Information Technology in Healthcare

Health systems globally are experiencing challenges reaching crises levels. Manifestations of these crises that compromise standards of care include difficulties in accommodating patients visiting emergency departments or needing admissions to hospitals, or overcrowding of acute care facilities with a lack of beds to accommodate demands in hospital admissions. As a result, patients experience prolonged emergency department (ED) waits to access urgent care, and many patients who are admitted are boarded in the ED due to a lack of bed spaces to treat patients. These challenges result in poor patient experiences, unexpected deteriorations or even mortality in the ED waiting rooms, compromised care of admitted patients, overall health system dissatisfactions, and health professional burn-out.

Innovative solutions using health technologies and data sciences offer opportunities to address ED and hospital overcrowding through virtual hospital models. With opportunities of virtual ED to triage patients, virtual beds to treat patients in their own homes through virtual care, and post-admission discharge using remote patient monitoring to support convalescence, virtual hospitals can deliver safe and cost-effective care to reduce unnecessary ED visits, reduce hospitalization and treat acutely ill patients in the comfort of their own homes. Virtual care, remote patient monitoring, remote medications dispensing and administration, and artificial intelligence for decision support for health professionals and patients are core technologies to enable virtual hospital operationalization.

This minitrack is to showcase different virtual hospital models being implemented in various health systems in different countries, exploring their designs, implementation, evaluation, strengths, and issues needing calibration or attention. We endeavour to understand why and how virtual hospitals function in these contexts, common success factors, and also contextual variations and differences to promote knowledge exchange and establish good practices of virtual hospitals through this global exchange.

Minitrack Co-chairs:

Kendall Ho (Primary Contact)
University of British Columbia
kendall.ho@ubc.ca

Weizi (Vicky) Li
Henley Business School
Weizi.li@henley.ac.uk

Kelvin Tsoi
Chinese University of Hong Kong
kelvintsoi@cuhk.edu.hk

The integration of Artificial Intelligence (AI) in medicine is transforming healthcare delivery, diagnostics, treatment planning, and patient care. This minitrack aims to explore the role of AI in medicine, with a particular focus on the infrastructures required for large-scale distribution of deep learning technologies, generative algorithms, and intelligent agents. We invite contributions that discuss the development, deployment, and evaluation of AI frameworks and systems in healthcare, including but not limited to: predictive analytics in patient care, personalized medicine, medical imaging analysis, and automated clinical decision support systems.

One of the most demanding challenges for AI development in medicine is standardization and management of large quantities of multimodal, highly sensitive data. The complete workflow for AI model creation, starting from data acquisition by clinical experts, through storing, sharing, anonymizing, and labelling of the data, but also creating and maintaining pipelines for training and validation of AI systems can, and should be, supported by modern, state-of-the-art information and communication technology (ICT) infrastructures.

With disruptive new trends in AI in medicine, such as Generative AI, Agent Foundation Models, and Few-shot learning, it is widely recognized that the importance of AI in this domain will keep increasing in the upcoming years. The main areas of AI-driven applications in medicine in the near future are focused on supporting the work of radiologists, surgeons, and even general practitioners. The technological response for those needs is: the availability of cluster/cloud/distributed (super)computing, large-scale federated learning infrastructures, digital-twin approaches, and cutting-edge visualization interfaces that highly improve usability of novel technologies in medicine.

Moreover, as healthcare moves towards more personalized and preemptive models, the demand for dedicated AI frameworks that can process vast amounts of health data is ever-increasing. This minitrack seeks to highlight innovative approaches to building scalable, efficient, and secure AI infrastructures in healthcare settings. We encourage submissions from interdisciplinary teams that address the unique challenges at the intersection of AI and medicine, such as data privacy and security, model interpretability, and the integration of AI tools into clinical workflows. Additionally, we are interested in studies that assess the impact of AI technologies on patient outcomes, healthcare efficiency, and the accessibility of medical services, and devices. Hence, submissions may cover a wide range of topics including, but not limited to:

• Architectures and frameworks for deep learning in healthcare
• Research infrastructures and advanced systems for bio-data management and analysis
• Clinical decision support systems powered by AI algorithms
• Real-time data analysis for operating rooms and medical devices
• Ethical considerations and societal impacts of AI in medicine
• Data privacy and security challenges in medical AI applications
• Robot-guided surgery, visually-guided surgeon support systems
• Innovative case studies and applications of AI in medical research and patient care
• Generative AI in the context of medical data (especially imaging data)
• Integration of AI technologies into healthcare IT systems
• Evaluations of AI tools in clinical settings and their impact on healthcare delivery
• Agents and agent foundation models in medical applications
• Few-shot learning for imaging data (also for not medical data)
• Quantum computing applications in medicine
• Explainable AI for medical imaging
• Digital twins and digital transformation in medicine

This minitrack aims to bring together researchers, clinicians, and technologists to share their latest findings, methodologies, and insights on the role of AI in reshaping the medical landscapes of today and tomorrow.

