–This event is organized in conjunction with the International Conference on Business Process Management (BPM 2019) in Vienna on September 2, 2019–
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 2nd International Workshop on Process-Oriented Data Science for Healthcare 2019 (PODS4H19) 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.
SESSION 1 (Chair: Niels Martin)
Opening: Welcome to PODS4H18
Paper 1: “Analysis and Optimization of a Sepsis Clinical Pathway using Process Mining”. Ricardo Alfredo Quintano Neira, Bart Franciscus Antonius Hompes, Gert-Jan de Vries, Bruno F. Mazza, Samantha L. Simões de Almeida, Erin Stretton, Joos C.A.M. Buijs and Silvio Hamacher.
Paper 2: “Understanding Undesired Procedural Behavior in Surgical Training: the Instructor Perspective”. Victor Galvez, Cesar Meneses, Gonzalo Fagalde, Jorge Munoz-Gama, Marcos Sepúlveda, Ricardo Fuentes and Rene de La Fuente.
Paper 3: “Towards Privacy-Preserving Process Mining in Healthcare”. Anastasiia Pika, Moe Wynn, Stephanus Budiono, Arthur Ter Hofstede, Wil van der Aalst and Hajo A. Reijers.
Paper 4: “Comparing Process Models for Patient Populations: Application in Breast Cancer Care”. Francesca Marazza, Faiza Bukhsh, Onno Vijlbrief, Jeroen Geerdink, Shreyaasi Pathak, Maurice van Keulen and Christin Seifert.
SESSION 2 (Chair: Owen Johnson)
Paper 5: “Evaluating the Effectiveness of Interactive Process Discovery in Healthcare: A Case Study”. Elisabetta Benevento, Prabhakar M. Dixit, Davide Aloini and Wil M.P. van der Aalst.
Paper 6: “Developing Process Performance Indicators for Emergency Room Processes”. Minsu Cho, Minseok Song, Seok-Ran Yeom, Il-Jae Wang and Byung-Kwan Choi.
Paper 7: “Interactive data cleaning for process mining: a case study of an outpatient clinic’s appointment system”. Niels Martin, Antonio Martinez-Millana, Bernardo Valdivieso and Carlos Fernandez-Llatas.
Paper 8: “Clinical Guidelines: a crossroad of many research areas. Challenges and opportunities in Process Mining for Healthcare”. Roberto Gatta, Mauro Vallati, Carlos Fernandez-Llatas, Antonio Martinez-Millana, Stefania Orini, Lucia Sacchi, Jacopo Lenkowicz, Mar Marcos, Jorge Munoz-Gama, Michel Cuendet, Berardino De Bari, Luis Marco, Alessandro Stefanini and Maurizio Castellano.
SESSION 3 (Chair: Carlos Fernandez-Llatas)
Paper 9: “Predicting outpatient process flows to minimise the cost of handling returning patients: A case study”. Marco Comuzzi, Jonghyeon Ko and Suhwan Lee.
Paper 10: “A Data Driven Agent Elicitation Pipeline for Prediction Models”. John Bruntse Larsen, Andrea Burattin, Christopher John Davis, Rasmus Hjardem-Hansen and Jørgen Villadsen.
Paper 11: “A solution framework based on process mining, optimization and discrete-event simulation to improve queue performance in an emergency department”. Bianca Antunes, Adrian Manresa, Leonardo Bastos, Janaina Marchesi and Silvio Hamacher.
Paper 12: “A multi-level approach for identifying process change in cancer pathways”. Angelina Prima Kurniati, Ciarán McInerney, Kieran Zucker, Geoff Hall, David Hogg and Owen Johnson.
SESSION 4 (Chair: Jorge Munoz-Gama)
Paper 13: “Adopting Standard Clinical Descriptors for Process Mining Case Studies in Healthcare”. Emmanuel Helm, Anna Lin, David Baumgartner, Alvin Lin and Josef Küng.
PODS4H Alliance Panel: Round-table community meeting session to discuss the current state of the discipline and future community efforts, next projects, collaborations, and position papers. All participants are welcome!
Closing: See you in PODS4H20 !
PODS4H18 Best Paper Award: To be announced in PODS4H19 …
PODS4H18 Best Student Paper Award: To be announced in PODS4H19 …
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
Two types of submissions are accepted:
Regular: Submitted papers will be evaluated on the basis of significance, originality, technical quality, and potential to generate relevant discussion. Submissions must use the Springer LNCS/LNBIP format. Submissions must be in English and must not exceed 12 pages (including figures, bibliography and appendices). Each paper should clarify the relation of the paper with the workshop 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=bpm2019) selecting the track “Workshop 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. Papers MUST include the line “Supported by the Process-Oriented Data Science for Healthcare Alliance (PODS4H Alliance)”. Accepted papers 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).
Success Cases: Success cases are short accessible communications describing a PODS4H experience performed by a group or a company in a specific scenario, along with some analysis that provides insights and learning for the future. Submissions must be in English and must not exceed 2 pages in Springer LNCS/LNBIP format. The document must include a first-page footnote with the ‘International Workshop on Process-Oriented Data Science for Healthcare (PODS4H) – Success Case’ reference. Papers should be submitted electronically as a self-contained PDF file via the submission system (https://easychair.org/conferences/?conf=bpm2019) selecting the track “Workshop Process-Oriented Data Science for Healthcare”. At least one author of each accepted paper must register and participate in the workshop. Accepted cases will be considered published work with oral presentation, being published online by PODS4H19 and authors will present it as a poster during the workshop’s breaks.
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 2.6. 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.
PODS4H19 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.
Abstract submission deadline (Regular):
17 May 2019 (with the paper submission)
Paper submission deadline (Regular):
24 May 2019 / 31 May 2019
Notification of acceptance (Regular): 28 June 2019
Camera ready (Regular): 12 July 2019
Success Case submission deadline: 8 July 2019
Success Case notification of acceptance: 17 July 2019
Workshop day: 2 September 2019
*Deadlines correspond to anywhere on earth (‘AoE’ or ‘UTC-12′)
- 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)
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
- Robert Andrews, Queensland University of Technology
- Joos Buijs, Eindhoven University of Technology
- Andrea Burattin, Technical University of Denmark
- Dr. Daniel Capurro, Pontificia Universidad Católica de Chile
- Josep Carmona, Universitat Politècnica de Catalunya
- Claudio di Ciccio, Vienna University of Economics and Business
- 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, VitalHealth Software
- Niels Martin, Hasselt University
- Renata Medeiros de Carvalho, Eindhoven University of Technology
- Jorge Munoz-Gama, Pontificia Universidad Católica de Chile
- Ricardo Quintano, Philips Research
- 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
- 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
- Moe Wynn, Queensland University of Technology