"The work program starts from a topic raised by the student's intellectual interest, a topic that will be addressed according to a customized program of work to be agreed with the supervisor. Notwithstanding this, the work to be done must materialize in a ""paper"" containing:
1.The formulation of a question or a problem, theoretically capable of having an appropriate response through the mobilization of scientific research methodology.
2.A review of the theoretical issues underlying the question above, obtained through research, analysis and critical interpretation of the latest internationally accepted scientific literature.
3.In coordination with the earlier theoretical balance, the dissertation must contain an exercise (theoretical and / or empirical) that complements an innovative way to approach the topic under investigation.
4.Finally, the dissertation must contain a conclusive synthesis answering the research starting point, as well as suggestions for further research"

"The evaluation of the CU process will be through the public discussion of the dissertation presented by the student, conducted by a panel.
The final rating (0 to 20) will be assigned by the panel, given the academic quality of written work presented (especially the relevance, originality and consistency of theoretical and methodological shown), as well as the student's performance during the presentation and discussion of the text."

Mandatory

"The bibliography adopted results from the survey conducted by the students themselves, taking into account the ""Question of Departure"" that guides the work of each student. Special attention should be given to bibliographical information provided by the Advisor."

Optional

"The work program is based on a topic of intellectual interest to the student, which will be approached according to a personalized work program to be agreed with the supervisor. However, the work to be carried out must materialize in a written document based on a pre-defined template containing:
1. The formulation of a question or problem (identification of objectives), theoretically susceptible of obtaining an adequate answer through the mobilization of a scientific research methodology.
2. Definition of the requirements and initial starting conditions.
3. The work must respond to a practical need in the area of health.
4. Finally, the project must contain a concluding summary that responds to the objectives identified, as well as suggestions for future research."

The evaluation of the CU process will be through the public discussion of the dissertation presented by the student, conducted by a panel.
The final rating (0 to 20) will be assigned by the panel, given the academic quality of written work presented (especially the relevance, originality and consistency of theoretical and methodological shown), as well as the student's performance during the presentation and discussion of the text.

Mandatory

Optional

PC1: Ethics in the Health Field
Ethics, conduct, and integrity in healthcare.
Ethical theories and moral decision-making: virtue ethics, utilitarianism, deontology, and principles approach.
Ethical issues and dilemmas in healthcare.
Codes of ethics and responsibilities of healthcare professionals.

PC2: Ethics and Research in the Health Field
Research involving human subjects: Belmont Report, WMA Declaration of Helsinki, principles, and practical guidance.
Clinical trials regulation in the EU and Portugal.

PC3: Privacy and Data Protection in the Health Field
GDPR: principles, definitions, lawfulness of processing, special categories of personal data, data subject rights.
Data processing for health, safety, and scientific research.
Anonymisation and pseudonymisation techniques.

PC4: Ethical Issues of Digitalization, Data Science, and AI in Healthcare.

PC5: Digital Health Policies in Portugal and the European Union.

1. Class participation and discussion: 20%
2. Assignments and projects: 50%
3. Midterm exam: 15%
4. Final exam: 15%

Mandatory

"A Preliminary Opinion on data protection and scientific research, The European Data Protection Supervisor, 2020. https://edps.europa.eu/sites/default/files/publication/20-01-06_opinion_research_en.pdf. Principles of Biomedical Ethics (7th edition); Tom L. Beauchamp e James F. Childress; Oxford University Press, 2013. Proposal for a Regulation of the European Parliament and of The Council Laying Down Harmonised Rules on Artificial Intelligence (Artificial Intelligence act) and Amending Certain Union Legislative Acts, 2021, https://eur-lex.europa.eu/legal-content/PT/TXT/?uri=CELEX%3A52021PC0206. The EDPB-EDPS Joint Opinion 03/2022 on the Proposal for a Regulation on the European Health Data Space, 2022. The handbook on European Data Protection Law, edited by The Council of Europe (CoE) and the European Court of Human Rights (ECtHR), 2018.

Optional

CP1.Introduction to Health Information Systems and Data: Overview of health information management. Importance of health data for healthcare provision and decision-making. Introduction to health information systems and electronic health records (EHRs)
CP2: Health data collection and standards.
CP3. Data interoperability in healthcare.
CP4. Health data management and analysis.
S5. Clinical decision support systems (CDSS)
CP6. Implementation of Health Information Systems: Selection and acquisition of systems. System implementation methodologies.
Change management and user adoption strategies.
CP7. Future trends in health data and information systems: Big data and analytics in healthcare. Artificial intelligence and machine learning in health data analysis. Personalized medicine and precision computing in healthcare.

The teaching-learning methodology of the UC is active. The student is the main responsible. There is an incentive to develop the capacity to absorb content autonomously, through the analysis of literature and practical cases, use and critical discussion of digital content, thus mixing theoretical content taught in personal participation, and individual and group projects. In theoretical classes, structural and conceptual bases are presented and the work is aligned with the learning objectives. The course follows a project-based continuous assessment model throughout the semester due to its highly practical nature, and does not include a final exam.

