Information Technology in Healthcare

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. The COVID-19 pandemic has additionally advanced these systems and now we are presented with an opportunity where digital biomarkers and personal technologies are increasingly accepted as health management tools and used in clinical decision making. 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
• Pilot work around the real-world deployment and application of health technologies at a personal and population health level
• 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

According to the 2021 FBI’s internet crime report, the healthcare industry was the critical infrastructure sector most victimized by ransomware. These attacks crippled major healthcare systems threatening thousands of patients’ lives, privacy, and security. The healthcare sector is vulnerable to many other cyberattacks, such as phishing, DDoS attacks, extorsion, and data breaches. Cybercriminals target healthcare data because of its complexity; it contains sensitive medical information, demographics, and financial information collected for medical billing making it a high-value target that can have devastating effects on public health and safety. Compared to other industries, the infantile nature of healthcare systems and networks, whether physical or virtual, may be key to the influx of cyberattacks. Other factors include outdated policies and lack of awareness and training at the organizational, employee, and patient levels.

This minitrack invites papers on a wide range of theoretical and/or analytical research related to cybercrimes in healthcare. Submissions can examine cyber security’s impact on patients, providers, or healthcare organizations. Papers may also evaluate how cybersecurity impacts care delivery in inpatient, ambulatory, or long-term care or at different treatment levels, including primary, secondary, and tertiary care. Research focusing on practical techniques and infrastructure to investigate, mitigate or eliminate cybersecurity threats is welcome. Topics of interest include, but are not limited to:

• Using machine learning and AI in detecting cyber-attacks in healthcare
• Using AI to detect employee and patient behaviors that can result in cyber-attacks
• Improving phishing detection mechanisms among healthcare professionals
• Improving awareness of cybercrimes among healthcare professionals and/or patients
• Improving system design of healthcare technologies
• Improving policies related to healthcare organizations and patients’ data
• Metadata and literature review research related to cybercrimes in healthcare
• Experimental design among patients and/or healthcare professionals

Minitrack Co-chairs:

Mohamed Abdelhamid (Primary Contact)
California State University, Long Beach
Mohamed.abdelhamid@csulb.edu

Pamella Howell
California State University, Los Angeles
phowell@calstatela.edu

The last years have highlighted the demand for efficient healthcare systems in which relevant health data are readily accessible wherever needed, whenever needed. The amount of sensitive and personal health data collected every day by a variety of mobile and medical devices (e.g., smartphones, wearables, implants) fosters the emergence of large data repositories and platforms at scale. However, it is essential to integrate and make this data accessible, such as through multisite health data sharing, so that it can be used to inform and impact care coordination, data-driven care research, and population health, create better (digital) treatments and interventions, and evaluate their risks and benefits based on real-world data.

In this context, healthcare systems frequently struggle to realize nation-wide information infrastructures and make data accessible to stakeholders who can act upon the knowledge generated from it. Beyond technological and interoperability barriers, there are challenges on the individual, organizational, legal and societal level, such as concerns to share health data openly due to fears of stigma, surveillance or potential misuse by third parties. In this context, it is critical to design health data sharing in a way that generates merit for the patient and their support network, and simultaneously preserves individual privacy and data utility, and to quickly find appropriate policies to do so while leveraging the benefits of digitization.

This minitrack invites papers on the emergence, design, evaluation, and evolution of health data ecosystems, generally defined as multi-stakeholder networks that enable value creation via platforms allowing various types of health data to be stored, shared, and reused in a secure, privacy-preserving, and FAIR manner. We welcome qualitative, quantitative, computational, and design contributions shedding light on the critical role of data and individual privacy preservation in and through healthcare platforms and ecosystems. In this context, we specifically encourage submissions that emphasize practical applicability within the healthcare environment. Topics of interest include but are not limited to:

• Data sharing and data donation in healthcare
  
• (Open) health data repositories
  
• Health data spaces and initiatives for data lofts, communities, and collectives
  
• Sustainable, circular data–driven value creation in healthcare ecosystems
• Cases on the emergence, design, and evolution of (open) data platforms in healthcare
• Design principles for privacy-preserving data platforms in healthcare
• Use of health data platforms for data-driven care research and artificial intelligence
• Openness and governance of biomedical data
• Data governance and its relation to social value
• AI-powered solutions based on (open) health data
• Patient and stakeholder engagement strategies

Minitrack Co-Chairs:

Daniel Fürstenau (Primary Contact)
IT University of Copenhagen
daniel.fuerstenau@itu.dk

Katarina Braune
Charité – Universitätsmedizin Berlin
katarina.braune@charite.de

Scott Thiebes
Karlsruhe Institute of Technology
scott.thiebes@kit.edu

Ali Sunyaev
Karlsruhe Institute of Technology
sunyaev@kit.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, 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 non-IT assets such as process changes, innovative IT artefacts, and interoperability standards. 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
• 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 (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 medical devices to support the processes and services
• Organizational change management for implementing new processes
• Impact of IT-enabled coordination of processes on patient/population health outcomes (e.g. hospital readmissions, cost efficiency)

Selected papers of the minitrack will be invited to submit an extended version to Health Systems and will be fast-tracked. Input for necessary changes and extensions will be provided by the minitrack chairs together with information on the submission process.

