5th International Workshop on
Process-Oriented Data Science for Healthcare

— This workshop is organized in conjunction with the International Conference on Process Mining (ICPM 2022) in Bozen-Bolzano (Italy) on October 24, 2022 —

The world’s most valuable resource is no longer oil, but data. The ultimate goal of data science techniques is not to collect more data, but to extract knowledge and valuable insights from existing data in various forms. To analyze and improve processes, event data is the main source of information. In recent years, a new discipline has emerged combining traditional process analysis and data-centric analysis: Process-Oriented Data Science (PODS). The interdisciplinary nature of this new research area has resulted in its application to analyze processes in a wide variety of domains. This workshop has an explicit focus on healthcare.

The International Workshop on Process-Oriented Data Science for Healthcare 2022 (PODS4H22) provides a high-quality forum for interdisciplinary researchers and practitioners to exchange research findings and ideas on data-driven process analysis techniques and practices in healthcare. PODS4H research includes a variety of topics ranging from process mining techniques adapted for healthcare processes, to practical issues related to the implementation of PODS methodologies in healthcare organizations.

During the 5th edition of our workshop, we aim to bring together researchers and practitioners in a spirit of collaboration and co-creation. In this way, we have the ambition to move PODS4H research and practice forward, taking into account the distinguishing characteristics and challenges of the healthcare domain which were recently published in the Journal of Biomedical Informatics (https://doi.org/10.1016/j.jbi.2022.103994).

This workshop is an initiative of the Process-Oriented Data Science for Healthcare Alliance  within the IEEE Task Force on Process Mining

Web: www.pods4h.com
Twitter: @PODS4H
Hashtag: #PODS4H2022


Important Dates

FULL PAPERS (closed for new submissions)

  • Abstract submission deadline: 10 August 2022 17 August 2022 (extended)
  • Paper submission deadline: 17 August 2022 24 August 2022 (extended, deadline expired)
  • Notification of acceptance: 14 September 2022 16 September 2022
  • Camera ready submission (pre-workshop):  5 October 2022
  • Workshop day:  24 October 2022
  • Post-workshop proceedings camera ready: 7 November 2022

ABSTRACTS AND POSTERS (closed for new submissions)

  • Submission deadline:  22 September 2022
  • Notification of acceptance:  ongoing review (*)
  • Camera ready submission:  20 October 2022
  • Workshop day:  24 October 2022

Deadlines correspond to anywhere on earth (‘AoE’ or ‘UTC-12′)

(*) Ongoing review: within two weeks after submission, 30 September 2022 at the latest


Workshop Topics

Submitted works should focus on the analysis, management, or improvement of processes using recorded data in the healthcare domain. Approaches which are not process-centric are considered out of scope. The workshop aims to compose a program containing both more theoretical contributions related to new techniques and algorithms, as well as more applied contributions such as methodologies and real-life case studies. We are looking forward to welcoming submissions from PODS4H researchers regarding their latest research results. Moreover, we highly encourage practitioners active in the healthcare domain to share their experiences and contribute to the workshop.

The topics of interest include, but are not limited to:

  • Process Mining in Healthcare
  • Process Discovery in Healthcare
  • Data-aided Process Modeling in Healthcare
  • Conformance Checking and Compliance Analysis of Healthcare Processes
  • Data-aided Process Enhancement and Repair
  • Healthcare Process Prediction and Recommendation
  • Healthcare Process Simulation
  • Healthcare Process Optimization
  • Process-Aware Hospital Information Systems Analysis and Data Extraction
  • Interfaces for PODS4H
  • Disease-driven PODS4H
  • Methodologies for PODS4H
  • Best Practices for PODS4H
  • Case Studies of PODS4H
  • WACI (Wild And Crazy Ideas) for PODS4H


Submission Instructions

Two types of submissions are considered: (1) full papers – research papers and case studies, and (2) abstracts and posters. 


