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

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

Extended abstract – Submission deadline: 21 July 2020
Extended abstract – Notification of acceptance: 4 August 2020
Extended abstract – Camera ready: 22 September 2020

Regular paper – Paper submission deadline: 25 August 2020
Regular paper – Notification of acceptance: 14 September 2020
Regular paper – Camera ready: 22 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

Two types of submissions are accepted: extended abstracts and regular papers.

Extended abstracts:
Submitted extended abstracts will be evaluated on the basis of significance, originality, and potential to generate a relevant discussion. Submissions 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 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 extended abstracts 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. At least one author of each accepted abstract must register and participate in the workshop. ​When submitting an extended abstract, it is required to also submit a regular paper on that topic. Note that this regular paper will undergo an autonomous peer review process.

Regular:
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. The best papers will be invited to submit an extended version on a fast-track at a JCR journal Special Issue (see Journal Special Issue section).

 

Journal Special Issue  

(To be Confirmed) 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 index, with a 5-Year Impact Factor of 2.95. 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

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.

 Awards

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

Contact

pods4h@nullhaplab.org