Minitrack Co-Chairs:

Mikolaj Buchwald (Primary Contact)
Poznan Supercomputing and Networking Center
Polish Academy of Sciences
mikolaj.buchwald@man.poznan.pl

Monika Polczynska-Bletsos
University of California, Los Angeles
MPolczynska@mednet.ucla.edu

Alberto Paderno
Humanitas University
albpaderno@gmail.com

Cezary Mazurek
Poznan Supercomputing and Networking Center
Polish Academy of Sciences
mazurek@psnc.pl

The past several decades have ushered unprecedented advancements in body sensor networks, which include wearable, implantable and ingestible technologies to measure various aspects of health and wellness related to health and healthcare. The ubiquity of smartphones, smart watches and fitness tracking tools have provided vast amounts of digital physiologic and behavioral data that enable providers to provide personalized medicine based on each individual’s data. These new digital biomarkers of health—prosody of smartphone use, biometric data surrounding health events, geolocation and ambient environment conditions—provide an opportunity for social scientists, engineers and clinicians to advance health interventions antecedent to exacerbations of disease. Additionally, on a population health level, technologies that leverage public health infrastructure such as wastewater-based epidemiology and crowdsourced street maps are providing never before seen insights into the effects of disease in communities.

This minitrack provides an opportunity for multidisciplinary collaboration and exploration of the various facets of health technologies and their ability to inform clinical decision-making and offer personalized medicine. We encourage submissions that describe:

• Innovative technological solutions and applications in chronic disease management at the intersection of medicine and public health
• Pilot work around the real-world deployment and application of health technologies at a personal and population health level
• Research that serves to address health equity issues, promote diversity, and disseminate new technologies to resource-limited settings.
• Qualitative research that informs behavioral health theory and acceptance models around personal health technology
• Health law and ethical approaches to personal and population health disease surveillance
• Early development and boundary condition exploration of technologies to detect changes in disease or health status
• Implementation Science strategies to bridge the gap between technological advances in research and real-world clinical deployment of these technologies

Minitrack Co-Chairs:

Charlotte Goldfine (Primary Contact)
Harvard Medical School
cgoldfine@bwh.harvard.edu

Jasper Lee
Harvard Medical School
jlee333@mgh.harvard.edu

Rachel Davis-Martin
UMass Chan Medical School
rachel.davis-martin@umassmed.edu

Healthcare processes (e.g. patient pathways) and services are often very complex and can involve various parties within an organization or between organizations such as hospitals and other caregivers, as well as the patients. The design of services is often different from traditional service design—as for many healthcare services patients receive care, but insurance companies pay for it. Implementing processes in this domain should result in providing faster, safer and more effective care, necessitating organizing and sharing information among all participants involved in patient care. While the need for well-defined healthcare processes is clear, there are many obstacles and opportunities for research, including technical, behavioral, and organizational topics.

Operational Research approaches including mathematical programming and simulation modelling can help address and solve logistical challenges in designing and managing healthcare processes and services. While mathematical programming can give the optimal locations of ambulances or shift schedules for hospital doctors, for example, simulation approaches are a crucial tool to analyze different scenarios and model complex settings like emergency departments or operating rooms.

Decision support systems play a crucial role in healthcare, not only in the form of clinical decision support systems to assist physicians and other health professionals with medical decision making, but also to support logistical and organizational processes.

This minitrack will focus on the analysis, design and optimization of healthcare systems, the use of IT to support and improve care processes as well as discussions on integrated planning in healthcare and how research can improve its impact in practice.We invite papers that focus on, but are not limited to:

• Analysis and optimization of healthcare processes and services (e.g. patient pathways, appointment planning, hospital logistics, emergency medical services)
• Multi-criteria decision analysis of healthcare processes and services
• Machine learning and artificial intelligence for healthcare processes and services (e.g. demand forecasts, medical decision making)
• Design of decision support systems in healthcare
• Design and analysis of healthcare processes and services, including the design of robust processes, e.g., with respect to pandemic or crisis preparedness
  
• Simulation studies of healthcare processes and services (e.g. emergency departments, hospital logistics)
  
• Simulation-optimization approaches for healthcare processes and services
  
• Integrated decision making in healthcare, within or between care institutions and stakeholder (e.g. simultaneously scheduling surgeries and physicians, assigning emergency patients in ambulances to hospitals taking turnaround times as well as the current ED occupancy and bed availability into account)
  
• The use of technology and medical devices to support the processes and services and analysis of necessary (organizational) changes
  
• Impact-driven healthcare research and discussion how research can increase the impact in healthcare practice

Minitrack Co-Chairs:

Melanie Reuter-Oppermann (Primary Contact)
University of Twente
m.n.reuter-oppermann@utwente.nl

Cameron Walker
University of Auckland
cameron.walker@auckland.ac.nz

Nikolaus Furian
Graz University of Technology
nikolaus.furian@tugraz.at

The World Health Organization declare this decade to be the ‘Decade of Healthy Ageing.’ This poses serious challenges, given the adverse demographic effects of our aging societies, namely the decline of the number of younger people who are able and wiling to assists our aging population.

