Summary
Multi-phase models of patient flow offer a practical but scientifically robust approach to the studying and understanding of the different streams of patients cared for by health care units. In this chapter, we put forward a decision support system that is specifically designed to identify the different streams of patient flow and to investigate the effects of the interaction between them by using readily available administrative data. The richness of the data dictate the use of data warehousing and On-Line Analytical Processing (OLAP) for data analysis and pre-processing; the complex and stochastic nature of health care systems suggested the use of discrete event simulation as the decision model. We demonstrate the application of the decision support system by reporting on a case study based on data of patients over 65 with a stroke related illness discharged by English hospitals over a year.
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Vasilakis, C., El-Darzi, E., Chountas, P. (2008). A Decision Support System for Measuring and Modelling the Multi-Phase Nature of Patient Flow in Hospitals. In: Chountas, P., Petrounias, I., Kacprzyk, J. (eds) Intelligent Techniques and Tools for Novel System Architectures. Studies in Computational Intelligence, vol 109. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-77623-9_12
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DOI: https://doi.org/10.1007/978-3-540-77623-9_12
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-77621-5
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