Minitrack Co-Chairs:

Melanie Reuter-Oppermann (Primary Contact)
Technical University of Darmstadt
oppermann@is.tu-darmstadt.de

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). 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 of 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:

Karoly Bozan (Primary Contact)
Duquesne University
bozank@duq.edu

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

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

Blood testing is one of the most common medical tests to assess various aspects of a person’s health status, informing approximately 70 percent of medical decisions. There are more than 100 types of blood tests available and there is an extremely high demand for laboratory-based blood tests, which gets further overwhelming during the pandemic. Analysis suggests an important role for digitally-enabled remote blood monitoring that would enable patients and health professionals to carry out their own tests remotely, greatly benefiting patients and speeding up decision making. The future of blood testing will lead to new digital health systems to achieve remote, inclusive, rapid, affordable and personalized blood monitoring.

This requires the development of interdisciplinary research across several relevant subject area boundaries such as: clinical science, information and communication technologies (ICT), data science and artificial intelligence, engineering and social science. For example ICT for secure data connectivity and data provenance are essential for remote and multiple parameters blood monitoring. Al and machine learning will enable automation for faster and accurate blood analysis to replace time and labor-intensive manual analysis, and will enable decentralized clinical trials with shorter times and lower costs for patient monitoring. Instead of population based blood test ranges, longitudinal blood monitoring and adaptive analytics will learn from each patient’s personalized blood value baselines, changes and trends. This will constitute a personalized approach to inform disease complexity and conditions over time for early detection and effective treatment management. Given the market demand in revolutionizing blood testing, significant research for real technologies are needed.

This minitrack aims to explore multidisciplinary approaches for digitally-enabled blood testing for remote monitoring and personalized analytics. It will consider both research in progress and completed working papers in the related topics. We have identified the following groups and topics but not limited to:   

• “Why” digitally-enabled blood testing: current gaps in blood testing and how it can improve or leapfrog
  • Unmet needs in health and wellbeing, healthcare and quality, efficiency and cost-saving
  • Review of current healthcare practice, gaps and opportunities of diagnostic testing and monitoring
  • Review of existing technologies, gaps and opportunities for digitally-enabled blood testing

• “What” enables digitally-enabled blood testing, and “How” to achieve this responsibly in healthcare
  • Affordable and portable blood remote monitoring devices
  • Mobile health and ICT for connected diagnostics
  • Privacy and security in remote blood monitoring
  • Decentralized blood testing and monitoring
  • Federated learning and edge computing for remote blood monitoring and analysis
  • Digital pathology
  • AI and machine learning-based testing analysis
  • Diagnostic testing automation and robotics
  • Personalised analytics using longitudinal blood monitoring data
  • Multimodal testing, monitoring and health record data processing and decision support
  • Public perceptions, trustworthiness and regulations of remote blood monitoring
  • Interoperability and standards for data connectivity between point of blood testing/monitoring and hospitals systems
  • Adoption, user acceptance, human, organisation and policy factors

• Healthcare applications of digitally-enabled blood testing today and future in the following areas but not limited to:
  • Prevention, early detection, improved diagnostics, treatment monitoring and personalisation
  • Efficiency improvement and capacity augmentation
  • Chronic disease management and selfcare and self-management
  • Clinical research and clinical trials
  • Evaluation of early adoptions

We will work with Journal of Medical Internet Research (JMIR) to create a theme issue on “Digitally Enabled Blood Testing”. We will select best papers from the minitrack and invite authors to submit a full paper to the theme issue. Minitrack chairs will be the guest editors of the theme issue.

Minitrack Co-Chairs:

Weizi Vicky Li (Primary Contact)
University of Reading
Weizi.li@henley.ac.uk

Kendall Ho
University of British Columbia and Vancouver General Hospital
kendall.ho@ubc.ca

Samantha Kanza
University of Southampton
s.kanza@soton.ac.uk

Hector Zenil
University of Oxford
hector.zenil@cs.ox.ac.uk

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 behaviour 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
• Implementation and evaluation
  • Health behaviour 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

Best papers from the Health Behaviour Change Support Systems minitrack will be invited to submit a significantly extended version (min. +30%) of their paper for consideration to the Special issue in Health Informatics Journal.