The continuous evolution of technology has led to a multi-faceted digitization of health care providing new possibilities for health and well-being for aging individuals and society at large. Innovation in patient-centered technological solutions, such as smartphone apps, health gadgets (smart watches etc.) and specific social media platforms indicate the increasing shift to self- initiated and self-coordinated health measures. These offerings aim to support the preservation of people’s physical, psychological, and social well-being, i.e. they enable longer autonomous living.

Although contemporary technologies aim to assist people in health-related aspects they often do not meet the specific needs and requirements of seniors. Hence, it becomes important to understand how and why elderly people interact with technology and how adequate tools and systems must be designed for this growing segment.

We invite papers that address the grand challenges ahead by providing insights (IS Research) and suggesting innovative solutions (Design Science Research), i.e., How can digital innovations be used to provide health related services for the aging generation?

The minitrack is open to a broad variety of research, conceptual or empirical. Topics of interest include (but are not limited to):

• Age-related digital divide in the IS discipline
• Age-related roles and stereotypes with respect to technology
• Specific IT/IS-adoption patterns of the elderly
• Online and mobile health platforms and communities for seniors
• The impact of e- and m-health, virtual communities, and social media on the well- being of seniors
• Theories and research frameworks for investigating age-related IS phenomena
• Methodological challenges of investigating elderly people’s technology usage
• Impact of technology training on technology adoption and usage
• Effective design of technology for elderly people
• Factors influencing technology/e-health/m-health adoption and usage of seniors
• Technology design factors influencing technology adoption and diffusion by seniors
• Computer and Internet self-efficacy of seniors
• Technostress experienced by elderly people
• Success factors, barriers and risks of technology adoption by seniors
• Understanding of elderly people’s technology needs and requirements
• User interface design, usability and accessibility issues
• Integration of elderly people in the design of technology
• Visions for future technologies for seniors
  Meta-analyses and meta-syntheses of research on elderly people in various IS phenomena
• Novel and innovative research on technology for seniors
• Trust and distrust of elderly people in e- and m-health
• Changes in personality characteristics and its impact on adoption of technology

Minitrack Co-Chairs:

Heiko Gewald (Primary Contact)
Neu-Ulm University of Applied Sciences
heiko.gewald@hs-neu-ulm.de

Karoly Bozan
Duquesne University
bozank@duq.edu

Doug Vogel
Harbin Institute of Technology
vogel.doug@gmail.com

Jennifer Claggett
Wake Forest University, USA
claggejl@wfu.edu

Advances in telecommunications over the past two decades have allowed care providers to consider delivery of care on a global scale with unprecedented levels of real-time awareness. Capabilities such as DaVinci have demonstrated the potential for global remote surgery under ideal conditions. New advances in satellite communications from companies such as Starlink, OneWeb, and Project Kuiper have the potential to deliver care to the most remote regions of the world. Such advances allow physicians and care providers the ability to provide near-real-time consultations, and consider patient vitals, to those who would normally have to travel hours to receive even the most rudimentary care. Increasing the scale of healthcare delivery also means increasing the scale of the attack surface available to determined nemeses. No longer are attacks limited to the premises of an enterprise; the attacker can consider cloud partners and telecommunications carriers as well. Attacks may also manifest themselves in a variety of ways from cyberattacks to jamming of radio wave communications.

This minitrack welcomes papers addressing issues that arise in the design, development, and evaluation of global telehealth networks, and on the applications optimized for use over global telehealth networks in solving real-world challenges and securely connecting clinicians and their patients. We also welcome papers identifying threats to global telehealth applications and networks as well as security implementations to mitigate such threats. Papers focusing on the use of artificial intelligence in managing path selection as well as those investigating new technologies such as 5G and 6G are of particular interest.

The following is a partial list of research topics of interest for this minitrack:

• Performance of telehealth applications over satellite communications
• Automated selection of global path and metrics driving such decisions
• Observed effects on globally deployed telehealth applications and methods for mitigation
• Network quality of service metrics for telehealth applications
• Threats to global telehealth applications to include cyberattacks and radio wave jamming
• Security mechanisms specific to the requirements for global telehealth applications
• Use of Artificial Intelligence in the detection of attacks and in automatic path reselection
• Novel applications for global telehealth networks
• Social and environmental benefits and consequences of the use of global telehealth networks and new applications.

