Characterization of the flow of patients in a hospital from complex networks

M. A. Miranda (), S. Salvatierra, I. Rodríguez, M. J. Álvarez and V. Rodríguez
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M. A. Miranda: University of Navarra
S. Salvatierra: University of Navarra
I. Rodríguez: University of Navarra
M. J. Álvarez: University of Navarra
V. Rodríguez: University of Navarra

Health Care Management Science, 2020, vol. 23, issue 1, No 6, 66-79

Abstract: Abstract We study the efficiency of operations management in a hospital from the dynamics of the flow of patients. Our principal aim is to characterize strategic departments and seasonal patterns in a hospital from a complex networks approach. Process mining techniques are developed to track out-patients’ pathways along different departments for the purpose of building weekly networks. In these networks, departments act as nodes with multiple out/in-going arrows connecting other departments. Strategic departments are classified into target and critical departments. On the one hand, target departments, which in this study belong to the oncology area, correspond to those affected by new management policies whose impact is to be assessed. On the other hand, critical departments correspond to the most active departments, the hubs of the networks. Using suitable networks parameters, strategic departments are shown to be highly efficient regardless of the season, which naturally translates into a high level of service offered to patients. In addition, our results show conformance with the new objectives concerning target departments. The methodology presented is shown to be successful in evaluating the efficiency of hospital services in order to enhance process performances, and moreover, it is suitable to be implemented in healthcare management systems at a greater scale and the service industry whenever the flow of clients or customers are involved.

Keywords: Complex networks in healthcare; Operational efficiency; Flow dynamics of patients; Process mining techniques (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (1)

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DOI: 10.1007/s10729-018-9466-2

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