Mandatory

Jossey-Bass. Robson, W. (1996), Strategic Management and Information Systems: An Integrated Approach, (2nd ed), FT Management; Bourgeois, D. T. (2014), Information Systems for Business and Beyond, S.l.: Lulu.com Ammenwerth, E., de Keizer, N., & Brender, J. (2011). Introduction to health information systems. Springer.
Wyatt, J. C. (2010). Health information systems: Challenges of the new millennium. J of the American Medical Informatics Association, 17(3), 263-266. Fridsma, D. B., & Altman, R. B. (2013). A practical approach to big data in health care : Strategies for getting to know your data. Journal of the American Medical Informatics Association, 20(1), 111-116.
Wager, K. A., Lee, F. W., & Glaser, J. P. (2017). Health care information systems: A practical approach for health care management (4th ed.).

Optional

Introduction to health resource management
Healthcare financing and budgeting
Understanding the financial aspects of healthcare and mastering budgeting strategies for sustainable healthcare systems
Resource allocation strategies
Inventory management and supply chain optimization
Enhancing inventory management and optimizing supply chains to ensure efficient resource utilization in healthcare settings
Human resource management in healthcare
Developing effective human resource management strategies to optimize healthcare workforce performance.
Technology utilization for resource efficiency
Exploring innovative technologies to enhance resource efficiency in healthcare operations.
Quality improvement and cost-effectiveness
Implementing quality improvement strategies to achieve cost-effective healthcare outcomes.
Ethical considerations in resource allocation
Exploring ethical dilemmas and decision-making in the equitable allocation of limited healthcare resources.

Online Quizzes: Regular online quizzes can be used as a formative assessment method to evaluate students' understanding of key concepts and principles in resource management.
Case Study Analysis: Assigning case studies related to resource management in the health sector can assess students' ability to apply their knowledge and skills in real-world scenarios.
Group Project: Engaging students in a collaborative group project focused on resource management can assess their ability to work in teams and apply their knowledge and skills collectively. The course follows a project-based continuous assessment model throughout the semester due to its highly practical nature, and does not include a final exam.

Mandatory

Health Costs And Financing: Challenges And Strategies For A New...by David Blumenthal and Sara R. Collins. Health Affairs, 2020. Priorities and challenges for health leadership and workforce … by James Buchan and Gail Tomblin Murphy. BMC Health Services Research, 2019. Strategic Human Resource Management in Health Care: by Ronald J Burke and Cary L Cooper. Advances in Health Care Management, 2010. World Health Organization. Global strategy on human resources for health: workforce 2030. Geneva: World Health Organisation; 2016. Reich MR, Javadi D, Ghaffar A. Introduction to the special issue on “effective leadership for health systems”. Health Syst Reform. 2016;2(3):171–5. Senkubuge F, Modisenyane M, Bishaw T. Strengthening health systems by health sector reforms. Glob Health Action. 2014;7(1):23568. Tricco AC, Langlois EV, Straus SE. Rapid reviews to strengthen health policy and systems: a practical guide. Geneva, Switzerland: World Health Organization; 2017.

Optional

Introduction: Course overview, objectives, and expectations. Importance of managerial and entrepreneurial skills in healthcare

Innovation Theory and Practice: Theoretical foundations of innovation in healthcare. Strategies for fostering and managing innovation in healthcare organisations

Business Setting and Digital Marketing: Digital marketing and effective management techniques for healthcare enterprises.

Pitching: Developing presentation skills for effective pitching

Social Innovation: Exploring social innovation initiatives in healthcare.

Social Enterprises: Analysing successful social enterprise models in healthcare.

Cases and Exercises: Analysing real-world cases and exercises in healthcare management.

Business Planning Labs: Practical workshops for developing comprehensive business plans. Applying business planning methodologies and tools in healthcare.

Presentation of the Business Plan: Presenting and defending business plans. Feedback and opportunities for improvement.

The assessment of students includes the evaluation of a group-based business plan, which serves as a comprehensive measure of their understanding and application of the course concepts.
The assessment methods utilized are a report and a laboratory assignment. The report serves as both a formative and summative assessment, allowing students to demonstrate their knowledge, analysis, and critical thinking skills in presenting their business plan. The laboratory assignment provides a formative assessment opportunity, allowing students to apply their learning in a practical setting and receive feedback for improvement. The course follows a project-based continuous assessment model throughout the semester due to its highly practical nature, and does not include a final exam.

Mandatory

Karagiannis, H.G. – Bakouros, I.L. (2010) "Innovation and Entrepreneurship: Theory - Practice" Sophia Publications. David Dawkins and Mark Freel (2007) "Entrepreneurship" Kritiki Publications. Piperopoulos, G.P. (2008) "Entrepreneurship, Innovation & Business Clusters", 2nd Edition, Thessaloniki: Sakkoulas Publications. Chatzikonstantinou, G., Goniadis, I. (2009) "Entrepreneurship and Innovation", Gutenberg Publications. Supplementary electronic notes are also distributed for free on elearning.auth.gr.