In general, this minitrack is expansive in welcoming submissions in any area related to global networks used for telehealth applications.  Prospective authors are encouraged to contact the minitrack chairs if they seek more detailed guidance.

Minitrack Co-Chairs:

John McEachen (Primary Contact)
Naval Postgraduate School
mceachen@nps.edu

James McEachen
U.S. Air Force
james.mceachen.3@us.af.mil

Ric Romero
Naval Postgraduate School
rnromero@nps.edu

Murali Tummala
Naval Postgraduate School
mtummala@nps.edu

Persuasive systems design can facilitate behavior change around an individual’s health, a populations’ health or a healthcare organization or system. Whether to promote health management, prevent disease, or make decisions around seeking or managing care, persuasive systems can promote behavior change on a personal or societal level.

This minitrack focuses on how persuasive systems and services created to influence health behaviors are designed, developed, implemented and evaluated. These Health Behavior Change Support Systems (HBCSS) can assist behavior change through various techniques and tools, such as providing information, education or motivation through an intentional system. The minitrack highlights how persuasive theories and models can be used to develop and evaluate efficient and effective HBCSSs for different contexts, including healthcare.

As all HBCSSs are persuasive systems, designed with the intent to influence user behavior, recognition of their applicability to patient health management is growing. Designing HBCSS interventions with and building technology platforms for, the patients as end-users is a major area of research to combat health challenges and achieve the outcomes desired. Some example topics are persuasive systems created for self-care, games designed to support chronic care, how end-users can be involved in designing a system, and evaluation methods to assess the impact of a system on health behaviors.

Our minitrack presents a wide range of cutting-edge research addressing the challenges to technology use for health behavior change. The emphasis in the minitrack will be placed on both design and development of the HBCSSs, implementation and evaluation, or appraisal of their effects or artifacts. The primary focus is not purely on methodologies or technologies, but also on their impact on a population or problem. Work to further develop design protocols and rigorous, long-term research of impact for BCSS is encouraged. The topics of interest include, but are not limited to:

Design and development

• Create digital health interventions for behavior change using stakeholders’ perspectives (users and experts)
• Design of mobile technologies for health (mHealth) and mobile approaches to HBCSSs
• HBCSS development that incorporates users early on in order to tailor systems with user profiles, characteristics or preferences
• Persuasive strategies for social support
• Persuasive prompts to create engagement and involvement in serious game interventions
• Creation and testing of user profiles to identify which persuasive strategies matter most for whom
• Discussion or evaluation of design approaches for developing HBCSSs, including considerations for personalization, privacy and security
• Utilization of behavior change technique and persuasive technology for health conditions
• Ethical perspectives on health behavior change support systems
• Applications of Augmented and Virtual Reality to promote health behavior change

Implementation and evaluation

• Health behavior change through mobile technologies, teleconsultation and telemedicine
• Patient education, patient empowerment, decision support tools for patients, and remote monitoring
• Evaluation of persuasiveness of different HBCSSs (mobile, ubiquitous, ambient technologies), moving towards a checklist for practice
• Adequate design for measuring the effect of persuasive strategies on task adherence during usage and long-term effects
• Frameworks and methodologies to measure A/B/C-Changes (attitude change, behavior change, or an act of compliance)
• Profiling personalities and matching them with persuasive strategies
• Multimodal cues and measurement of the effects on adherence and outcomes
• Advanced analytics to predict adherence, and to identify usage patterns and the effects on adherence

Minitrack Co-Chairs:

Sriram Iyengar (Primary Contact)
University of Arizona
msiyengar@arizona.edu

Elena Vlahu-Gjorgievska
University of Wollonging
Elenavg@uow.edu

Khin Than Win
University of Wollongong
win@uow.edu.au

Harri Oinas-Kukkonen
University of Oulu
Harri.Oinas-Kukkonen@oulu.fi

This Minitrack delves into the intricacies of mobility-integrated health systems, where cutting-edge technologies intersect with the evolving landscape of transportation. From engine-powered vehicles such as cars, motorcycles, e-scooters, and pedelecs to non-human transportation devices like drones, our minitrack spans a spectrum of mobility modes.

Recent system research addressed healthcare applications for vehicles beyond driving assistance.Individuals can therefore take advantage of technology benefits to improve their health and well-being with monitoring systems integrated into vehicles providing long- and short-term recommendations or warnings of potential health issues. For example, the vehicles are equipped with sensors to measure vital signs such as heart rate, respiratory rate, blood pressure, body temperature, and other biomedical parameters such as electrocardiography, electro-dermal activity, skin impedance, glucose, or stress levels. In shared mobility systems, health data is subject to special privacy and security concerns as well as particularly designed analysis concerning possible regulatory aspects such as risk analysis, usability, or evidence in healthcare or well-being. Further challenges arise from sensor calibration, network connectivity, and energy efficiency.

