20-30 © 2009 Universidad de Talca - Chile

This paper is available online at www.jtaer.com DOI: 10.4067/S0718-18762009000200003

Using Visual Analytics to Improve Hospital Scheduling and Patient Flow
Janna Anneke Fitzgerald1 and Ann Dadich2
University of Western Sydney, Centre for Industry and Innovation Studies 1 [e-mail],2 [e-mail]
Received 8 January 2009; received in revised form 24 May 2009; accepted 15 June 2009

Abstract
The increasing demand for hospital emergency services has important implications for the allocation of limited public resources and the management of healthcare
It often involves the use of information technology to create visual process maps such as activity diagrams, flowcharts, Program (or Project) Evaluation and Review Technique (PERT) diagrams, and the like. Coined by Williams [80], Business Process Modeling (BPM) is premised on the belief that techniques for understanding physical control systems can be equally valuable for understanding business processes. Similarly, process modelling has been applied to healthcare settings. With the push for delivering high quality care, while reducing care costs, process modelling has been used to manage and improve workflows in healthcare [8]. For example, BPM was used to assess inpatient transport services in an effort to reduce occasions of service within the NSW ambulance service [58]. However, the academic literature is devoid of papers on tangible improvements as a direct result of BPM in healthcare institutions. Process modelling generally commences with data mining – that is, the analysis of large-scale datasets from different sources. The purpose of data mining is to identify key patterns and trends, and thus understand macro processes reflected in the datasets [43]. This might include patterns of service delivery, production, and/or consumer behaviour. Process mining is then conducted to identify patterns and trends at a micro level. Event logs are used to analyse business processes and understand the minutiae of operational practices [79]. And it is this understanding that allows problem areas to be identified, and improvement strategies to be simulated. Simulation is a versatile way to understand and optimise the operation of systems [75], [50]. It can also help to visualise the impact of local decisions on entire systems. Macro and micro processes can be portrayed and manipulated, and