Analysis and Optimization of a Sepsis Clinical Pathway Using Process Mining

  • Ricardo Alfredo Quintano NeiraEmail author
  • Bart Franciscus Antonius Hompes
  • J. Gert-Jan de Vries
  • Bruno F. Mazza
  • Samantha L. Simões de Almeida
  • Erin Stretton
  • Joos C. A. M. Buijs
  • Silvio Hamacher
Conference paper
Part of the Lecture Notes in Business Information Processing book series (LNBIP, volume 362)


In this work, we propose and apply a methodology for the management and optimization of clinical pathways using process mining. We adapt the Clinical Pathway Analysis Method (CPAM) by taking into consideration healthcare providers’ needs. We successfully applied the methodology in the sepsis treatment of a major Brazilian hospital. Using data extracted from the hospital information system, a total of 5,184 deviations in the execution of the sepsis clinical pathway were discovered and categorized in 43 different types. We identified the process as it was actually executed, two bottlenecks, and significant differences in performance in cases that deviated from the prescribed clinical pathway. Furthermore, factors such as patient age, gender, and type of infection were shown to affect performance. The analysis results were validated by an expert panel of clinical professionals and verified to provide valuable, actionable insights. Based on these insights, we were able to suggest optimization points in the sepsis clinical pathway.


Clinical Pathways Sepsis Process analytics 



The authors thank A. Medeiros, D. Brizida Dreux, M. Santos, R. da Silva Santos, S. Barbosa, W.M.P. van der Aalst and all professionals involved from Hospital Samaritano and Philips for their help in the development of this research. This study was partly financed by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - Brasil (CAPES) - Finance Code 001, Conselho Nacional de Desenvolvimento Científico e Tecnológico - CNPq [grant numbers 140511/2018-0, 306802/2015-5, 403863/2016-3], and Philips Research.


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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Ricardo Alfredo Quintano Neira
    • 1
    • 2
    Email author
  • Bart Franciscus Antonius Hompes
    • 2
    • 3
  • J. Gert-Jan de Vries
    • 2
  • Bruno F. Mazza
    • 4
  • Samantha L. Simões de Almeida
    • 4
  • Erin Stretton
    • 2
  • Joos C. A. M. Buijs
    • 3
  • Silvio Hamacher
    • 1
  1. 1.Industrial Engineering DepartmentPontifícia Universidade Católica do Rio de JaneiroRio de JaneiroBrazil
  2. 2.Philips ResearchEindhovenThe Netherlands
  3. 3.Department of Mathematics and Computer ScienceEindhoven University of TechnologyEindhovenThe Netherlands
  4. 4.Hospital Samaritano de São PauloSão PauloBrazil

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