–This workshop is organized in conjunction with the International Conference on Process Mining (ICPM 2020) in Padua (Italy) on October 5, 2020 —

Due to the COVID-19 outbreak, PODS4H 2020 will be a fully virtual conference, with no travel involved. However, the entire program will be retained, and will not change. With the spirit of keeping the entire conference as interactive as possible, presentations will be given live using webinars. The presentations will also be broadcasted, and also available after the conference for off-line viewing. Attendees will be able to ask questions, which will be answered at the end of each presentation. The virtualization of the conference makes it an excellent opportunity to bring together everybody working on Process Mining in Healthcare. 

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 insights from existing data in various forms. For analyzing and improving 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 for analyzing processes in different domains such as education, finances, and especially healthcare.

The 3rd International Workshop on Process-Oriented Data Science for Healthcare 2020 (PODS4H 2020) aims at providing a high-quality forum for interdisciplinary researchers and practitioners (both data/process analysts and medical audience) to exchange research findings and ideas on healthcare process analysis techniques and practices. PODS4H research includes a wide range of topics from process mining techniques adapted for healthcare processes, to practical issues on implementing PODS methodologies in healthcare centers’ analysis units.

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: #PODS4H2020

Important Dates

Abstract submission deadline:            18 August 2020 1 September 2020 (final extension – strict deadline)

Paper submission deadline:               25 August 2020 4 September 2020 (final extension – strict deadline)

Notification of acceptance:                 14 September 2020 22 September 2020

Camera ready submission:                  22 September 2020 29 September 2020

Workshop day:                                   5 October 2020

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

Workshop Topics

Submitted works should involve the analysis, management, or improvement of processes using recorded data in the healthcare domain. Non process-centric approaches will fall out of scope. The workshop aims at both more theoretical contributions such as new techniques and algorithms, and more applied contributions such as methodologies and case studies.

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

  • Process Mining in Healthcare
  • Process Discovery and 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 and Best Practices for PODS4H
  • Case Studies and Application of PODS4H
  • WACI (Wild And Crazy Ideas) for PODS4H

Submission Instructions

Submitted papers will be evaluated on the basis of significance, originality, technical quality, and their potential to generate a relevant discussion. 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). Each paper should clarify the relation of the paper to the workshop’s main topics, clearly state the problem being addressed, the goal of the work, 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=pods4h2020). 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 regular 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.

For papers that are not accepted as regular papers but are still deemed valuable contributions to the topic of PODS4H, we plan to invite the authors to submit a version that will be published in the CEUR workshop proceedings [tentative].


PODS4H 2020 is a full-day workshop. The workshop would include regular paper presentations, poster presentations during the break, and a round-table panel about future initiatives and collaborations among the researchers in the area.


Celonis Academic Alliance promotes the “PODS4H 2020 Best Paper Award” and the “PODS4H 2020 Best Student Paper Award“. 

PODS4H 2020 Best Paper Award: Winners will be announced the day of the workshop.
PODS4H 2020 Best Student Paper Award: Winners will be announced the day of the workshop.

Organizing Committee

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

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 

  • Wil van der Aalst, RWTH Aachen University
  • Davide Aloini, Università di Pisa
  • Robert Andrews, Queensland University of Technology
  • Andrea Burattin, Technical University of Denmark
  • Dr. Daniel Capurro, University of Melbourne
  • Claudio di Ciccio, Sapienza University of Rome
  • 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
  • Roberto Gatta, Università Cattolica del Sacro Cuore
  • Emmanuel Helm, University of Applied Sciences Upper Austria
  • Zhengxing Huang, Zhejiang University
  • Owen Johnson, University of Leeds
  • Felix Mannhardt, SINTEF
  • Ronny Mans, Philips VitalHealth
  • 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
  • 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, University of Vienna
  • 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
  • Rob Vanwersch, Maastricht University Medical Center
  • Moe Wynn, Queensland University of Technology