For the full papers, a distinction is made between research papers and case studies. Research papers should focus on extending the state of the art of PODS4H research. Case studies should focus on a practical application of PODS4H in a real-life context and should clearly illustrate the distinguishing characteristics and challenges associated with PODS4H (https://doi.org/10.1016/j.jbi.2022.103994). Submissions should explicitly indicate whether they are a research paper or a case study by adding “Research Paper” or “Case Study” as a subtitle.

Submitted full papers will be evaluated on the basis of relevance, originality, technical quality, and their potential to generate a relevant discussion, while taking into account whether it is a research paper or a case study. Submissions must use the Springer LNCS/LNBIP format. Submissions must be in English and cannot exceed 12 pages (including tables, figures, the bibliography and appendices). Besides stating whether the submission is a research paper or a case study, each paper should clarify the relation of the paper to the workshop’s main topics, clearly state the problem being addressed, the proposed solution, the results achieved, and the relation to other work. Papers should be submitted electronically as a self-contained PDF file via the Easychair submission system (https://easychair.org/conferences/?conf=icpm2022 and select “Process-Oriented Data Science for Healthcare”). Submissions must be original contributions that have not been published previously, nor already submitted to other conferences or journals in parallel with this workshop. Accepted full papers will be presented during one of the workshop’s sessions and will be published by Springer as a post-workshop proceedings volume in the series Lecture Notes in Business Information Processing (LNBIP). At least one author of each accepted paper must register and participate in the workshop.


Abstracts are an accessible way to share your ideas and experiences with the PODS4H community. They can focus on more theoretical contributions (new algorithms or techniques), but submissions on practical applications of existing methods or related to practical experiences are especially welcomed.

Abstracts should be in English and cannot exceed 250 words. Abstracts should be submitted electronically via the Easychair submission system (https://easychair.org/conferences/?conf=icpm2022 and select “Process-Oriented Data Science for Healthcare”). They will be reviewed on an ongoing basis and we have the firm ambition to provide you with a notification within two weeks after submission. Authors of accepted abstracts are entitled to participate in the workshop’s poster session and will get the opportunity to give a short pitch during one of the workshop’s sessions. Upon request of the author, the poster can be published on the workshop’s website, but the abstract and poster will not be part of the post-workshop proceedings. At least one author of each accepted submission must register and participate in the workshop. The author is responsible for bringing a printed copy of the poster to the workshop.



The full text versions of the full papers are available by clicking on the title.

09:00 – 10:45: SESSION 1 (chair: Marcos Sepúlveda)

10:45 – 11:30: COFFEE BREAK

11:30 – 12:45: SESSION 2 (chair: Carlos Fernandez-Llatas)

12:45 – 14:30: LUNCH BREAK

14:30 – 15:45: SESSION 3 (chair: Emmanuel Helm)

15:45 – 16:30: COFFEE BREAK

16:30 – 17:30: POSTER SESSION (chair: Niels Martin)

  • Poster 1: Owen P. Dwyer – “Process-Oriented Knowledge Graphs: Incorporating Knowledge Graph Methods into Patient Pathway Models”
  • Poster 2: Emmelien De Roock, Niels Martin and Filip Van Droogenbroeck – “Do you know what healthcare professionals want to know? Towards a method to identify the information needs of healthcare professionals.”
  • Poster 3: Mariachiara Savino, Roberto Gatta, Giuditta Chiloiro, Nikola Dino Capocchiano, Jacopo Lenkowicz, Benedetta Gottardelli, Carlotta Masciocchi, Vincenzo Valentini and Andrea Damiani – “A Real-World Application of Process Mining for Clinical Guidelines Compliance in Rectal Cancer”
  • Poster 4: Emmanuel Helm, Georg Buchgeher and Lisa Ehrlinger – “Online Plausibility Checks for Patient Pathways with Medical Ontologies” (abstract)
    download poster (poster)
  • Poster 5: Jungeun Lim, Kangah Park, Kidong Kim, Sooyoung Yoo, Hyunyoung Baek, Seok Kim and Minseok Song – “BPMN-based CP modeling considering existing CP models and repetition patterns”
  • Poster 6: Lara Chammas – “Translation of the patient record into event logs of different abstraction levels”
  • Poster 7: Víctor Gálvez, Rene de la Fuente, Jorge Munoz-Gama and Marcos Sepúlveda – “The control-flow aspect in procedural skills training: why it is needed and how to include it?”
  • Poster 8: Mariagrazia Lorusso, Arianna Dagliati, Lucia Sacchi, Erica Tavazzi, Stefania Orini, Mauro Vallati and Roberto Gatta – “pMinShiny: A Graphical User Interface for Process Mining in Healthcare”
  • Poster 9: Davide Aloini, Elisabetta Benevento, Marco Berdini and Alessandro Stefanini – “Predicting Waiting and Service Times in Emergency Departments through Machine Learning and Process Mining”

