Abstract
The Emergency Department (ED) is responsible to provide medical and surgical care to patients arriving at the hospital in need of immediate care. At the regional level, the EDs system can be seen as a network of EDs cooperating to maximise the outputs (number of patients served, average waiting time, ...) and outcomes in terms of the provided care quality. In this paper we discuss how quantitative analysis based on health care big data can provide a tool to evaluate the dispatching policies for the network of emergency departments operating in Piedmont, Italy: the basic idea is to exploit clusters of EDs in such a way to fairly distribute the workload. Further, we discuss how big data can enable a novel methodological approach to the health system analysis.
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References
Aringhieri, R., Addis, B., Tànfani, E., Testi, A.: Clinical pathways: insights from a multidisciplinary literature survey. In: Proceedings ORAHS 2012 (2012), ISBN: 978-90-365-3396-6
Aringhieri, R., Bruni, M., Khodaparasti, S., van Essen, J.: Emergency medical services and beyond: addressing new challenges through a wide literature review. Comput. Oper. Res. 78, 349–368 (2017)
Aringhieri, R., Carello, G., Morale, D.: Supporting decision making to improve the performance of an Italian emergency medical service. Ann. Oper. Res. 236, 131–148 (2016)
Aringhieri, R., Duma, D.: The optimization of a surgical clinical pathway. In: Obaidat, M.S., Ören, T., Kacprzyk, J., Filipe, J. (eds.) Simulation and Modeling Methodologies, Technologies and Applications. AISC, vol. 402, pp. 313–331. Springer, Cham (2015). https://doi.org/10.1007/978-3-319-26470-7_16
Borshchev, A.: The Big Book of Simulation Modeling. Multimethod Modeling with AnyLogic, vol. 6 (2013), ISBN: 978-0-9895731-7-7
Brailsford, S., Lattimer, V., Tarnaras, P., Turnbull, J.: Emergency and on-demand health care: modelling a large complex system. J. Oper. Res. Soc. 55(1), 34–42 (2004)
Cardoen, B., Demeulemeester, E.: Capacity of clinical pathways - a strategic multi-level evaluation tool. J. Med. Syst. 32(6), 443–452 (2008)
De Bleser, L., Depreitere, R., De Waele, K., Vanhaecht, K., Vlayen, J., Sermeus, W.: Defining pathways. J. Nurs. Manag. 14, 553–563 (2006)
Hoot, N., Aronsky, D.: Systematic review of emergency department crowding: causes, effects, and solutions. Ann. Emerg. Med. 52(2), 126–136 (2008)
Hwang, U., Concato, J.: Care in the emergency department: how crowded is overcrowded? Acad. Emerg. Med. 11(10), 1097–1101 (2004)
Ozcan, Y., Tànfani, E., Testi, A.: Improving the performance of surgery-based clinical pathways: a simulation-optimization approach. Health Care Manag. Sci. 20, 1–15 (2017)
Panella, M., Marchisio, S., Stanislao, F.: Reducing clinical variations with clinical pathways: Do pathways work? Int. J. Qual. Health Care 15, 509–521 (2003)
Proudlove, N., Black, S., Fletcher, A.: Or and the challenge to improve the NHS: modelling for insight and improvement in in-patient flows. J. Oper. Res. Soc. 58(2), 145–158 (2007)
Rotter, T., Kinsman, L., James, E., Machotta, A., Gothe, H., Willis, J., Snow, P., Kugler, J.: Clinical pathways: effects on professional practice, patient outcomes, length of stay and hospital costs (review). The Cochrane Library, vol. 7 (2010)
Setzler, H., Saydam, C., Park, S.: EMS call volume predictions: a comparative study. Comput. Oper. Res. 36(6), 1843–1851 (2009)
Vanderby, S., Carter, M.: An evaluation of the applicability of system dynamics to patient flow modelling. J. Oper. Res. Soc. 61(11), 1572–1581 (2010)
Wolstenholme, E.: A patient flow perspective of U.K. health services: exploring the case for new “intermediate care” initiatives. Syst. Dyn. Rev. 15(3), 253–271 (1999)
Wolstenholme, E., Monk, D., McKelvie, D., Arnold, S.: Coping but not coping in health and social care: masking the reality of running organisations beyond safe design capacity. Syst. Dyn. Rev. 23(4), 371–389 (2007)
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Aringhieri, R., Dell’Anna, D., Duma, D., Sonnessa, M. (2018). Evaluating the Dispatching Policies for a Regional Network of Emergency Departments Exploiting Health Care Big Data. In: Nicosia, G., Pardalos, P., Giuffrida, G., Umeton, R. (eds) Machine Learning, Optimization, and Big Data. MOD 2017. Lecture Notes in Computer Science(), vol 10710. Springer, Cham. https://doi.org/10.1007/978-3-319-72926-8_46
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DOI: https://doi.org/10.1007/978-3-319-72926-8_46
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