To address changes and challenges and to promote research and new developments in the field, we invite research papers to explore a wide range of topics, e.g.:

• Healthcare systems embedded into mobility
• Health sensor systems including image/video-based health sensing
• System architectures, data platforms, healthcare ecosystems, and energy efficiency
• Acceptance and success models
• Privacy protection, security management, authentication sensors, and wireless networking
• Data analytics, data integration, and cross-domain data usage
• Artificial intelligence (AI) and explainable/understandable AI
• Shared mobility applications

We will invite outstanding papers to submit a revised version to Biomedical Engineering (DeGruyter) (Impact Factor: 1.426).

Minitrack Co-Chairs:

Thomas Deserno
TU Braunschweig and Hannover Medical School
thomas.deserno@plri.de

Christian Baumgartner
TU Graz
christian.baumgartner@tugraz.at

This minitrack focuses on the role of adoption, implementation, diffusion, and evaluation factors and the interaction of these factors at various levels to healthcare system success. These successes or failures can be on individual, group, national and international level. Papers may explore these issues for any form of healthcare technology (for example telemedicine, PACS, electronic medical records, mobile health and on-line health).This track is open to all methodologies including, but not limited to case study (business/information systems oriented), survey, experimental design, workflow and other forms of business process modeling, interview, content analysis, conceptual papers, and the various forms of quantitative analysis. In addition, we welcome innovative research focused on adoption, implementation, use, and evaluation in Healthcare Work should be at a mature (data collected and some analysis performed), though not necessarily final stages. Completed, high quality research will receive special consideration. The best papers are often fast tracked to a journal and, for other high quality papers, special issues may be created. Topics include but are not limited to:

• Application of adoption, implementation, and diffusion theories, models, and constructs to the health care context
  • Unified Technology Adoption & Use Theory (UTAUT)
  • Technology Acceptance Model and Social Learning theory
  • Diffusion of Innovation Theory
  • Information Systems Success Models
  • Theory of Planned Behavior
  • Organizing Vision and Organizational Adoption Models
  • Information Assurance constructs of confidentiality, integrity, and availability IT
• Adoption at the individual, project, organizational, or system level
  • Stakeholder analysis
  • User characteristics
  • Organizational or project structure and/or strategies
  • Regional Healthcare Initiatives and Global development
  • Interaction among individual, organizational, project, and/or system level
  • Role/impact of regulatory structures
  • Adoption of Lifestyle Apps in health
  • E-Health strategies
• IT Implementation
  • Effective implementation strategies
  • Electronic Medical Records and Personal Health Records
  • Health IT project management
  • Participation of professionals in e-health projects
  • The influence of the local system
  • Workflow analysis
  • Serious Gaming in health
• IT Use
  • Factors and models of continued use
  • Human Computer Interaction
  • Models to measure or predict Use of IT (USE IT or PRIMA)
  • Emergence of standards and process controls
  • E-Health and mobile health
  • Meaningful Use
• IT Evaluation
  • Evidence-based support of emerging healthcare technologies
  • Measures for evaluating healthcare technologies
  • Level of IT capabilities
  • Health IS success factors
  • Feasibility Analysis
  • Allied Health Professions
  • Business modeling and business cases
  • Digital innovation of healthcare

Minitrack Co-Chairs:

Ton Spil (Primary Contact)
University of Twente
a.a.m.spil@utwente.nl

Arnold Kamis
Brandeis University
akamis@brandeis.edu

Karoly Bozan
Duquesne University
bozank@duq.edu

We are currently witnessing the digital transformation of healthcare delivery. The rapid rise of a myriad of smart technology solutions are enabling more individualized health management that isboth personalized and precise. Our minitrack serves to unpack critical aspects around harnessing the power and potential of artificial intelligence and analytics to support superior person health management. We welcome research in progress or completed research papers that address technological aspects, human factors, medical challenges, socio-technical issues as well as applications, use cases, theories, and models including but not limited to:

Living Assistance and Chronic Disease Management

• Smart home technologies and assisted living
• Self-quantifying technologies to assist fitness and wellness promotion
• Mobile technologies and software solutions for personal health management and fitness
• Mobile Apps and wearables to support health and fitness monitoring
• Bio-sensors and remote monitoring solutions to support chronic disease management

Artificial Intelligence and Advanced Analytics in Health Technology

• Methodologies, models, and frameworks to support personal preventive care
• Machine learning, deep learning, and other smart analytics of individual health data
• Generative and conversational artificial intelligence to assist personal health management
• Development of mobile solutions by incorporating co-design and design science research