Minitrack Co-Chairs:

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

Amanda Blok
University of Michigan
acblok@umich.edu

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

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

Engine-powered personal vehicles include not only cars and motorcycles but also increasingly electrical vehicles like e-scooters and pedal electric cycles (pedelecs). Therefore, the number of people using such devices as well as the individual utilization time increases. E.g., the elderly shift their primary way of mobility from bicycles to pedelecs whereas the young use applications for shared mobility with e- scooters and other personal vehicles as their primary means of transportation.

Recent research addressed healthcare applications for personal vehicles beyond driving assistance, e.g., for levels 3 to 5 of autonomous driving. Individuals can therefore take advantage of technology benefits to improve their health and well-being with monitoring systems integrated into personal vehicles providing long- and short-term warnings of potential health issues. Therefore, the vehicles are equipped with sensors to measure vital signs such as heart rate, respiratory rate, blood pressure, body temperature, and other biomedical parameters like electro-dermal activity or glucose level. In shared mobility applications, health data is subject to special privacy and security concerns as well as particularly designed analysis. 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.:

• Health sensors configuration and coupling, signal/sensor fusion, digital imaging for health sensing, and hardware technologies
• 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

Michael Breitner
Leibniz University Hannover
breitner@iwi.uni-hannover.de

Andreas Rausch
TU Clausthal
ndreas.rausch@tu-clausthal.de

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 minitrack 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. 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. 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

As we move into a post COVID world healthcare delivery is recalibrating service delivery and reaching a new steady state. This new dawn brings with it a tremendous reliance on digital health solutions including Apps, platforms, mobile solutions, and telehealth initiatives. Moreover, analytics, artificial intelligence and machine learning are becoming key enablers for supporting superior health and wellness management. Hence, today, empowering patients and focusing on patient centered care delivery is more critical than ever before.

Digital health solutions are a key enabler in this regard with mobile Apps, wearables, and individualized services dramatically influencing how patients and their families can manage health and wellness. Further, they have the potential to facilitate and enhance superior healthcare delivery by clinicians and caregivers as well as assist in addressing many of the challenges currently facing healthcare delivery in all OECD countries. Moreover, these solutions foster active patient participation in their care as well as promote self-management of wellness and fitness; essential aspects in managing chronic diseases. In addition, the data collected from these solutions have the potential to enable sophisticated services for self-care, sustainable wellness management and value-based care to ensue. This is an exciting time for health and wellness management as a new normal is being defined.

This minitrack focuses on how such technologies and digital services might be utilized to address the challenges currently facing healthcare delivery such as managing the impacts of the COVID-19 pandemic, escalating cost pressures, a growing aging population, an increasing prevalence of chronic diseases and a move to a preventive care focus. Integral to these approaches is a patient-centric view in order to satisfy consumer expectations, provide high quality care, and improve wellness. This minitrack provides an outlet for all research focused on health and wellness related mobile technologies, applications, and services.

This minitrack is highly interdisciplinary and brings together attendees interested in technical solutions, behavioral aspects, medical impacts, and business value of personal health and wellness management. It also brings together theory and practice by presenting scientific concepts and methods as well as empirical investigations and case studies. We welcome research in progress or completed research papers that address technological aspects, socio-technical issues and/or process issues, applications, use cases, theories, and models as well as other critical issues, including but not limited to:

• Mobile technologies, portals and software solutions for personal health management and fitness/wellness
• Mobile Apps and wearables to support health and fitness monitoring
• Technologies and services to manage epidemics, pandemics, and health crises
• Self-quantifying technologies to assist fitness and wellness promotion
• Self-management of recovery processes and compliance control
• Personal health records and fitness trackers
• Advanced analytics of individual health and wellness data
• Augmented, Mixed and Virtual Reality to promote personal health
• Smart home technologies and assisted living
• Bio-sensors and remote monitoring solutions to support superior chronic disease management and wellness management
• Methodologies, models, and frameworks to support personal preventive care
• Development of mobile solutions by incorporating co-design and design science research methodologies
• Cost-effective concepts to foster patient centric healthcare
• 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

Minitrack Co-Chairs:

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

Nilmini Wickramasinghe
Epworth Health Care and Swinburne University of Technology
nwickramasinghe@swin.edu.au

Tuan Huy Ma
Fujifilm Europe GmbH
tuan.huy.ma@fujifilm.com

Process mining has recently gained increasing attention in information science as a set of concepts, methods, and techniques to analyze the execution of business processes. In traditional application domains of business process technology, including finance and electronic commerce, process mining provides insights into how exactly business processes are performed. Since then, process mining has experienced an explosion of its use to other more novel application scenarios, including logistics, public administration, and, more prominently, healthcare.