Optional

Course Topics:
PC1: Introduction to Digital Transformation in Healthcare Management
PC2: Health information systems and interoperability
PC3: Telehealth technologies and applications
PC4: Data-driven decision-making in healthcare
PC5: Importance of patient engagement in healthcare
PC6: Managing digital transformation projects
PC7: Privacy and security of healthcare data
PC8: Analysis of successful digital transformation initiatives in healthcare organizations
PC9: Data analytics exercises using healthcare datasets
PC10: Blockchain and its applications in healthcare
PC11: Addressing interoperability challenges

The course will be delivered through a combination of lectures, case studies, discussions, and student-led presentations. Students will be required to complete individual assignments and a group project that involves designing an interoperability solution using emerging technologies. The course follows a project-based continuous assessment model throughout the semester due to its highly practical nature, and does not include a final exam.

Mandatory

Digital Health Technologies: The Future of Health Care. Academic Press.
The Role of Digital Transformation in Health Care Service Delivery. In Digital Transformation in Healthcare (pp. 1-19). Springer.
Healthcare Transformation: A Guide for the Hospital Board Member. CRC Press.
Health Informatics: An Interprofessional Approach (2nd ed.). Elsevier.
Deep Medicine: How Artificial Intelligence Can Make Healthcare Human Again. Basic Books.
Health Care Information Systems: A Practical Approach for Health Care Management. Jossey-Bass.

Optional

The course starts with a pre-assignment in which students analyze and describe their home country's health and wellbeing systems. The joint sessions start with a flipped classroom approach, in which students will present their findings in class. During joint sessions, students will then discuss key differences and similiarities between countries. The course also includes lectures by external professionals within the health and wellbeing sector. During the course, students will do a project in groups. This group work project consists of an interview with a health and wellbeing sector professional, with the aim of mapping challenges and possibilities related to digitalization. he interviewee can a person be from the public, private, or third sector in the health sector. In an individual assignment, students write an essay where they synthesize their learning. The essay includes an assessment of how different health and well-being systems can respond to different health objectives.

Students will be assessed based on individual (60%) and group (40%) assignments. The course follows a project-based continuous assessment model throughout the semester due to its highly practical nature, and does not include a final exam.

Mandatory

International (e.g. UN) comparative material of health care systems and models in different countries. Organizational structure of health care systems. Objectives of health care systems. https://health.ec.europa.eu/state-health-eu/country-health-profiles_en International (e.g. UN) comparative material of health care systems and models in different countries. Organizational structure of health care systems. Objectives of health care systems. https://www.eu-healthcare.fi/know-your-rights/legislation Latest research artcles published in this area.

Optional

PC1: Different models of well-being production, including institutional, neoliberal, populist, and residual welfare state regimes.
PC2: Various visions of digital transformation in health and well-being.
PC3: Examples of product implementation and roadmaps for digital service pathways.
PC4: Well-being, its promotion, and prevention as a concept.
PC5: EU values and fundamental rights within the EU and its member states.
PC6: National and EU-level structures for EU policy-making and regulations.
PC7: Regulatory frameworks for EU health and well-being digitalisation.
PC8: EU health and welfare digitalisation regulatory frameworks.
PC9: Perspectives of public and private health and well-being service providers, the third sector, and health technology companies on collaborative change in digital transformation.
PC10: Concrete steps for implementing digital health and well-being applications, considering existing regulations and institutional structures.

The study unit is evaluated with points (maximum 100). Students need to get at least 50 points (50%) to pass the study unit. Each university will change the points to the grades based on their own grading system. The evaluation grading is based on home univesity crading. Assessment: exercises / problems performed in group, during the course classes (30%), and an group assignments in the performed at the end of the course (70%).
The course follows a project-based continuous assessment model throughout the semester due to its highly practical nature, and does not include a final exam.

Mandatory

Yörük, E., Öker, I. & Tafoya, R.T. 2022. The four global worlds of welfare capitalism: Institutional, neoliberal, populist and residual welfare state regimes. Journal of European Social Policy 32(2), 119-134. https://european-union.europa.eu/priorities-and-actions/actions-topic/health_en European Health Union (europa.eu) Public health - EUR-Lex (europa.eu) https://eur-lex.europa.eu/summary/chapter/public_health.html?root_default=SUM_1_CODED=29 https://health.ec.europa.eu/medical-devices-sector/new-regulations_en National relevan legislation from Finland, France, Greek and Portugal Example: https://www.eu-healthcare.fi/know-your-rights/legislation/ Värri, A. O. (2023). The impact of EU Digital Services Act and Digital Markets Act on health information systems . Finnish Journal of EHealth and EWelfare, 15(1), 67–76. Ministry of Social affairs and Health https://stm.fi/en/wellbeing-services-counties

