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1st International Workshop on Process Mining Applications for Healthcare (PM4H 23)

In conjuntion with the International Conference on Artificial Intelligence in Medicine (AIME23) in Portoroz, Slovenia

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 Mining Applications for Healthcare 2023 (PM4H23) 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. PM4H research includes a variety of topics ranging from process mining techniques adapted for healthcare processes, to practical issues related to the implementation of PM4H methodologies in healthcare organizations. During the 1st edition of our workshop at AIME, 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 PM4H 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, which is a chapter within the IEEE Task Force on Process Mining.

Proceedings​

CCISProceedings

Papers selected and presented during PM4H 2023 were published in a CCIS Springer as part of the Proceedings of the International Workshops on Explainable Artificial Inteligence and Process Mining for Healthcare 2023.

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

Submission Instructions​

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

Full papers & Short Papers - Research papers and case studies: 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. Full Papers cannot exceed 12 pages (including tables, figures, the bibliography and appendices), and Short Papers cannot exceed 6 pages . 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.. 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 as a post-workshop proceedings in an Editorial to be determined. At least one author of each accepted paper must register and participate in the workshop.

Abstracts and posters: 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. 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.

Important Dates​

  • Full papers & Posters - Abstract submission deadline: 15 April 2023

  • Full papers & Posters- Paper submission deadline: 15 April 2023

  • Full papers & Posters- Notification of acceptance: 15 May 2023

  • Full papers & Posters - Pre-workshop camera-ready: 7 June 2023

  • Workshop day: 15 June 2023

  • Full papers - Post-workshop proceedings camera-ready: 1 July 2023

Program​

Organizing Committee​

  • Carlos Fernandez-Llatas, Universitat Politècnica de Valencia (Spain)
  • Niels Martin, Hasselt University (Belgium)
  • Owen Johnson, University of Leeds (UK)
  • Marcos Sepúlveda, Pontificia Universidad Católica de Chile (Chile)
  • 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.

Program Committee​

  • Davide Aloini, University of Pisa
  • Iris Beerepoot, Utrecht University
  • Elisabetta Benevento, University of Pisa
  • Andrea Burattin, Technical University of Denmark
  • Arianna Dagliatti, University of Pavia
  • Benjamin Dalmas, Centre de Recherche Informatique de Montréal
  • Rene de la Fuente, Pontificia Universidad Católica de Chile
  • Kerstin Denecke, Bern University of Applied Sciences
  • Hans Eguia, Universitat Oberta d Cataluña
  • Carlos Fernandez-Llatas, Universitat Politècnica de València
  • Roberto Gatta, Department of Radiation Oncology, Università Cattolica S. Cuore, Italy
  • Josha Grueger, University of Trier
  • Emmanuel Helm, University of Applied Sciences Upper Austria
  • Gema Ibanez-Sanchez, Universitat Politècnica de València
  • Owen Johnson, Leeds University
  • Luis Marco, Norwegian Centre for E-Health Research
  • Mar Marcos, Universitat Jaume I
  • Niels Martin, University of Hasselt
  • Begoña Martinez, Universitat Jaume I
  • Renata Medeiros de Carvalho, Eindhoven University of Technology
  • Jorge Munoz-Gama, Pontificia Universidad Católica de Chile
  • Simon Poon, The University of Sydney
  • Luise Pufahl, TU Berlin
  • Hajo Reijers, Utrecht University
  • Octavio Ribera-Romero, Universidad de Sevilla
  • Eric Rojas, Universidad Católica de Chile
  • Massimiliano Ronzani, Fundazione Bruno Kessler
  • 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, University of Pisa
  • Emilio Sulis, University of Turin
  • Erica Tavazzi, University of Padova
  • Pieter Toussaint, Norwegian University of Science and Technology
  • Vicente Traver, Universitat Politècnica de València
  • Zoe Valero-Ramon, Universitat Politècnica de València
  • Mathias Weske, HPI, University of Potsdam
  • Moe Wynn, Queensland University of Technology
  • Francesca Zerbato, University of St. Gallen