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Analysis and Optimization of a Sepsis Clinical Pathway Using Process Mining

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Business Process Management Workshops (BPM 2019)

Part of the book series: Lecture Notes in Business Information Processing ((LNBIP,volume 362))

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Abstract

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.

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Notes

  1. 1.

    See https://promtools.org, https://fluxicon.com, and https://r-project.org.

  2. 2.

    Two-tailed Mann-Whitney U test: \(U=261,472.5\); \(n1=366\); \(n2=1,199\); \(p<0.001\).

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Acknowledgments

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.

Author information

Authors and Affiliations

  1. Industrial Engineering Department, Pontifícia Universidade Católica do Rio de Janeiro, Rio de Janeiro, Brazil

    Ricardo Alfredo Quintano Neira & Silvio Hamacher

  2. Philips Research, Eindhoven, The Netherlands

    Ricardo Alfredo Quintano Neira, Bart Franciscus Antonius Hompes, J. Gert-Jan de Vries & Erin Stretton

  3. Department of Mathematics and Computer Science, Eindhoven University of Technology, Eindhoven, The Netherlands

    Bart Franciscus Antonius Hompes & Joos C. A. M. Buijs

  4. Hospital Samaritano de São Paulo, São Paulo, Brazil

    Bruno F. Mazza & Samantha L. Simões de Almeida

Authors
  1. Ricardo Alfredo Quintano Neira
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  2. Bart Franciscus Antonius Hompes
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  3. J. Gert-Jan de Vries
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  4. Bruno F. Mazza
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  7. Joos C. A. M. Buijs
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Correspondence to Ricardo Alfredo Quintano Neira .

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Editors and Affiliations

  1. Fondazione Bruno Kessler, Trento, Italy

    Chiara Di Francescomarino

  2. Eindhoven University of Technology, Eindhoven, The Netherlands

    Remco Dijkman

  3. University of Vienna, Vienna, Austria

    Uwe Zdun

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Quintano Neira, R.A. et al. (2019). Analysis and Optimization of a Sepsis Clinical Pathway Using Process Mining. In: Di Francescomarino, C., Dijkman, R., Zdun, U. (eds) Business Process Management Workshops. BPM 2019. Lecture Notes in Business Information Processing, vol 362. Springer, Cham. https://doi.org/10.1007/978-3-030-37453-2_37

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  • DOI: https://doi.org/10.1007/978-3-030-37453-2_37

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  • Online ISBN: 978-3-030-37453-2

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