Optional

Bertin G., Carrino L. & Pantalone M. (2021) Do standard classifications still represent European welfare typologies? Novel evidence from studies on health and social care. Social Science & Medicine,Volume 281,2021, 114086, ISSN 0277-9536,https://doi.org/10.1016/j.socscimed.2021.114086. Kawiorska D. (2016) Healthcare in the light of the concept of welfare state regimes - comparative analysis of EU member states. Oeconomia Copernicana. 2016;7(2):187-206. https://doi.org/10.12775/OeC.2016.012. Collington R. (2022) Disrupting the Welfare State? Digitalisation and the Retrenchment of Public Sector Capacity. New Political Economy, 27:2, 312-328, DOI: 10.1080/13563467.2021.1952559 https://topl.hee.nhs.uk/The Lost and the New ‘Liberal World’ of Welfare Capitalism: A Critical Assessment of Gøsta Esping-Andersen's The Three Worlds of Welfare Capitalism a Quarter Century Later https://www.cambridge.org/core/journals/social-policy-and-society/article/lost-and-the-new-liberal-world-of-welfare-capitalism-a-critical-assessment-of-gosta-espingandersens-the-three-worlds-of-welfare-capitalism-a-quarter-century-later/4580DFDBE02493BA798D846B217143C5 Shapes 2022. Ecological Organisational Models of Health and Care Systems for Ageing https://shapes2020.eu/wp-content/uploads/2022/01/D3.1-SHAPES-Ecological-Organisation-Models-07-Dec-2020.pdf Shapes 2022. Scaling-up Improved Integrated Care Service. https://shapes2020.eu/wp-content/uploads/2022/01/D3.2_Scaling-up-Improved-Integrated-Care-Delivery-V1_v1.0.pdf

Introduction to Science and Technology Studies (STS)
Course overview: Presentation of key STS concepts such as symmetry, sociotechnical controversies, and the social construction of technology.
Knowledge production in medicine: Examine transformations from the 1970s-80s, including molecularization, biotech advances, clinical trials, and genomics.
Medical expertise: Explore the evolution of medical expertise, including the rise of agencies, medical activism, and knowledge co-production.
E-health worlds: Understand the development, politics, and impact of e-health, focusing on the Global South.
Big Data and Medicine: Define medical data and explore issues related to data politics, innovation, and labor transformation.
Gender and Medicine: Investigate gender inequalities and the role of science in gender assignment.
Technoabilities: Explore technology’s role in disability.
Restitution: Present and discuss student projects.

Online Quizzes: Regular online quizzes can be used as a formative assessment method to evaluate students' understanding of key concepts and principles in resource management.

Reading, summarizing and illustrating a scientific article. Each session will be introduced by a group of students responsible for presenting a key text for the session and illustrating it with a concrete case study.

Group Investigation: Engaging students in a collaborative group investigation focused on analyzing a medical controversy or studying the socio-technological trajectory of a medical device or therapy.

The course follows a project-based continuous assessment model throughout the semester due to its highly practical nature, and does not include a final exam.

Mandatory

"Barnes, L., Hall, P. A., & Taylor, R. C. R. (2023). The Structural Sources of Socioeconomic Inequalities in Health: A Cross-National Perspective. Socius, 9. Deivanayagam, T.A et al. (2023), “Envisioning environmental equity: climate change, health, and racial justice”, The Lancet, 402: 64-78. Iyver H et al. (2021), “Sustaining planetary health through systems thinking: Public health’s critical role”, SSM – Population Health, 15: 100844. Lee, S, Sang Chul Lee & Yung Ho Suh (2016) Technostress from mobile communication and its impact on quality of life and productivity, Total Quality Management & Business Excellence, 27:7-8, 775-790 OECD (2019b), How’s Life in the Digital Age?, OECD Publishing, pp. 11-29 Sachs, J.D., et al. (2019) Six transformations to achieve the Sustainable Development Goals. Nature Sustainability 2: 805–14. Wilkinson, R. G., and Pickett, K. E. (2017) The enemy between us: The psychological and social costs of inequality. Eur. J. Soc. Psychol., 47: 11–24. "

Optional

"Bardzell, S., et al. (2012). Critical design and critical theory: the challenge of designing for provocation. Proceedings of the Designing Interactive Systems Conference. Newcastle Upon Tyne, United Kingdom, Association for Computing Machinery: 288–297. Manzini, Ezio. Politics of the Everyday. London: Bloomsbury Visual Arts, 2019. Print. OECD (2020) How’s Life? 2020: Measuring Well-being. OECD Publishing, pp.103-115. OECD (2023), Health at a Glance 2023: OECD Indicators, OECD Publishing, pp.33-58. Pickett, Kate E., Richard G. Wilkinson, (2015), Income inequality and health: A causal review, Social Science & Medicine, 128: 316-326. Stickdorn, M. (2018). This Is Service Design Doing. O'Reilly Media, Inc. Yu, E. (2017). A reflection on and Suggestion of Service Design Processes: from Activity-Centered Descriptions toward Outcome-Oriented Demonstrations. Archives of Design Research, 30(1), 25-39. "

