Programme Structure for 2024/2025
| Curricular Courses | Credits | |
|---|---|---|
| 1st Year | ||
|
Digital Tools for Controlling and Preventing Antimicrobial Resistance
3.0 ECTS
|
Postgraduate Seminar (2nd Cycle) | 3.0 |
|
Digital tools for Waste Management in Public Health
3.0 ECTS
|
Postgraduate Seminar (2nd Cycle) | 3.0 |
|
Behavioural Change Tools for Patients Empowerment
3.0 ECTS
|
Postgraduate Seminar (2nd Cycle) | 3.0 |
Digital Tools for Controlling and Preventing Antimicrobial Resistance
Upon completing the course, students should be able to:
LO1: Identify and describe the functioning of the Internet of Things (IoT) in healthcare, the principles of Artificial Intelligence (AI) and Generative AI, and the use of Blockchain for the security and integrity of health data.
LO2: Utilise digital systems that support the prevention and control of antimicrobial resistance.
LO3: Apply data annotation techniques and text mining to extract relevant information for controlling antimicrobial resistance.
LO4: Discuss ethical and privacy issues related to the use of digital technologies in healthcare.
LO5: Evaluate the effectiveness of digital interventions in promoting the responsible use of antibiotics.
CP1: Introduction to Emerging Technologies in Healthcare: Definition and functioning of IoT in healthcare. Principles of AI and Generative AI. Use of Blockchain for the security and integrity of health data.
CP2: Digital Transformation and Data Systems: Digital systems for tracking the prescription and use of antibiotics, identifying inappropriate usage patterns.
CP3: Data Annotation, Text Mining, and Voice-to-Text Conversion: Techniques for data annotation, text mining tools, and voice-to-text applications.
CP4: Privacy and Ethical Issues: Ensuring the ethical use of patient data and maintaining privacy when applying digital technologies.
CP5: Technology and Behavioural Change: Behavioural change theories and digital interventions, assessing their effectiveness.
CP6: Digital skills applied to specific cases for nurses, pharmacists, healthcare managers, and doctors.
Students can complete the Curricular Unit (CU) through assessment conducted throughout the semester, which includes: (i) individual analysis of two online modules that apply digital tools to content related to AMR. This involves engaging with the content provided in these modules, completing the associated quizzes, and presenting the digital content covered in these modules during synchronous classes (50%); (ii) group work (50%) Students must achieve a minimum score of 9.5 points in each assessment component and an overall final average of 9.5 points or higher to pass the course.
Bibliography"Wachter, R. (2015). The Digital Doctor: Hope, Hype, and Harm at the Dawn of Medicine's Computer Age. McGraw-Hill Education. Chambers, R., Schmid, M., & Birch-Jones, J. (2016). Digital healthcare: The essential guide (Paperback ed.). Future Plc. Wade, S.B. (2023). Transforming Healthcare: Harnessing the Power of Artificial Intelligence for Enhanced Patient Care: AI leads to accuracy and precision, minimizing discrepancies and improving patient outcomes. Independently published. Hoyt, R. E., & Yoshihashi, A. K. (2014). Health informatics: Practical guide for healthcare and information technology professionals (6th ed.).
