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 Nursing. 

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

Course content and structure

In this course, participants with a background in (business) informatics, medicine, nursing, or related fields will gain insights into trends, technologies, and developments in digital healthcare innovations. Amidst the current Corona pandemic, healthcare is still considered one of the least digitized industries, partly due to high data security requirements and partly due to limited data availability. 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. 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 and technologies 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. This includes aspects on systems development, business models, data mining as well as legal regulations. During the course, students receive input through pre-recorded video sessions that will be discussed in class. First, we will introduce the foundations of digital health and information systems in healthcare. Building on this, we cover advanced topics such as data mining, AI, and data privacy in health. In parallel, 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. This analysis will be presented and summarized within a project report.

Learning Objectives

• Describe the function, challenges, and opportunities of using digital technologies in healthcare
• Identify and describe requirements for the design, implementation and use of digital technologies in the healthcare context
• Understand and explain methods and techniques of data analysis and machine learning in scenarios of digital healthcare
• Identify a research opportunity in the realm of digital healthcare innovation and conduct independent desk-based research involving secondary data to investigate this issue

Examination

• 6/7.5 ECTS
• Form: Oral exam (Present Pitchdeck) + Project Report (Idea Paper, 15 pages)