Digital Health in Practice, Fall 2024, University of Zurich
Hypertension Digital Therapeutics (Nature Hypertension Research 2024), Digital Therapeutics from Bench to Bedside (npj Digital Medicine, 2023), Digital Therapeutics for Mental Health and Addiction (Elsevier 2023), Large Language Models in Medicine (Nature Medicine, 2023), How to e‐mental health (Nature Mental Health, 2023), Artificial Intelligence and Machine Learning in Medicine (New England Journal of Medicine, 2023), LLM‐based AI Chatbots in Medicine (Nature Medicine, 2023)
Digital health applications use information, sensor, and communication technology to understand, prevent, manage, or treat diseases. The design of these applications requires interdisciplinary expertise at the intersection of medicine, psychology, computer science, technology, management, economics, and law. Only a close collaboration between experts from these disciplines and a specific target population can lead to a shared understanding of the problem at hand and, as a result, highly effective digital health applications. For this reason, national and international students studying computer science, business informatics, psychology, management, economics, or law are invited to work collaboratively with medical students.
Digital health applications and companies have the goal of advancing health care services to fight the ongoing increase of non-communicable diseases (NCDs) and common mental disorders (CMDs) in developed countries. To this end, the question arises of how to develop evidence-based digital health interventions (DHI) that allow medical doctors and other caregivers to scale and tailor long-term treatments to individuals in need at sustainable costs. Through input lectures and practical applications, this module has, therefore, the objective to help students to understand better the need, design, implementation, and evaluation of DHIs.
After the course, students will be able …
- to understand the importance of digital health interventions for the prevention, management, and treatment of non-communicable diseases and common mental disorders
- to discuss the opportunities and challenges of digital health interventions (e.g., data collection with wearables, smartphone- and chatbot-delivered health interventions)
- to gain hands-on experience in the conceptual design, implementation, and evaluation of a wearable- and smartphone-based digital health intervention
To reach these learning objectives, the following topics are covered:
- DHIs for the prevention, management, and treatment of NCDs and CMDs
- Strategies for long-term compliance with DHI
- Conceptual design of a wearable- and smartphone-based DHI
- Technical implementation of a wearable- and smartphone-based DHI
- Evaluation of a wearable- and smartphone-based DHI
Course Structure
The module consists of live input sessions with interactive group exercises and discussions. Complementary learning material is provided through tutorial video clips, multiple-choice questions, and exercises. Additional coaching sessions are offered to support the groups with the development of their DHI and with the preparation of their presentations. In addition to the MobileCoach platform (www.mobile-coach.eu), an open-source software platform for developing digital biomarkers and health interventions, students will gain hands-on experience with wearable fitness trackers (Fitbits). Programming skills are not required.
The module is structured as follows:
- Students are equipped with relevant foundational knowledge (2 sessions)
- Students build groups and develop a wearable- and smartphone-based DHI (3 sessions)
- Students use the wearable- and smartphone-based DHIs of their peers (ca. 10 days)
- Students in groups evaluate their wearable- and smartphone-based DHI (1 session)
- Students in groups present and critically discuss their findings (1 session)
Course Literature
All relevant learning material will be made available via the online learning platform. Moreover, the content of this module is drawn from the experience of the lecturers and the following work:
- Balbim GM, IG Marques, DX Marquez, et al. (2021) Using Fitbit as an mHealth Intervention Tool to Promote Physical Activity: Potential Challenges and Solutions, Journal of Medical Internet Research (JMIR) Mhealth Uhealth 9(3):e25289, 10.2196/25289
- Collins LM (2018) Optimization of Behavioral, Biobehavioral, and Biomedical Interventions: The Multiphase Optimization Strategy (MOST), New York: Springer, 10.1007/978-3-319-72206-1
- Hisaki, F., Aga, M., Tomitani, N., Okawara, Y., Harada, N., & Kario, K. (2024) Daily self-reported behavioural efficacy records on hypertension digital therapeutics as digital metrics associated with the reduction in morning home blood pressure: post-hoc analysis of HERB-DH1 trial. Hypertension Research, 47(1), 120-127. 10.1038/s41440-023-01434-4
- Jacobson N, T Kowatsch & LA Marsch (2023) Digital Therapeutics for Mental Health and Addiction: The State of the Science and Vision for the Future (1st ed.), Cambridge: Elsevier, Academic Press, 978-0-323- 90045-4
- Kowatsch T & Fleisch E (2021) Digital Health Interventions, in: Gassmann, O.; Ferrandina, F. (eds): Connected Business, Springer: Cham, 10.1007/978-3-030-76897-3_4
- Kowatsch T, L Otto, S Harperink, A Cotti & H Schlieter (2019) A Design and Evaluation Framework for Digital Health Interventions, it- Information Technology 61(5-6), 253-263, 10.1515/itit-2019-0019
- Kowatsch T, T Schachner, S Harperink et al. (2021) Conversational Agents as Mediating Social Actors in Chronic Disease Management Involving Health Care Professionals, Patients, and Family Members: Multisite Single-Arm Feasibility Study, Journal of Medical Internet Research (JMIR) 23(2):e25060, 10.2196/25060
- Sim I. (2019) Mobile Devices and Health, New England Journal of Medicine (NEJM) 381(10):956-968, 10.1056/NEJMra1806949
Summary
Digital Health in Practice, University of Zurich, Fall 2024, 4 ECTS, Tuesday, 8:15 a.m. – 12:00 a.m., Links:
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