"Experience of Health Care Professionals Using Digital Tools in the Hospital: Qualitative Systematic Review (JMIR Publications, 2023) - This review synthesizes qualitative studies exploring healthcare professionals' experiences with digital tools, revealing both benefits and challenges. Digital technologies in support of universal health coverage: a WHO guide (World Health Organization, 2023) - This guide provides a framework for using digital technologies to achieve universal health coverage, highlighting their potential and implementation strategies. The impact of digital health tools on healthcare professionals' well-being and work-life balance (Journal of Medical Internet Research, 2022) - This study investigates the impact of digital health tools on healthcare workers' well-being, highlighting the need for proper implementation and support. Effectiveness of mHealth interventions for improving health care professional practice and patient outcomes: a systematic review (PLOS ONE, 2019) - This review assesses the effectiveness of mobile health (mHealth) interventions for healthcare professionals, demonstrating positive impacts on practice and patient outcomes. Reports and White Papers: Digital Health: 7 Tools You Need to Succeed in This Industry (Sydle, 2023) - This blog post outlines seven essential digital health tools that are shaping the future of the industry, including EHRs, telemedicine platforms, and cybersecurity solutions. Digital Technologies in Primary Health Care (World Health Organization, 2021) - This report explores the role of digital technologies in strengthening primary health care, offering recommendations for implementation and scaling up. The Topol Review: Preparing the healthcare workforce to deliver the digital future (Health Education England, 2019) - This influential report examines the implications of digital technologies for the healthcare workforce, emphasizing the need for education and training to harness their potential. Transforming healthcare with AI: The impact on the workforce and organizations (McKinsey & Company, 2018) - This report explores the impact of AI on the healthcare workforce, highlighting both opportunities and challenges for health professionals.
Digital tools for Waste Management in Public Health
Upon completing the course, students should be able to:
LO1: Identify and analyse IoT, AI, and Blockchain technologies applied to healthcare waste management, considering their challenges and benefits with a focus on sustainability.
LO2: Understand and evaluate digital transformation in healthcare and its application to waste traceability, including the impact of digital technologies on process security.
LO3: Apply data techniques to improve the quality and accessibility of waste information, developing digital solutions that integrate technologies and strategies.
LO4: Use digital tools to ensure data privacy and security in waste management, evaluating the advantages and limitations of digital technologies in sustainability.
LO5: Apply behavioural change strategies to promote sustainable practices and evaluate the effectiveness of behavioural interventions in waste management.
CP1: Emerging Technologies in Waste Management in Healthcare: Understand the use of IoT, AI, and Blockchain in waste management and analyse their challenges and benefits with a focus on sustainability.
CP2: Digital Transformation and Waste Traceability: Understand digital transformation and waste traceability in healthcare and evaluate their impact on process security.
CP3: Data Techniques for Quality and Accessibility: Apply data techniques to improve the quality and accessibility of waste information and develop integrated digital solutions.
CP4: Data Privacy and Security: Use digital tools to ensure data privacy and security and evaluate the advantages and limitations of digital technologies in sustainability.
CP5: Behavioural Strategies for Sustainable Practices: Apply behavioural change strategies and evaluate the effectiveness of interventions for responsible practices and waste reduction.
Group work weighing 50% and individual assessment throughout the different modules 50% of the final grade (case study or quizes).
Minimum mark of 8 in each of the group and individual assessment components.
"Hasselgren A, Kralevska K, Gligoroski D, Pedersen SA, Faxvaag A. Blockchain in healthcare and health sciences-A scoping review. Int J Med Inform. 2020 Feb;134:104040. doi: 10.1016/j.ijmedinf.2019.104040. Epub 2019 Dec 11. PMID: 31865055. M. O. Raji and A. G. Adeogun, “Healthcare Waste Management: An Overview”, AJERD, vol. 7, no. 1, pp. 14-27, Mar. 2024.
Behavioural Change Tools for Patients Empowerment
LO1. Understand how modifying patient behaviours leads to better health outcomes and increases the effectiveness of healthcare.
LO2. Gain proficiency in using various behavioural change models and strategies in healthcare settings to support patients through effective behaviour modification.
LO3. Observe, develop, and apply methods to empower patients, equipping them with the knowledge and skills necessary to take an active role in managing their health.
LO4. Acquire and apply techniques to engage and motivate patients, promoting their active participation in their own healthcare, improving treatment adherence, and supporting sustainable behavioural changes.
LO5. Identify and utilise digital tools and technologies (e.g., health apps) to facilitate and enhance behavioural change in patients, improving their engagement, adherence, and overall health outcomes.
PC1: Introduction to Behavioural Change
Definition and key concepts.
