Digital Therapeutics Project, Spring 2024, University of St.Gallen
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)
What are the implications and rationale behind the recent developments in digital health?
Digital Health is the use of information and communication technology for the prevention and treatment of diseases in the everyday life of individuals. It is thus linked to topics such as digital health interventions, digital biomarkers, digital coaches and healthcare chatbots, telemedicine, mobile and wearable computing, self‐tracking, personalized medicine, connected health, smart homes, or smart cars.
In the 20th century, healthcare systems specialized in acute care. In the 21st century, we now face the challenge of dealing with the specific characteristics of non‐communicable diseases. These are now responsible for around 70% of all deaths worldwide and 85% of all deaths in Europe and are associated with an estimated economic loss of $7 trillion between 2011 and 2025. Chronic and mental diseases are characterized in particular by the fact that they require an intervention paradigm that focuses on prevention and lifestyle change. Lifestyle (e.g., diet, physical activity, tobacco, or alcohol consumption) can reduce the risk of suffering from a chronic condition or, if already present, can reduce its burden. A corresponding change in lifestyle is, however, only implemented by a fraction of those affected, partly because of missing or inadequate interventions or health literacy, partly due to sociocultural influences. Individual personal coaching of these individuals is neither scalable nor financially sustainable.
To this end, the question arises of how to develop evidence‐based digital therapeutics (DTx) that allow medical doctors and other caregivers to scale and tailor long‐term treatments to individuals in need at sustainable costs. At the intersection of health economics, behavioral medicine, information systems research, and computer science, this lecture aims to help students and upcoming healthcare executives interested in the multi‐disciplinary field of digital health better understand the need, design, implementation, and assessment of DTx.
After the course, students will be able to…
- understand the importance of DTx for the management of chronic and mental conditions
- discuss the opportunities and challenges related to DTx
- better understand the design, implementation and evaluation of smartphone‐based and chatbot‐delivered DTx
To reach the learning objectives, students will work on the following topics:
1. Motivation for Digital Health
- The rise of chronic diseases in developed countries
- Prevention, management, and treatment of disease
2. Design of a Digital Therapeutics (DTx)
- Overview of design frameworks for health interventions
- Development of a conceptual model for a DTx
- Implementation of a smartphone‐based and chatbot‐delivered DTx
3. Evaluation of DTx
- Overview of evaluation methods and evaluation criteria for DTx
- Evaluation of a smartphone‐based and chatbot‐delivered DTx
Course Structure
The course is structured in two parts and follows the concept of a blended treatment consisting of on‐site live sessions and complementary online self‐service lessons. In on‐site live sessions, students will learn and discuss the topics of the three learning modules. Complementary learning material (e.g., video clips), multiple‐choice questions, and exercises are provided online via Canvas.
In the second part, students work in teams and will use their knowledge from the first part of the lecture to develop a smartphone‐based and chatbot‐delivered health intervention with MobileCoach (www.mobile‐coach.eu), an open‐source software platform for the development of digital biomarker and digital health interventions. Each team will then present and discuss the resulting digital health intervention and evaluation results with their fellow students, who will provide peer reviews. Additional live coaching sessions are offered to support the teams with the design and evaluation of their digital health intervention and with the preparation of their presentations.
In Spring 2024, medical doctors bring in relevant use cases students can work on.
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:
- Castro, O., Mair, J. L., Salamanca‐Sanabria, A. et al (2023). Development of “LvL UP 1.0”: a smartphone‐based, conversational agent‐delivered holistic lifestyle intervention for the prevention of non‐communicable diseases and common mental disorders. Frontiers in Digital Health, 5. 10.3389/fdgth.2023.1039171
- Jacobson, N., Kowatsch, T., & Marsch, L. (Eds.). (2023). Digital Therapeutics for Mental Health and Addiction: The State of the Science and Vision for the Future (1st ed.). Elsevier, Academic Press. https://doi.org/10.1016/C2020‐0‐02801‐X.Kowatsch, T., L. Otto, S. Harperink, A. Cotti and H. Schlieter (2019) A Design and Evaluation Framework for Digital Health Interventions it ‐ Information Technology, 61(5‐6), 253‐263.
- Kowatsch, T., Otto, L., Harperink, S., Cotti, A., & Schlieter, H. (2019). A design and evaluation framework for digital health interventions. it ‐ Information Technology, 61(5‐6), 253‐263. 10.1515/itit‐2019‐0019
- Lee, P., Bubeck, S., & Petro, J. (2023). Benefits, Limits, and Risks of GPT‐4 as an AI Chatbot for Medicine. New England Journal of Medicine, 388(13), 1233‐1239. 10.1056/NEJMsr2214184
- Seiferth, C., Vogel, L. et al (2023). How to e‐mental health: a guideline for researchers and practitioners using digital technology in the context of mental health. Nature Mental Health, 1(8), 542‐554. 10.1038/s44220‐023‐00085‐1
- Thirunavukarasu, A. J., Ting, D. S. J., Elangovan, K., Gutierrez, L., Tan, T. F., & Ting, D. S. W. (2023). Large language models in medicine. Nature Medicine, 29(8), 1930‐1940. 10.1038/s41591‐023‐02448‐8
- Wang, C., Lee, C., & Shin, H. (2023). Digital therapeutics from bench to bedside. npj Digital Medicine, 6(1), 38. 10.1038/s41746‐ 023‐00777‐z
Summary
Digital Therapeutics Project (12,801), University of St.Gallen, Spring 2024, 3 ECTS
Lecturers
Contact Person
BSc in Biomedicine (University of Zurich) and a MSc in Medical Technology (ETH Zurich)
Teaching Support
BSc in Biomedicine (University of Zurich) and a MSc in Medical Technology (ETH Zurich)