S01. Introduction to Cybersecurity in Healthcare
S02. Security Fundamentals for Health Systems
S03. Risk Assessment and Management in Health Systems
S04. Network Security in Health Systems
S05. Application Security in Health Systems
S06. Data Privacy and Confidentiality in Health Systems
S07. Incident Response and Disaster Recovery in Health Systems
S08. Threat Detection and Prevention in Health Systems
S09. Secure Cloud Computing in Health Systems
S10. Medical Device Security
S11. Security Governance and Compliance in Health Systems
S12. Emerging Trends and Future Directions in Healthcare Cybersecurity

Periodic Assessment:
- Group labs (50%) (max. 3 students per group) [minimum score of 10 points for each lab]
- Two individual tests (50%) [minimum score of 6 points for each test] (1 test during the semester, the other on the 1st season date)
Students should attend a minimum of 50% of classes to be able to do the periodic assessment.
The course follows a project-based continuous assessment model throughout the semester due to its highly practical nature, and does not include a final exam.

Mandatory

Ayala, L. (2016). Cybersecurity for Hospitals and Healthcare Facilities: A Guide to Detection and Prevention. Apress. Hernandez, S. (Ed.). (2014). Official (ISC)2 Guide to the HCISPP CBK (1st edition). Auerbach Publications. Herzig, T. W. (2010). Information Security in Healthcare: Managing Risk (1st edition). HIMSS Publishing. Herzig, T., & Walsh, T. (2013). Implementing Information Security in Healthcare: Building a Security Program (1st edition). HIMSS Publishing. Johnson, C. B. (2023). HIPAA Privacy & Security Compliance for Healthcare Administrators. Independently published. Koontz, L. (2021). Information Privacy in the Evolving Healthcare Environment (2nd edition). CRC Press. MBA, T. W. Y. T. Y. C. C. M. S., & MacAlister, D. (2015). Hospital and Healthcare Security (6th edition). Butterworth-Heinemann. Ogu, E. C. (2021). Cybersecurity for eHealth: A Simplified Guide to Practical Cybersecurity for Non-Technical Healthcare Stakeholders & Practitioners (1st edition). Routledge.

Optional

Robichau, B. P. (2014). Healthcare Information Privacy and Security: Regulatory Compliance and Data Security in the Age of Electronic Health Records (1st ed. edition). Apress. Tan, J. (2019). Adaptive Health Management Information Systems: Concepts, Cases, and Practical Applications: Concepts, Cases, and Practical Applications (4th edition). Jones & Bartlett Learning. Murphy, S. P. P. (2015). Healthcare Information Security and Privacy (1st edition). McGraw Hill.

CP1: Foundations of AI in Health (1 ECTS)
• Introduction to Health Informatics and its significance in healthcare
• History of Artificial Intelligence
• Basics of Artificial Intelligence and Machine Learning
• Ethical and Regulatory Considerations in AI for Health
CP2: Setting up the working Environment (1 ECTS)
• Creation of Working Directories
• Install the tool Orange.
• Install BERT (R Excel Toolkits)
CP3: Data Pre-processing (1 ECTS)
• Data Collection
• Data Preparation
• Data Cleaning
• Data Validation
CP4: Machine Learning Algorithms (1 ECTS)
• Supervised, Unsupervised, and Reinforced Learning
• Evaluation Metrics
• Utilisation of the dataset in the tool Orange
CP5: Applications (2 ECTS)

"Evaluation Parameters:
Total: 100 points

Assignment 1: Write a report on the basic algorithms used in AI with at least five scientific journal references (20 points)

Assignment 2: Extract some statistical features from the data and do some visualization of the data (20 points)

Quiz 1: A quiz to check the basics of AI (10 points)

Quiz 2: To Check the knowledge of the algorithms from different use case scenarios. (10 points)

Project Completion: (40 points)

Open Discussion: About a notion of application of ML in the healthcare sector

The course follows a project-based continuous assessment model throughout the semester due to its highly practical nature, and does not include a final exam.

Mandatory

"Hastie T, Tibshirani T, Friedman J, The elements of statistical Data-Mining, Inférence and prediction second edition. Springer-Verlag New York, (2009), 533p. ISBN : 978-0-387-84858-7 Artificial Intelligence in Healthcare: AI, Machine Learning, and Deep and Intelligent Medicine Simplified for Everyone (English Edition), Parag Mahajan P. Tattar, T. Ojeda, S. P. Murphy B. Bengfort, A. Dasgupta, Practical Data Science Cookbook, Second Edition. Packt Publishing. 2017 C. O'Neil, R. Schutt. Doing Data Science: Straight Talk from the Frontline. O'Reilly. 2013"

Optional

"""Python for Data Analysis"" by Wes McKinney - This book is a comprehensive guide to data analysis using Python, and covers topics such as data manipulation, visualization, and machine learning. ""Data Science from Scratch: First Principles with Python"" by Joel Grus - This book provides an introduction to data science using Python, and covers topics such as data cleaning, exploratory data analysis, and statistical inference. James G, Witten D, Hastie T, Tibshirani T, An introduction to statistical learning with applications in R. second edition. Springer-Verlag New York, (2021), 607p. ISBN : 978-1-0716-1418-1 Topol, E. J. (2019). Deep Medicine: How Artificial Intelligence Can Make Healthcare Human Again. Basic Books. P. Mathur, Machine Learning Applications Using Python: Cases Studies from Healthcare, Retail, and Finance. Apress. 2018."