Impact on health and effectiveness of healthcare.
PC2: Behavioural Change Models
Behavioural change models: Transtheoretical Model, Health Belief Model, and COM-B.
Practical applications and adaptations in healthcare settings.
PC3: Patient Empowerment and Education
Patient education strategies.
Tools and techniques for empowerment.
Role of communication and feedback in patient empowerment.
PC4: Patient Engagement and Motivation
Techniques for engagement and motivation.
Promoting active participation and adherence to treatment.
PC5: Use of Digital Tools for Behavioural Change
Introduction to digital tools: health apps, telemedicine platforms.
Integration of digital tools into clinical practice.
Students can complete the Curricular Unit through assessment conducted throughout the semester, comprising two main components. The first involves engaging with content from two online modules, complemented by associated quizzes, which account for 50% of the final grade. The second component is an individual test that assesses students’ knowledge of behavioural change models and strategies, also weighted at 50%. To pass, students must achieve a minimum score of 9.5 in each component and an overall average of 9.5 or higher.
Bibliography"Bandura, A. (2012). Self-efficacy the exercise of control Albert Bandura. Frates, B., & Faries, M. D. (2024). Empowering behavior change in patients: Practical strategies for the healthcare professional. CRC Press. Mather, M., Pettigrew, L. M., & Navaratnam, S. (2022). Barriers and facilitators to clinical behaviour change by primary care practitioners: A theory-informed systematic review of reviews using the theoretical domains framework and behaviour change wheel. Systematic Reviews, 11(1). https://doi.org/10.1186/s13643-022-02030-2 Michie, S., Atkins, L., & West, R. (2014). The behaviour change wheel: A guide to designing interventions.
"Alcántara, C., Diaz, S. V., Cosenzo, L. G., Loucks, E. B., Penedo, F. J., & Williams, N. J. (2020). Social determinants as moderators of the effectiveness of health behavior change interventions: Scientific gaps and opportunities. Health Psychology Review, 14(1), 132–144. https://doi.org/10.1080/17437199.2020.1718527 Cuevas, C., Batura, N., Wulandari, L. P., Khan, M., & Wiseman, V. (2021). Improving antibiotic use through behaviour change: A systematic review of interventions evaluated in low- and middle-income countries. Health Policy and Planning, 36(5), 754–773. https://doi.org/10.1093/heapol/czab021 Davis, R., Campbell, R., Hildon, Z., Hobbs, L., & Michie, S. (2014). Theories of behaviour and behaviour change across the social and Behavioural Sciences: A scoping review. Health Psychology Review, 9(3), 323–344. https://doi.org/10.1080/17437199.2014.941722 Johnson, M. J., & May, C. R. (2015). Promoting professional behaviour change in healthcare: What interventions work, and why? A theory-led overview of systematic reviews. BMJ Open, 5(9). https://doi.org/10.1136/bmjopen-2015-008592 Krebs, P., Prochaska, J. O., & Rossi, J. S. (2010). A meta-analysis of computer-tailored interventions for health behavior change. Preventive Medicine, 51(3–4), 214–221. https://doi.org/10.1016/j.ypmed.2010.06.004 Laffont, J.-J., & Martimort, D. (2013). The theory of incentives: The principal-agent model. World Publishing Corporation. Oliver, J. W., Kravitz, R. L., Kaplan, S. H., & Meyers, F. J. (2001). Individualized patient education and coaching to improve pain control among cancer outpatients. Journal of Clinical Oncology, 19(8), 2206–2212. https://doi.org/10.1200/jco.2001.19.8.2206 Suttels, V., Van Singer, M., Clack, L. C., Plüss-Suard, C., Niquille, A., Mueller, Y., & Boillat Blanco, N. (2022). Factors influencing the implementation of antimicrobial stewardship in primary care: A narrative review. Antibiotics, 12(1), 30. https://doi.org/10.3390/antibiotics12010030