Legal and Ethical Considerations

• Regulatory, privacy, and security issues of personal health data
• Impact of Affordable Care, Meaningful Use and similar initiatives on design, development, adoption, and analytics of personal health technologies

Interdisciplinary and Innovative Approaches

• Integrating game design and behavioral psychology into health management
• Augmented, Mixed, and Virtual Reality to promote personal health
• Exploring the integration of various therapeutic approaches such as music, visual arts, and movement therapies with digital health applications

Minitrack Co-Chairs:

Freimut Bodendorf (Primary Contact)
University of Erlangen-Nürnberg
freimut.bodendorf@fau.de

Nilmini Wickramasinghe
La Trobe University
n.wickramasinghe@latrobe.edu.au

Mathias Kraus
University of Regensburg
mathias.kraus@informatik.uni-regensburg.de

Elliot Sloane
Villanova University
elliot.sloane@villanova.edu

Digitizing healthcare services can provide many new benefits and opportunities. However, it can also introduce new research challenges in terms of protecting the security and privacy of patient data and electronic health records. The global COVID-19 pandemic and the increasing security incidents and breaches put patient information at risk, and organizations are under pressure to enhance the credibility and reliability of the health facilities and databases they operate.

This minitrack encourages research in emerging problems and opportunities for security and privacy in healthcare. It addresses new approaches and strategies to improve the capabilities for protecting healthcare information, reducing misinformation, and fostering secured data exchange among stakeholders, facilities, and devices. Research may focus on specific areas related to themes and issues, tools and techniques, mobile health (mHealth) security and privacy, securing electronic health records, reducing health-related misinformation, mitigating risks, incident response, technical and legal issues related to the security and privacy of patient data, including data obtained through Internet of Things (IoT), cloud and mobile computing, artificial intelligence (AI), and virtual reality (VR) technologies implemented in healthcare. Topics covered by the mini-track include, but are not limited to:

• Security and privacy challenges associated with Electronic Health Records (EHR)
• Privacy concerns and ethical considerations on patients’ data
• Security and privacy risks associated with technologies such as cloud and mobile computing, Internet of Things (IoT), artificial intelligence (AI), and virtual reality (VR) for healthcare
• Mobile health (mHealth) security and privacy
• Privacy and security implications of telemedicine and remote patient monitoring
• Security and privacy risks in healthcare data sharing ecosystems
• Mitigating risks in the secondary use of healthcare data
• Reducing healthcare-related misinformation
• Incident and breach response and digital forensic readiness in healthcare
• Healthcare data breaches and their impact on patient privacy and organizations
• EHR vendor selection and management with a focus on security and privacy
• Legal issues and security regulations (e.g., HIPAA, GDPR)
• Security Education, Training, and Awareness (SETA) programs
• Emerging technologies, techniques, and algorithms for protecting patient data
• Utilization of artificial intelligence and machine learning approaches to enhance patient data protection
• Privacy-preserving technologies
• Healthcare infrastructure protection
• Theoretical foundations of security and privacy for healthcare
• Design Science Research (DSR) artifacts to promote security and privacy in healthcare

Minitrack Chairs:

Maike Greve (Primary Contact)
University of Goettingen
maike.greve@uni-goettingen.de

Miloslava Plachkinova
Kennesaw State University
mplachki@kennesaw.edu

Ace Vo 
Loyola Marymount University
ace.vo@lmu.edu

Kristin Masuch
University of Goettingen
kristin.masuch@uni-goettingen.de

According to the U.S. National Center for Health Statistics, a disease is chronic when its course lasts for more than three months. Chronic diseases and conditions, persist an entire lifetime and generally cannot be prevented by vaccines or cured by medication. This minitrack characterizes Chronic Diseases and Conditions very broadly to include, illnesses (such as diabetes, Alzheimer asthma), conditions (such as physical, sensory, mental, and cognitive disabilities, post-traumatic stress disorder, attention deficit hyperactivity disorder, autistic spectrum, Tourette syndrome, old age related conditions). Recurrent illnesses and conditions caused by chronic diseases, if not managed carefully, cannot only diminish quality of life and ability to work, but can also result in health emergencies, complications, and even death. According to World Health Organization (WHO), chronic diseases are the leading cause of mortality worldwide, and 80% of chronic disease deaths occur in low- and middle-income countries.