In this minitrack, we intend to provide a forum for researchers and practitioners to discuss novel ideas in the area of process mining in healthcare environments. We believe that the topic is scientifically interesting and practically relevant. The topics of the minitrack include but are not limited to the following aspects:

• Data quality and data preparation for process mining in healthcare
• Event log generation in healthcare environments
• Data privacy in healthcare
• Process mining for interleaving treatment processes
• Healthcare processes in the age of pandemics
• Discovery and analysis of patient treatment processes
• Healthcare process analytics
• Care pathway construction and analysis
• Formalization of medical knowledge and reasoning
• Process conformance and clinical guidelines
• Healthcare procedures training, assessment, and feedback
• Data-driven compliance analysis for health care processes
• Healthcare information, systems, and architectures
• Logistics processes in healthcare
• Processes in the development, production, and provision of medication
• Human-in-the-loop approaches to process mining in healthcare
• Methods and frameworks to deploy process mining in healthcare

Minitrack Co-Chairs:

Niels Martin (Primary Contact)
Hasselt University
niels.martin@uhasselt.be

Mathias Weske 
University of Potsdam
mathias.weske@hpi.de

Luise Pufahl
Technical University of Munich
luise.pufahl@posteo.de

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 minitrack 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
• Mitigating risks in Healthcare Information Technology
• 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:

Miloslava Plachkinova (Primary Contact)
Kennesaw State University
mplachki@kennesaw.edu

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

Maike Greve
University of Goettingen
maike.greve@uni-goettingen.de

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 variety of advanced technologies such as Virtual Reality (VR), Augmented Reality (AR), Artificial Intelligence (AI), or Machine Learning (ML). We call for the papers that investigate 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 life style 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 for fast track review and publication. There will also be opportunities to fast track papers from this minitrack to the journal of Data Base for Advances in Information Systems.

Minitrack Co-Chairs:

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

Bahae Samhan
Illinois State University
bmsamha@ilstu.edu

K.D. Joshi
University of Nevada, Reno
kjoshi@unr.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 provides a venue for researchers to present current work and discuss diverse uses relating to social media in healthcare including methodological, conceptual, and design issues. Papers will include research studies that:

• describe social media communities and the mining of data from social media platforms to address health issues;
• evaluate the design, development, and implementation of social media applications related to health;
• assess the impact of these applications, including impacts on patients, healthcare providers, organizations, and society in general; and
• 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, we therefore welcome submission 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
Center for Health Policy and Health Services Research, Henry Ford Health System
jbracis1@hfhs.org

Cumulative psychological stress, factoring in both the number of acute stressful events and periods of chronic stress, is routinely correlated with adverse health outcomes. Human stress responses comprise the various cognitive, emotional, and physiological reactions that stressors can elicit. Accurately measuring stress is therefore vital to the mitigation and treatment of stress- related pathologies, including trauma. In a subjective fashion, patients can self-report their stress levels using various self-report scales (e.g. SRRS or Hassles Scale). However, despite this association between stress, health outcomes and overall well-being, stress and health researchers have struggled to devise and implement quantitative, objective, and practical measures to assess stress levels that function in diverse patient populations.

In this minitrack, we provide an open forum to discuss novel methods and technologies for the accurate and real-time detection of human psychological stress to be used in conjunction with existing self-report scales. Such technologies can feature wearable devices that measure verified biomarkers of interest and function with or without intervention from the patient or researcher. We further welcome papers that focus on the treatment of stress and trauma utilizing novel methods or technologies. Topics of this minitrack include but are not limited to:

• Stress biomarker discovery and validation
• Sensor development for quantitative detection of stress
• Proof-of-concept platform construction for patient use
• Patient and population-level data collection and processing
• Novel methodologies and/or technologies for treating stress and stress-related pathologies
• Qualitative research improving on existing or developing novel self-report scales

Minitrack Co-Chairs:

Daniel Roxbury (Primary Contact)
University of Rhode Island
roxbury@uri.edu

Nina Ayala
Brown Medical School
Nina_ayala@brown.edu

Beth Bock
Brown Medical School
beth_bock@brown.edu

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 cardiopulmonary resuscitation
• Drone-delivered antidotes in rural environments
• Bystander acceptability of drone-delivered antidotes to reverse overdose
• Natural language processing to improve triage accuracy
• Wearable biosensing to assess analgesia delivered in ambulances
• Preventing bias in emergency department datasets
• Preventing bias in treatment algorithms
• Methods to improve diversity in emergency care datasets
• Wearable biosensing to detect racial bias in analgesic dosing
• Machine learning-driven image analysis of point of care ultrasound
• Ways to enhance diversity in healthcare data scientists working in acute care settings

Material from this minitrack will be fast tracked for publication following peer review in Journal of the American College of Emergency Physicians Open.

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

Andrew Goldsmith
Brigham and Women’s Hospital
ajgoldsmith@partners.org