Healthcare systems in many countries are leveraging emerging technologies (e.g., cloud computing, mobile apps, data science, biosensors, and wearable devices) and modern software engineering approaches to ensure continuous quality improvement in the presence of rapid change and increasing challenges. Software-intensive systems are seen as a key enabler for healthcare system reform in many jurisdictions with major investments and incentives to propel this transformation. At the same time, interoperability barriers continue to impede adoption, especially in the context of complex care where different types of healthcare providers from different organizations need to collaborate.
This workshop will provide a forum where students, researchers, and practitioners from software engineering, health informatics, and medical domains will be able to discuss the design, evaluation, and evolution of software systems in healthcare, disseminating standards, methods, models and techniques that will help to shape the next generation of such systems, especially in regard to safety, data governance, and sustainability.


The workshop is focused on, but not limited to the following topics:

Software engineering:

methods and techniques for modeling, designing, developing, and evaluating healthcare systems, software architectures, reference architectures, software product lines, context awareness and autonomous computing, technical debt, software quality, development processes, user interfaces, systems interoperability, cloud native applications, safety, security, sustainability, data governance, workflow integration, compliance and regulatory issues, and data analytics;

Healthcare systems:

eHealth, mHealth, telehealth, electronic health records systems, medical devices, biomedical data, healthcare performance management, quality of care, medication adherence and health monitoring, electronic prescription, health care management systems, ageing users, standards, and clinical decision support. We look for papers that explore the above topics and the role that Software engineering plays in creating solutions to address them. We are expressly interested in submissions from researchers in developing and underserved countries. We are also particularly interested in emerging trends in current practice submitted by those working in the healthcare domain.


Three types of submissions are invited:
Technical papers limited to 8 pages, presenting novel or tailored methods, processes, and tools;
Case studies l limited to 4 pages, reporting experiments and/or industry experiences; and
Short papers limited to 4 pages, reporting preliminary results of ongoing studies, emerging trends in current practice, or identifying relevant challenges.

The page limit includes all text, figures, tables, and references. All submissions must be unpublished original work and not be under review elsewhere. All papers will be judged on the basis of their clarity, relevance, originality, and applicability in practice.

Formatting and Submission Links: All submissions must be in English, formatted according to the ICSE 2019 Format and Submission Guidelines:

All submissions must conform to the IEEE Conference Proceedings Formatting Guidelines (title in 24pt font and full text in 10pt type, LaTEX users must use \documentclass[10pt,conference]{IEEEtran} without including the compsoc or compsocconf option).
Works must be submitted in PDF format via EasyChair:

Publication of Papers

Accepted papers will be published in the electronic ICSE 2019 Proceedings in the IEEE Digital Library.
Authors of accepted papers are required to register for the workshop and attend the workshop in order to have the paper included in the proceedings.
The official publication date of the workshop proceedings is the date the proceedings are made available by IEEE. This date may be up to two weeks prior to the first day of ICSE 2019. The official publication date affects the deadline for any patent filings related to published work.

Important Dates

Abstract Submission deadline (CLOSED): February 1, 2019
Full Paper Submission deadline (CLOSED): February 4, 2019
Notification to authors (CLOSED): March 1, 2019
List of accepted papers sent to workshop co-chairs (CLOSED): March 5, 2019
Camera-ready copy due (CLOSED): March 15, 2019
Workshop date: May 27, 2019



David L. Buckeridge, MD Ph.D

McGill University, Montreal, Canada

Bio: David Buckeridge is a Professor of Epidemiology and Biostatistics at McGill University in Montreal where he holds the Canadian Institutes of Health Research (CIHR) Applied Public Health Chair in eHealth Interventions. A Fellow of the Royal College of Physicians and Surgeons of Canada with specialty training in Public Health and Preventive Medicine, Dr Buckeridge practices Public Health as a Medical Consultant to the Montreal Public Health Department, the Quebec Public Health Institute, and the Quebec Institute for Excellence in Health and Social Services. As a clinician-scientist in public health, his research and practice focus on the informatics of public health surveillance and disease control. At McGill, Dr Buckeridge directs the Surveillance Lab, which is an interdisciplinary group of over twenty students and staff with a mission to develop, implement, and evaluate novel computational methods for public health surveillance. Laboratory research activities are funded by the Canadian Institutes of Health Research, the National Sciences and Engineering Research Council, the Canadian Foundation for Innovation, and the Bill and Melinda Gates Foundation. Dr Buckeridge has consulted on surveillance to groups such as the Public Health Agency of Canada, Canada Health Infoway, the US National Academy of Medicine, the US and Chinese Centers for Disease Control, the European Centers for Disease Control, and the World Health Organization. He has a M.D. from Queen's University, a M.Sc. in Epidemiology from the University of Toronto, and a Ph.D. in Biomedical informatics from Stanford University.

Abstract: Most intelligent systems used in healthcare represent knowledge in the form of logical assertions or the numerical parameters of quantitative models. Through two examples, I will describe some challenges and benefits of both approaches. In the first example, I will describe the development and evaluation of a system for detecting interactions of drugs that might cause an older person to fall and for guiding a clinician in changing drug therapy to reduce that risk. The knowledge in this system was encoded in the form of a statistical model, with parameters learned from health records for nearly half a million people. The second example is the Population Health Record, a system for calculating, analyzing, and disseminating a wide range of indicators of population health to guide public health and health system professionals in making decisions about allocating resources. The knowledge in this system is encoded in the form of an ontology, which encodes taxonomical and causal relationships between risk factors, diseases, and health interventions.

Workshop Program

08:30 - 08:45: Workshop Opening

08:45 - 10:30: Technical Session 1: Healthcare Systems: Design, Development and Experiences

10:30 - 11:00: Coffee break

11:00 - 12:30: Keynote speaker: Prof. David Buckeridge (Clinical and Health Informatics Research, University of McGill, Canada)

12:30 - 14:00: Lunch

14:00 - 15:30: Technical Session 2: Interoperability for Healthcare systems

15:30 - 16:00: Coffee break

16:00 - 17:35: Technical Session 3: Technical challenges in Healthcare

17:35 - 18:00: Discussion Session and Workshop Closing



Frances Paulisch

Siemens Healthineers, Germany


Elisa Y. Nakagawa

University of São Paulo, Brazil


Liam Peyton

University of Ottawa, Canada


Elena Navarro

University of Castilla-La Mancha, Spain


Milena Guessi

University of São Paulo, Brazil


Lina Garcés

University of São Paulo, Brazil

Program Committee



For more information, feel free to contact us: (