PC1 Image representation
PC2 Image operations
PC3 Extraction of image features
PC4 Introduction to machine learning
PC5 Artificial neural networks
PC6 Convolutional neural networks
PC7 Transfer Learning
PC8 Network architectures for detecting and identifying image objects
PC9 Network architectures for automatic content generation
PC10 Developed Health Care Applications

Theoretical-practical classes that alternate exposition and application moments, with examples and exercises that involve the development of code snippets using the OpenCV and Tensorflow libraries. The course follows a project-based continuous assessment model throughout the semester due to its highly practical nature, and does not include a final exam.

Mandatory

Feature Extraction and Image Processing for Computer Vision, 4th Edition, M. Nixon e Alberto Aguado, Academic Press, 2019 Deep Learning, I. Goodsfellow, Y. Bengio e A. Courville, MIT Press, 2016 Learning OpenCV 4 with Python 3, 3rd Edition, Joseph Howse, Joe Minichino, Packt Publishing, 2020 Tutoriais e documentação das bibliotecas OpenCV e Tensorflow

Optional

Introduction to E-Health and Telemedicine: Overview of e-health and telemedicine, their benefits, and challenges in healthcare.

Telecommunication Systems in Healthcare: Covers systems for remote healthcare such as teleconsultation, telemonitoring, and teleconferencing.

Digital Health Technologies: Examines electronic health records, mobile health apps, wearable devices, and their effects on healthcare delivery.

Legal and Ethical Considerations: Discusses privacy, security, and regulatory issues in e-health and telemedicine.

Implementing E-Health and Telemedicine: Looks at infrastructure needs, deployment considerations, and system interoperability.

Case Studies and Real-World Examples: Offers insights through case studies and real-world applications of e-health and telemedicine.

The assessment for the curricular unit "E-Health and Telemedicine" will employ various methods to evaluate student learning. Written examinations will be used to assess knowledge and understanding of the principles and applications of e-health and telemedicine. Practical assignments will test students' skills in utilizing digital technologies and telecommunication systems for remote healthcare delivery. Additionally, case studies or projects will provide opportunities for students to demonstrate their competencies in analyzing and addressing challenges and ethical considerations in the field. By employing a diverse range of assessment methods, students' comprehensive understanding, practical skills, and critical thinking abilities in e-health and telemedicine will be effectively evaluated.
The course follows a project-based continuous assessment model throughout the semester due to its highly practical nature, and does not include a final exam.

Mandatory

Grigsby, J., Rigby, M., Hiemstra, A., & House, M. (2015). Telemedicine readiness for hospice care center patients. Telemedicine Journal and e-Health, 21(8), 647-651. Topol, E. J. (2012). The creative destruction of medicine: How the digital revolution will create better health care. Basic Books. Mooney, S. E., & DeBate, R. D. (2013). Telemedicine and e-Health: A reader for Health Professionals. Routledge. Bashshur, R. L., Shannon, G. W., Bashshur, N., & Yellowlees, P. M. (2015). The empirical evidence for telemedicine interventions in mental disorders. Telemedicine Journal and e-Health, 21(12), 942-948. Oh, H., Rizo, C., Enkin, M., & Jadad, A. (2010). What is eHealth (3): A systematic review of published definitions. Journal of Medical Internet Research, 12(1), e1. World Health Organization. (2010). Telemedicine: Opportunities and developments in Member States: Report on the second global survey on eHealth. World Health Organization. Mair, F. S., May, C., & O'Donnell, C. (2012). Developing telehealthcare in rural Scotland: A qualitative study of patients' views. Journal of Telemedicine and Telecare, 18(6), 357-361. Sood, S., Mbarika, V., Jugoo, S., Dookhy, R., Doarn, C. R., & Prakash, N. (2010). What is telemedicine? A collection of 104 peer-reviewed perspectives and theoretical underpinnings. Telemedicine and e-Health, 16(9), 977-983.

Optional

1: Introduction to digital health trends and standardization: Data coding, definitions, and classifications. Terminologies and vocabularies.
2: Common data classifications: International Classification of Diseases (ICD). Systematized Nomenclature of Medicine (SNOMED CT). Logical Observation Identifiers Names and Codes (LOINC). International Classification of Health Interventions (ICHI). International Classification of Functioning, Disability, and Health (ICF). Anatomical Therapeutic Chemical Classification System (ATC) and Defined Daily Dose (DDD).
3: Data exchange formats: Health Level Seven (HL7). Fast Healthcare Interoperability Resources (FHIR). Clinical Document Architecture (CDA).
4: Data standards and reuse: Data interoperability challenges. Primary and secondary uses of data. Actors, constraints, and challenges.
5: Case studies and applications.