Advancing patients’ ability to engage in self-managed health through information and communication technologies (ICTs), such as mobile technologies and machine learning, is increasingly a top priority. Effective self-management is a proven way of improving the lives of individuals suffering from chronic diseases. Self-management refers to a care management approach in which patients actively take responsibility for treating their chronic diseases. It is a self-regulating, dynamic, continuous, interactive process. Despite technological advances in healthcare ICTs that improve care and reduce costs, patients often avoid using them. Although, ICTs have improved the health in healthcare services in terms of the delivery of high-quality patient care at low cost, but the development of ICTs that focus chiefly on patient-centered care is still in its infancy.

With that in mind, we are looking for papers taking a variety of approaches to answering research questions related to the design, development, and use of ICTs on patient-centered care. Such approaches might be described as experiments or quasi-experiments, design science, case studies, surveys, action research, psychometrics, and ethnography. We invite papers that use a variety of advanced technologies such as Virtual Reality (VR), Augmented Reality (AR), Artificial Intelligence (AI), or Machine Learning (ML). We call for papers that investigate the use of ICTs for patients with chronic physical and psychological conditions, from diabetes and asthma to obesity and fitness SM programs, to autism, dementia, bipolar disorders, and depression. Studies that investigate technologies that help patients with chronic diseases improve their health and wellness can also be submitted to this minitrack.

Authors are invited to submit papers that address issues related to the design, development, and implementation of ICTs in self-management of chronic diseases and conditions. Potential issues and topics include, but are not limited to:

• Learning about condition and health needs
• Learning self-management regimen, skills, and strategies (e.g., Monitoring and managing symptoms, side effects, and body responses, adjusting treatment regimen to manage symptoms and side effects, Managing/taking medications, Goal setting, decision making, problem solving, planning, prioritizing and pacing in the self-management process)
• Managing lifestyle changes (e.g. modifying diet, nutrition, smoking, and physical activity, changing behaviors to minimize disease impact, Balancing living life with health needs, Managing disruptions in school, work, family, and social activities)
• Managing psychological aspects of chronic diseases and conditions (e.g. Developing confidence and self-efficacy, reducing stress caused by the chronic disease, Identifying and benefiting from psychological resources drawing on intrinsic resources, e.g., creativity, strength and wisdom from past experiences, maintaining positive outlook, hope, and self-worth, Dealing with shock of diagnosis, self-blame, and guilt)
• Managing relationships with healthcare providers (e.g. Creating and maintaining relationships with healthcare providers)
• Managing and sustaining relationships with family, friends, relatives, and peers (e.g. Creating a community of peers with similar experiences, Obtaining and managing social support from family and friends)
• Cultivating courage, discipline, and motivation
• Working through issues of dependence/independence
• Seeking resources, such as financial assistance (e.g., prescription subsidies), environmental support (e.g., assistive devices), and community resources (e.g., transportation)
• Exploring and expressing emotional responses
• Making sense of the chronic disease (e.g. Finding meaning in work, relationships, activities, and spirituality)
• Identifying and confronting change and loss (e.g., changes in physical function, role, identity, body image, control, and mortality)
• Developing coping strategies (e.g., self-talk)
• Focusing on possibilities (e.g., envisioning the future, reframing adversity into opportunity)
• Designing virtual coaches
• ICT designs for elder care and home care
• ICT enabled preventative approaches

Selected papers from this minitrack will be recommended to the editors of the journal of Information Technology & People and Data Base for Advances in Information Systems for fast track review and publication.

Minitrack Co-Chairs:

Kourosh Dadgar (Primary Contact)
University of San Francisco
kdadgar@usfca.edu

Zuan Sun
Whitworth University
zsun@whitworth.edu

Social media is changing the way patients, medical practitioners, and healthcare organizations, interact. Patients use social media to create communities with similar medical concerns or diagnoses, to research health related issues, and to inform their health decisions —including selecting a doctor, researching courses of treatment and sharing experiences with online communities. Clinicians and researchers use social media to design and implement behavioral interventions for a variety of health conditions, and to study how social media shapes healthcare decisions.  Physicians use it to network professionally with colleagues and share medical knowledge within the medical community.  Healthcare providers and organizations use social media to serve their communities, patients, and physicians, while also building awareness and enhancing their brand.  Each of these uses provide opportunities to consider how social media influences health care, and to consider what data derived from social media exchanges – and which analytical methodologies – best serves this goal.

This minitrack aims to provide a venue for researchers to present current work and discuss diverse uses relating to social media in healthcare including methodological, conceptual, and design issues. It calls for research studies that: (1) describe social media communities and the mining of data from social media platforms to address health issues; (2) evaluate the design, development, and implementation of social media applications related to health; (3) assess the impact of these applications, including impacts on patients, healthcare providers, organizations, and society in general; and (4) develop theories and models to better understand the mechanisms by which social media produces impacts on healthcare and health behavior.

