–This workshop is organized in conjunction with the International Conference on Process Mining (ICPM 2021) in Eindhoven (the Netherlands) on November 1, 2021 —

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 different domains such as education, finance, and especially healthcare.

The 4th International Workshop on Process-Oriented Data Science for Healthcare 2021 (PODS4H 2021) 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 related to the implementation of PODS methodologies in healthcare organizations.

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: #PODS4H2021

 

Important Dates

REGULAR PAPER

  • Abstract submission deadline:  19 August 2021
  • Paper submission deadline:  26 August 2021
  • Notification of acceptance:  16 September 2021
  • Camera ready submission (pre-workshop):  30 September 2021
  • Workshop day:  1 November 2021

EXTENDED ABSTRACT AND POSTER

  • Submission deadline:  23 September 2021
  • Notification of acceptance:  30 september 2021 (or earlier)
  • Camera ready submission:  7 October 2021
  • Workshop day:  1 November 2021

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

 

Workshop Topics

Submitted works should cover the analysis, management, or improvement of processes using recorded data in the healthcare domain. Approaches which are not process-centric 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

Two types of submissions are accepted: regular papers and extended abstracts (with posters).

REGULAR PAPER

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=icpm2021 and select “4th International Workshop on 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 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.

EXTENDED ABSTRACT AND POSTER

Submitted extended abstracts and posters will be evaluated on the basis of significance, originality, and potential to generate a relevant discussion. Extended abstracts must use the Springer LNCS/LNBIP format. Submissions must be in English and cannot exceed 2 pages (including tables, figures and the bibliography). Extended abstracts and posters should be submitted electronically in PDF-format via the Easychair submission system (https://easychair.org/conferences/?conf=icpm2021 and select “4th International Workshop on 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 submissions are entitled to participate in the workshop’s poster session and will get the opportunity for a one-minute teaser presentation during one of the workshop’s sessions. Accepted submissions will be published on the workshop’s website, but are not part of the post-workshop proceedings. At least one author of each accepted submission must register and participate in the workshop.

 

Journal Special Issue

The best regular papers will be invited to submit an extended version on a fast-track at the Special Issue on Process-Oriented Data Science of the International Journal of Environmental Research and Public Health (IJERPH). IJERPH is indexed in the Journal Citation Reports – Thomson Reuters, with a 5-Year Impact Factor of 3.127. The expanded workshop paper must fulfill the following requirements: (1) the paper should be expanded to the size of a journal research article; (2) the workshop paper should be cited and noted on the first page of the paper; (3) if the authors do not hold the copyright of the published workshop paper, authors should seek the appropriate permission from the copyright holder; (4) authors are asked to disclose that it is workshop paper in their paper’s introduction and include a detailed statement on what has been changed compared to the original workshop paper. Papers MUST include the line “Supported by the Process-Oriented Data Science for Healthcare Alliance (PODS4H Alliance)”. Notice that IJERPH is an open-access journal, and it is the authors responsibility to cover the Article Processing Charges (http://www.mdpi.com/journal/ijerph/apc) if the paper is finally accepted.  

 



Program

The workshop program will be announced once it has been compiled.



 

Awards

PODS4H21 will have two awards: the “PODS4H21 Best Paper Award” and the “PODS4H21 Best Student Paper Award”. The awards will be provided during the conference and will be announced on the website afterwards.

 

Organizing Committee

  • 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 (chapter within the  IEEE Task Force on Process Mining). 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

 

Contact

pods4h@nullhaplab.org