Organizing Committee

  • Niels Martin, Hasselt University (Belgium)
  • Carlos Fernandez-Llatas, Universitat Politècnica de Valencia (Spain)
  • Owen Johnson, University of Leeds (United Kingdom)
  • Marcos Sepúlveda, Pontificia Universidad Católica de Chile (Chile)
  • Emmanuel Helm, University of Applied Sciences Upper Austria (Austria)
  • Jorge Munoz-Gama, Pontificia Universidad Católica de Chile (Chile)

The workshop is an initiative of the Process-Oriented Data Science for Healthcare Alliance. The goal of this international alliance is to promote the research, development, education and understanding of process-oriented data science in healthcare. For more information about the activities and its members visit  pods4h.com/alliance. PODS4H Alliance is the chapter within the  IEEE Task Force on Process Mining to promote the use of Process Mining in Healthcare.


Program Committee 

  • Davide Aloini, University of Pisa
  • Robert Andrews, Queensland University of Technology
  • Iris Beerepoot, Utrecht University
  • Elisabetta Benevento, University of Pisa
  • Andrea Burattin, Technical University of Denmark
  • Dr. Daniel Capurro, University of Melbourne
  • Marco Comuzzi, Ulsan National Institute of Science and Technology
  • Benjamin Dalmas, École des Mines de Saint-Étienne
  • Carlos Fernandez-Llatas, Universitat Politècnica de Valencia
  • Dr. René de la Fuente, Pontificia Universidad Católica de Chile
  • Claudio Di Ciccio, Sapienza University of Rome
  • Onur Dogan, Izmir University Bakircay
  • Roberto Gatta, Università Cattolica del Sacro Cuore
  • Emmanuel Helm, University of Applied Sciences Upper Austria
  • Owen Johnson, University of Leeds
  • Felix Mannhardt, Eindhoven University of Technology
  • Ronny Mans, Philips Research
  • Niels Martin, Hasselt University
  • Mar Marcos, Universitat Jaume I
  • Renata Medeiros de Carvalho, Eindhoven University of Technology
  • Jorge Munoz-Gama, Pontificia Universidad Católica de Chile
  • Marco Pegoraro, RWTH Aachen University
  • Simon Poon, University of Sydney
  • Luise Pufahl, Technische Universität Berlin
  • Ricardo Quintano, Philips Research
  • Hajo Reijers, Utrecht University
  • David Riaño, Universitat Rovira i Virgili
  • Stefanie Rinderle-Ma, Technical University of Munich
  • Eric Rojas, Pontificia Universidad Católica de Chile
  • Lucia Sacchi, University of Pavia
  • Fernando Seoane, Karolinska Institutet
  • Marcos Sepúlveda, Pontificia Universidad Católica de Chile
  • Minseok Song, Pohang University of Science and Technology
  • Alessandro Stefanini, Università di Pisa
  • Emilio Sulis, Università di Torino
  • Pieter Toussaint, Norwegian University of Science and Technology
  • Vicente Traver, Universitat Politècnica de Valencia
  • Wil van der Aalst, RWTH Aachen University
  • Rob Vanwersch, Maastricht University Medical Center
  • Mathias Weske, HPI – University of Potsdam
  • Moe Wynn, Queensland University of Technology