In general, students will complete assignments that involve analyzing and applying health data classifications and exchange formats to real-world scenarios. Online Quizzes: Regular online quizzes can be used as a formative assessment method to evaluate students' understanding of key concepts and principles.
Students will analyze case studies to demonstrate their understanding of health data classification and exchange. Case Study Analysis: Assigning case/use studies can assess students' ability to apply their knowledge and skills in real-world scenarios.
Project: Students will work on a project to propose and implement appropriate health data classifications and exchange formats for a specific healthcare setting.
Group Project: Engaging students in a collaborative group project can assess their ability to work in teams and apply their knowledge and skills collectively. More specifically, an inter-disciplinary project involving the different contexts (data science, social and business health contexts) in topics of health data re-use is a niche idea. Examinations: Periodic examinations will be conducted to assess students' knowledge of the course material. The course follows a project-based continuous assessment model throughout the semester due to its highly practical nature, and does not include a final exam.

Mandatory

Holub et al. 2018. Enhancing Reuse of Data and Biological Material in Medical Research:From FAIR to FAIR-Health BIOPRESERVATION AND BIOBANKING. Volume 16, Number 2, 2018. Mary Ann Liebert, Inc.
C. Safran 2017. Update on Data Reuse in Health Care. Yearb Med Inform. 2017 Aug; 26(1): 24–27.Published online 2017 Sep 11. doi: 10.15265/IY-2017-013 PMCID: PMC6239227PMID: 29063535
WHO 2022. Sharing and reuse of health-related data for research purposes: WHO policy and implementation guidance.
Törnvall E, Jansson I. Preliminary evidence for the usefulness of standardized nursing terminologies in different fields of application: A Literature Review. Int J Nurs Knowl. 2017 Apr;28(2):109-119.
Mykkänen, M. et al. Using standardized nursing data for knowledge generation - Ward level analysis of point of care nursing documentation. Int J Med Inform 2022 Nov;167:104879.
Kinnunen, U et al. (2021-08-30) User GuideThe Finnish Care Classification System FinCC 4.0_v1.1.

Optional

General Information on sensors and Instrumentation (8 hours)
Sleep pathologies (8 hours)
Instrumentation for Electrophysiological measurements (8 hours)
Miniaturization and integration (8 hours)
Monitoring electrical properties of living one (8 hours)
Synthesis and Oral Defense (10 hours)

Online Quizzes : At the end of all chapter of the lectures, multiple choice questions will be used to evaluate student's progress.
Writing exam : Two writing exam (mid-term and end) will be plan with a view to developing reasoning skills and highlight on-line lab work.
Personal/group work : a short report an associated oral presentation (video) will conlude the lectures. This personal work will be avaluate by a peer review. The course follows a project-based continuous assessment model throughout the semester due to its highly practical nature, and does not include a final exam.

Mandatory

[1] Biomedical Sensors and Instruments, CRC Press, Second Edition by Tatsuo Tagawa, Toshiyo Tamura, P. Ake Oberg [2] Enginnering of Micro/Nano Biosystems Fundamentals and Applications, Springer by Gregory Barbillon, Alain Bosseboeuf, Kukjin Chun, Rosaria Ferrigno, Olivier Français. [3] An introduction to signal processing for non-engineers, CRC Press, 1st Edition by Afshin Samani.

Optional

"Pre-assignment (reading, writing key insights on a discussion forum)
Online kick-off (online 2 hours)
Desk Research and stakeholder interviews (remote work between the kick-off and 5-day sprint, individual and teamwork)
5-Day Co-creation Sprint Week held annually in ManagiDiTH partners' countries about once a year
1. Problem definition
2. Ideation and sketching
3. Deciding and iterating
4. Prototyping and piloting
5. Showcasing results
End Gala Presentations

Note: Students who are unable to participate in the 5-day sprint on-site form their team and do their assignments online and/or in their local community. The supportive activities and coaching that are part of the 5-day sprint are organised as asynchronic and synchronic online activities. This has to be planned in more detail."

Study unit is evaluated with points (maximum 100). Students need to get at least 50 points (50%) to pass the study unit. Each university will change the points to the grades based on their grading system. Assessment: Individual pre-assignment (pass/fail), online Quizzes individually (10%), service design case in teams (90%). The course follows a project-based continuous assessment model throughout the semester due to its highly practical nature, and does not include a final exam.

Mandatory

Pfannstiel. 2019. Service Design and Service Thinking in Healthcare and Hospital Management. Springer International Publishing.Media Inc.
Pfannstiel, M. A., Brehmer, N. & Rasche, C. 2022. Service design practices for healthcare innovation: Paradigms, principles, prospects. Cham: Springer Nature Switzerland.
Pfannstiel, M. A. 2023. Human-centered service design for healthcare transformation: Development, innovation, change. Singapore: Springer International Publishing AG.
Junginger, S. (2017) Transforming Public Services by Design Re-Orienting Policies, Organizations and Services around People. Oxfordshire, UK; Routledge.
Foglieni F., Villari B., Maffei S. (2018). From Service to Service Design. In Designing Better Services. Springer Briefs in Applied Sciences and Technology. Springer, Cham.;
Design Council (2021). "Beyond Net Zero. A Systemic Design Approach."

