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Digital Health (S)

(10181611)

TypSeminar
Dozent/inProf. Dr. Daniel Fürstenau
SpracheEnglisch
SemesterSommersemester 2022
Veranstaltungsumfang180 Stunden
Leistungspunkte6 ECTS

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Zielgruppe

This elective course is open to master-level students of all study programs within and outside the Freie Universität Berlin especially Business Information Systems, Computer Science, Medicine and Business Administration. 

Voraussetzungen

There are no formal prerequisites to participate. Prior knowledge of healthcare or digital technologies is helpful, but not a must.

Course content and structure

This course lays the foundations for gaining insights into trends, technologies, and developments in digital healthcare innovations as well as user-design-oriented digital innovation approaches in the healthcare field. Amidst the ongoing Corona pandemic, healthcare is still considered one of the least digitized industries. However, increasing digitization, mobile devices and sensor-based technologies, combined with machine learning and artificial intelligence methods, hold enormous potential to improve quality and access to healthcare while limiting costs. In recent years, not only many startups but also big players such as health insurance companies, pharmaceutical companies and hospitals have become interested in innovative healthcare solutions, we can observe an overall shift in mindset towards a more qualitative oriented definition of health. In this growing market, there is a high demand for talent that can understand both the technical and medical perspectives and contribute to the development of innovative ideas.

This course is designed to give participants an overview of healthcare information systems and infrastructures and the latest trends, technologies and legal frameworks embedded in these. For each of these trends, we will cover the underlying conceptual, theoretical, and methodological foundations as well as concrete cases and application scenarios in different healthcare contexts. During the course, students receive input through video sessions that will be discussed in class, also methods are put into practice with hands on approaches on how to shape digital health innovations. Additionally, professional guest speakers will provide insights on what makes innovative drivers in practice successful and how to tackle those challenges of the market.

The course is divided into three sections: First, we will introduce the fundamentals of digital health and health information systems. Building on this, we cover in the second part advanced topics on the application of digital health technologies such as data mining, AI, and data privacy. In the third section, we tackle the issue of how digital technologies can provide the basis for innovation. Here the focus is on digital innovation at the consumer-end such as mobile and digital health platforms. We will discuss implications for digital business models and marketing in the online space.

Students apply the learned content to develop an innovative healthcare solution in a project group. Several rounds of feedback are provided, allowing the groups to improve their ideas. Students identify a specific application scenario and independently obtain secondary data and use the data to assess the feasibility of the idea. The course concludes with a summary and wrap-up, in which the students pitch the case they investigate for their synopsis paper.

Learning Objectives

LO 1.   Describe the function, challenges, and opportunities of using digital technologies in health care.

LO 2.   Identify and describe the requirements for designing, implementing, and using digital technologies in health care.

LO 3.   Analyze and discuss specific healthcare IT cases based on the theories presented in the course, and provide recommendation for practice.

LO 4.   Reflect on how the health care industry can leverage on digital technologies to address current health care objectives and requirements.

Examination

  • 6 ECTS
  • Form: Oral exam + Project Report (group - 4 pages)
Department Winfo
Digital-Innovation-Lab
ECDF
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