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2021/2022  KAN-CIHCO1602U  Frontiers of Digital Healthcare

English Title
Frontiers of Digital Healthcare

Course information
Language English
Course ECTS 7.5 ECTS
Type Elective
Level Full Degree Master
Duration One Quarter
Start time of the course First Quarter
Timetable Course schedule will be posted at calendar.cbs.dk
Max. participants 50
Study board
Study Board for MSc in Business Administration and Innovation in Health Care
Course coordinator
  • Chee-Wee Tan - Department of Digitalisation
Main academic disciplines
  • Information technology
  • Innovation
  • Statistics and quantitative methods
Teaching methods
  • Blended learning
Last updated on 27-01-2021

Relevant links
Learning objectives
  • describe technology trends at the frontier of digital healthcare innovation, including social communities, cloud computing, mobile health, big data, and cognitive computing
  • relate digital healthcare innovation trends to key concepts from the academic literature and draw connections in-between relevant theoretical concepts
  • explain and apply methods and techniques of data analysis and machine learning in scenarios of digital healthcare
  • reflect on their individual learning progress and identify touchpoints, intersections, and gaps in comparison to their prior knowledge
  • identify a research opportunity at the digital healthcare frontier and conduct independent desk-based research involving secondary data to investigate this issue
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.
Examination
Frontiers of Digital Healthcare:
Exam ECTS 7,5
Examination form Oral exam based on written product

In order to participate in the oral exam, the written product must be handed in before the oral exam; by the set deadline. The grade is based on an overall assessment of the written product and the individual oral performance, see also the rules about examination forms in the programme regulations.
Individual or group exam Individual oral exam based on written group product
Number of people in the group 2-3
Size of written product Max. 15 pages
Assignment type Project
Duration
Written product to be submitted on specified date and time.
20 min. per student, including examiners' discussion of grade, and informing plus explaining the grade
Grading scale 7-point grading scale
Examiner(s) Internal examiner and second internal examiner
Exam period Autumn
Make-up exam/re-exam
Same examination form as the ordinary exam
If a student is ill during the regular oral exam, he/she will be able to re-use the project at the make-up exam. If a student is ill during the writing of the project and did not contribute to the project, the make-up exam can be written individually or in groups (provided that other students are taking the make-up/re-exam). If the student did not pass the regular exam or did not show up at the oral exam, he/she must make a new revised project/business plan (confer advice from the examiner) and hand it in on a new deadline specified by the secretariat.
Course content, structure and pedagogical approach

This course aims to provide participants from various backgrounds with insights into the latest trends, technologies, and developments at the frontier of digital healthcare innovation.

 

Digital technology innovations are poised to disrupt the healthcare landscape, a sector that has often been thought of as one of the least digitized industries. Omnipresent trends such as online social communities, ubiquitous mobile devices, and the surge of smart sensor technologies, lead to an exponential growth of available data that can have great relevance to healthcare provision. In addition, advances in cloud computing, machine learning, artificial intelligence, and other technologies make unprecedented opportunities available to store, process, and use these data at large scale, for the benefit of consumers, healthcare providers, and other stakeholders in the healthcare field.

 

A boosting number of healthcare startups are currently aiming to disrupt the traditional model in which healthcare services are provided by exploiting these and other digital technology trends and helping patients and healthcare professionals at the point of care. At the same time, the larger 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 Microsoft, Google, and IBM) are pushing forward to foster digital innovation under the roof of their own established business models. From a societal perspective, digital innovations provide enormous opportunities to improve the achievement of the global triple aim of higher quality, lower cost, and better access in healthcare systems worldwide.

 

In sum, digital innovations hold the promise to solve some of the major challenges in healthcare. Hence, healthcare is turning from a less digitized industry into a vibrant field: Tech startups, established players, as well as governments currently seek for the much-needed talent that understands these tech trends and is able to turn health data into information relevant to the problems and opportunities in the healthcare field.

 

This course is designed to make the participants acquainted with the latest trends, technologies, and developments at the frontier of digital healthcare innovation and to provide them with hands-on skills needed to analyze and exploit health data in a real-world scenario. Over the five weeks of this course, we cover several trends in digital innovation, including: social, cloud, mobile, big data, and cognitive. For each of these trends, we drill both into the underlying conceptual, theoretical, and methodological foundations, as well as into concrete cases and application scenarios in different healthcare system contexts. In parallel to these conceptual elements, course participants will acquire basic data mining and machine learning skills and learn how to apply these techniques on concrete healthcare problems.

 

As the course proceeds, the participants will work in groups to compile a learning diary with their summary of, and reflections about, each of the different trends reviewed in the lecture including its drivers and inhibitors, enabling technologies, and potential application scenarios. This learning diary will form the basis for the first part of the written product (the project report). Towards the end of the course, students will then identify a specific application scenario (i.e., a case) and independently acquire secondary data to analyze this data using the quantitative methods acquired in this course. This analysis should inform their case study research, which then forms the second part of the written product.
Description of the teaching methods
This course adopts a blended learning format. This means it combines classroom teaching with the use of online media and resources.

The classroom teaching will combine classic lecture modes with in-class discussions and small interactive exercises. The classroom sessions primarily focus on the technology trends and their applications to the healthcare field.

From session to session, participants will work through an open online course on machine learning. These self-paced online modules primarily focus on acquiring basic machine learning techniques. They are intentionally not limited to the application in the healthcare field.

In order to link the online and classroom activities and reflect on some of these methodological and technical foundations, hands-on demonstrations will be provided in class that showcase specific tools or methods.

The course also aims to include industry experts as guest speakers as necessary and adequate.
Feedback during the teaching period
Students will receive feedback amongst others
- in class during and after discussion and exercise modes
- online in quizzes of the self-paced study modules
- from their peers they work with in groups
- during office hours, on request
- at the oral examination
Student workload
teaching 30 hours
preparation of class 60 hours
project 90 hours
exam preparation 35 hours
Expected literature

Relevant literature: 
(subject to change)

 
Last updated on 27-01-2021