Optional

S1 Social and individual approach to the digital transformation in the health sector
S1.1 Role and limitations of digitality in individual health
S1.2 Regulation and other public policy tools related to public health
S2 Applying behavioral insights in health care and health promotion contexts
S2.1 Development and evaluation of digital solutions and real life behavioral interventions
S2.2 The cognitive biases and heuristics in understanding patients and service providers behaviour
S3 Behavioral change principles and interventions as means to improve health outcomes
S3.1 Governmental interventions and policies in promoting public health
S3.2 Health care professionals role in assisting patients in forming healthy habits
S4 Impact assessment of behavioral interventions
S4.1 Evaluation of the behavioral change and the related health benefits
S4.2 Financial impact and cost effectiveness of the interventions

Study Units are evaluated with points. Students need to get at least 50% of the maximum points to pass the Study Unit. Each university will change the points to the grades based on their grading system. Group assignments (90%) and individual assignments (10%). This CU includes also assignments that are graded with fail/pass. The course follows a project-based continuous assessment model throughout the semester due to its highly practical nature, and does not include a final exam.

Mandatory

The Elements of Choice: Why the Way We Decide Matters
Developing Behavior Change Interventions, in M.S. Hagger , L.D. Cameron , K. Hamilton , N. Hankonen & T. Lintunen (eds) The handbook of behavior change, Cambridge Handbooks in Psychology , Cambridge University Press, 300-317.
Faries MD. Why We Don't "Just Do It": Understanding the Intention-Behavior Gap in Lifestyle Medicine. Am J Lifestyle Med. 2016 Jun 22;10(5):322-329. doi: 10.1177/1559827616638017. PMID: 30202289; PMCID: PMC6125069.
Should Governments Invest More in Nudging?

Optional

PC1: Introduction to Interoperability in Healthcare
PC2: Healthcare Interoperability Standards and Protocols (HL7, IHE tools, prototypes)
PC3: Nomenclatures and Terminologies - data sets (EU experiences)
PC4: International Experiences, Best Practices of Interoperability in Healthcare (present country cases, regional cases, etc.)
PC5: Interoperability Implementation: testing, conformity assessment
PC6: My Health@EU Primary Use Interoperability Requirements
PC7: My Data@EU Secondary Use Interoperability Requirements
PC8: Past & Active European Relevant Initiatives
PC9: Blockchain Technology in Interoperability
PC10: AI Technology in Interoperability
PC11: IoT Technology in Interoperability
PC12: Ethical, Legal, and Policy Issues
PC13: Challenges and Opportunities of Interoperability in Healthcare (Governance Issues, etc.)

Online Quizzes: Regular online quizzes can be used as a formative assessment method to evaluate students' understanding of key concepts and principles.
Case Study Analysis: Assigning case/use studies can assess students' ability to apply their knowledge and skills in real-world scenarios. Assessment: exercises / problems performed in group, during the course classes.
Group Project: Engaging students in a collaborative group project can assess their ability to work in teams and apply their knowledge and skills collectively. The course follows a project-based continuous assessment model throughout the semester due to its highly practical nature, and does not include a final exam.

Mandatory

"Asamoah, D. A., & Sheth, A. P. (2019). Blockchain in healthcare: Opportunities, challenges, and future directions. Journal of Web Semantics, 56, 49-58 eHealth Action Plan 2018-2022: https://ec.europa.eu/digital-single-market/en/news/ehealth-action-plan-2018-2022-innovative-healthcare-21st-century, European Union. (2016). Health Level Seven International. (2018). HL7 Fast Healthcare Interoperability Resources (FHIR): https://www.hl7.org/fhir/ EHRxF Community of Practice, EU Health Policy Platform, i~HD European Network of Excellence for Hospitals, IHE for European Users, HL7 Essentials EU directives & documents https://eur-lex.europa.eu/legal-content/EN/TXT/PDF/?uri=CELEX:32015D1302 Interoperability Profiles: www.ihe.net/resources/profiles/ Interoperability Standards: https://www.i-hd.eu/health-standards/ Data and Systems Security Guide:http://ehaction.eu/wp-content/uploads/2021/01/Data-and-systems-security-Guide.pdf"

Optional

Kuo, T. T., & Kim, H. E. (2018). The current state of interoperability in healthcare: An overview. Journal of the American Medical Informatics Association, 25(10), 1250-1259. National Institute of Standards and Technology. (2019). Blockchain Technology Overview. Retrieved from https://csrc.nist.gov/publications/detail/nistir/8202/final Ross, M. K., & Lin, M. (2018). The Internet of Things: Risks and challenges in healthcare. Journal of Law, Medicine & Ethics, 46(2), 475-484. World Health Organization. (2016). Global strategy on digital health 2020-2025. Retrieved from https://www.who.int/publications/i/item/9789241511766 Zhang, P., White, J., Schmidt, D. C., Lenz, G., & Rosenbloom, S. T. (2019). FHIRChain: Applying blockchain to securely and scalably share clinical data. Computers in Biology and Medicine, 109, 234-245.