2024/2025 KAN-CIHCO1602U Frontiers of Digital Healthcare
English Title | |
Frontiers of Digital Healthcare |
Course information |
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Language | English |
Course ECTS | 7.5 ECTS |
Type | Mandatory (also offered as elective) |
Level | Full Degree Master |
Duration | One Quarter |
Start time of the course | Second Quarter |
Timetable | Course schedule will be posted at calendar.cbs.dk |
Max. participants | 20 |
Study board |
Study Board for MSc in Business Administration and Innovation
in Health Care
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Course coordinator | |
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Main academic disciplines | |
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Teaching methods | |
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Last updated on 23-04-2024 |
Relevant links |
Learning objectives | ||||||||||||||||||||||||||
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Course prerequisites | ||||||||||||||||||||||||||
This elective course is open to master-level
students of all study programmes inside and outside CBS. There are
no formal prerequisites to participate. Prior knowledge of
healthcare or digital technologies field is helpful, but not a
must.
This is a mandatory elective course for the MSc in Business Administration and Innovation in Health Care. To sign up send a 1-page motivational letter and a grade transcript to ily.stu@cbs.dk before the registration deadline for elective courses. You may find the registration deadlines on my.cbs.dk ( https://studentcbs.sharepoint.com/graduate/pages/registration-for-electives.aspx ) Please also remember to sign up through the online registration. |
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Examination | ||||||||||||||||||||||||||
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Course content, structure and pedagogical approach | ||||||||||||||||||||||||||
This course aims to deliver participants from various backgrounds with insights into the latest developments, technologies, and trends at the frontier of digital healthcare innovation.
Digital technology innovations are poised to disrupt the healthcare landscape, a sector which has often been thought of as one of the least digitized industries. Omnipresent trends in the likes of online social communities, ubiquitous mobile devices, and the surge of smart sensor technologies, have culminated in the exponential growth of available data that bear significant implications for healthcare provision. Additionally, advances in artificial intelligence, cloud computing, machine learning, and other technologies have created unprecedented opportunities for harvesting, storing, processing, and utilizing these massive data repositories, for the benefit of patients, healthcare providers, and other stakeholders in the healthcare industry.
A burgeoning number of healthcare startups are currently aiming to disrupt the traditional model in which healthcare services are provided by exploiting advances in digital technologies to assist patients and healthcare professionals at the point of care. At the same time, incumbent players in the healthcare industry (e.g., healthcare providers, pharmaceutical firms, and insurers) as well as new entrants (e.g., information technology leaders such as IBM, Google, and Microsoft) are pushing forward to foster digital innovation under the roof of their own established business models. From a societal standpoint, digital innovations deliver enormous opportunities to bolster the chances of achieving the triple mission of higher quality, lower cost, and better access to healthcare systems worldwide.
With digital innovations holding the promise of resolving focal challenges in healthcare, healthcare is transforming into a vibrant space. Governmental institutions, incumbent players, and techological startups are currently seeking much-needed talent that comprehends digitalization trends and is able to turn health data into information pertinent to tackling contemporary problems in the field of healthcare.
This course is designed to acquaint participants with the latest technological developments and trends at the frontier of digital healthcare innovation, providing participants with hands-on experience on analyzing and exploiting health data in a real-world setting. Over the duration of this course, we will cover modern trends in digital healthcare innovation, including: big data, cognitive computing, machine learning, wearables, as well as mobile and social platforms. For each of these trends, we will not only drill into its underlying conceptual, theoretical, and methodological foundations, but we will also touch on concrete application scenarios and business cases across different healthcare system contexts. In parallel to these conceptual elements, course participants will acquire and apply basic data mining and machine learning techniques to tackle contemporary problems in healthcare.
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Description of the teaching methods | ||||||||||||||||||||||||||
Classroom teaching blends classic lectures with
in-class discussions and small interactive exercises. The classroom
sessions will primarily focus on the introduction of technological
trends and their applications to the field of healthcare.
Participants will have a hands-on module on basic machine learning techniques . In order to link classroom activities with online pedagogical materials as well as reflect on the methodological and technical foundations of the course, practical demonstrations will take place in class to showcase how machine learning techniques can be applied. |
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Feedback during the teaching period | ||||||||||||||||||||||||||
Students will receive feedback amongst others
- in class during and after discussion and exercise modes - during office hours, on request - at the oral examination |
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Student workload | ||||||||||||||||||||||||||
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Expected literature | ||||||||||||||||||||||||||
Relevant literature:
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