Research in this rapidly developing field must address key methodological questions that critically engage the following:

• How are health-related social media data appropriately accessed? What constitutes an appropriate social media data set?
• What analytic strategies or theories, both quantitative and qualitative, are optimal for analyzing social media data?
• How to best measure effectiveness, acceptability and reach of social media-delivered health education?
• What human subjects or ethical guidelines, inform the use of data obtained through social media?
• Are existing social media applications designed to produce medical, psychological or public health impacts effective, safe and acceptable?

Minitrack Co-Chairs:

Beth Bock (Primary Contact)
Brown Medical School
Beth_Bock@Brown.edu

Jordan Braciszewski
Henry Ford Health
jbracis1@hfhs.org

Young Anna Argyris
Michigan State University
argyris@msu.edu

Today’s healthcare systems are very complex involving not only connected digital systems but also systems of people, processes, policies, and societies. In such a connected system of systems, functional deficiencies arise not only from individual system performance but also from the complex interactions and interdependencies of individual systems and components. Recent World Health Report 2000 titled “Health Systems: Improving Performance” focuses on three key questions: “What makes for a good health system? What makes a health system fair? And how do we know whether a health system is performing as well as it could?” Today, a typical hospital relies on hundreds of specialized medical systems and devices that all struggle to interoperate properly. Information delay, loss, or errors rapidly propagate through the systems contributing to compounded errors, waste, poor care coordination, and serious patient harm. Furthermore, additional complexities are being introduced daily by a plethora of medical and consumer health apps, devices, and IoT products and services that are an integral part of today’s smart healthcare platforms.

This minitrack focuses on important opportunities for applying System of System Engineering (SoSE) concepts and approaches to the next generation digital healthcare enterprise. SoSE methodologies can help create new healthcare enterprises that are not only more efficient, equitable, sustainable, and humane, but are also more readily adapted to the endless evolution of science, society, and technology, and the equally endless and unpredictable emergent behaviors that all systems of systems inevitably provoke. Topics of interest (but not limited to) are as follows:

• Integration, verification, and validation of AI/ML in clinical decision support systems, clinical and patient workflow, medical and personal health devices, supply chain, logistics, and complex technology-laden systems
• Re-engineering of patient monitoring, care co-ordination, and remote care patient care innovations
• Modeling and simulation to improve critical care outcomes, patient safety, clinical efficacy, error reduction, and equitable access
• System dynamics modeling and assessment that combines both qualitative and quantitative approaches for policy evaluation
• Integration of both simulation and AI/ML models for continuum of care • IoT in healthcare interdependencies, analysis, and risk mitigation
• Economics of modeling and simulation in healthcare
• Reliability, risk mitigation, and sustainability of ever more complex healthcare systems of systems, including, for example escalating cyber threats and constant software patch requirements
• SoSE challenges and trends in healthcare, including detecting and managing emergent behaviors and unintended consequences in healthcare systems of systems

Minitrack Co-Chairs:

Vijay Gehlot (Primary Contact)
Villanova University
vijay.gehlot@villanova.edu

Elliot Sloane
Villanova University
elliot.sloane@villanova.edu

Nilmini Wickramasinghe
La Trobe University
n.wickramasinghe@latrobe.edu.au

Duane F. Wisk

New sensors, technologies, data sources, and analytics have transformed the delivery of medical care in ambulances, emergency departments, observation units and, increasingly, in the burgeoning field of ‘home hospital’ treatment.  Clinical decisions are increasingly based upon algorithms which may be derived from biased datasets.  This minitrack focuses on research and practice at the intersection of technology and acute medical care, machine learning in emergency medical environments, and the healthcare impact of bias in algorithmic medicine. We welcome original papers on these topics from researchers and practitioners, including case studies. Potential topics may include:

• Use of machine learning to optimize emergency care
• Natural language processing to improve triage accuracy
• Wearable biosensing for remote monitoring
• Preventing bias in emergency department datasets
• Preventing bias in treatment algorithms
• Methods to improve diversity in emergency care datasets
• Machine learning-driven image analysis of point of care ultrasound
• Ways to enhance diversity in healthcare data scientists working in acute care settings
• Methods to include minoritized population in emergency research

Material from this minitrack will be fast tracked for publication following peer review in Journal of the American College of Emergency Physicians Open. An opportunity for fast-tracked publication following peer review is also available in Frontiers in Disaster and Emergency Medicine.

Minitrack Co-Chairs:

Edward Boyer (Primary Contact)
Ohio State University College of Medicine
edward.boyer@osumc.edu

Guruprasad Jambaulikar
Brigham and Women’s Hospital
gjambaulikar@bwh.harvard.edu

Nicole Duggan
Harvard Medical School
nmduggan@bwh.harvard.edu

Mohammad Adrian Hasdianda
Harvard Medical School
mhasdianda@bwh.harvard.edu