Introduction to Health Data Analytics

Course description

Globally, there is a rapid growth in demand for Data Scientists, with an estimated shortfall of two million skilled workers in 2017. Worldwide, universities are positioning themselves to offer training and research leadership required to take advantage of data analytics. Indeed, there are new foci of research and programmes dealing with aspects of data analytics in many universities. Although many universities in developing countries are offering courses in mathematics or statistics relevant to data science to address the skills shortage, there is inadequate focus on higher-level data analytics skills.

These new foci present several critical challenges in the Global South that inhibit these new research and academic offerings. Firstly, there is a limitation on the knowledge required to train, teach, research and deploy the right techniques for health data analytics in most universities. Secondly, the diversity and multi-disciplinary nature and technical requirements in data analytics make it a challenge even for the better-endowed universities to develop and maintain a talented team to offer these courses. The lack of health data analysts means Africa cannot adequately harness the data revolution’s potential for the quality of health for her citizens. Indeed, in the global south, most healthcare organisations do not have the necessary skills to capture, analyse, and synthesise the valuable information and knowledge that can be derived from big data. Currently, there are no health data analytics programmes offered online in Africa.
Introduction to Health Data Analytics

Course details

1. Introduction to Applied Statistics in Health
This unit will introduce participants to assess and support decision-making in health through applying health analytics knowledge and skills in different cases.

2. Introduction Epidemiology and Biostatistics
This unit will provide an overview of the main types of study design(s) used in epidemiological studies. It will provide an overview of managing data and identifying different data types. Provide brief introduction to the concepts of bias and confounding in epidemiological studies. This unit will also provide a general overview of the different elements of statistical tests. Including R as part of tutorials (Self Study).

3. Introduction to Omics Data
This unit will introduce participants to key concepts and methodologies used in -omics as well as an overview of the different types of omics. Specific focus will be on genomics (the study of the human genome). Consequences of variations in DNA will be explained. Using a short case study the unit will demonstrate how health informatics and omics are integrated.

4. Introduction to Text Analytics
This unit will introduce participants to analytics packages.

5. Introduction to Data Visualisation
This unit will introduce concepts related to the design of management reports and graphics.
Units with a practical component such as analytic software and data retrieval applications will provide opportunities for skills development.

Statement of purpose

The purpose of the course is to equip people working in healthcare settings with an overview of health analytics and give them skills to use health data for effective decision making in health. Therefore, expanding the capacity of individuals working in healthcare settings with regards to improving coordination, management and application of health data information. The purpose of this course is also to expand the university’s intellectual footprint both in the North and the South through collaborative efforts with partner institutions.

Course outcomes

On completion of this course participants should be able to:
• Assess and make decisions about health conditions using health data and information.
• Comprehend basic epidemiology and biostatistics concepts.
• Use tools and methodologies for health data analytics (current software).
• Understand and apply key concepts and methodologies used in Omics.
• Extract and analyse health data and information from different sources.
• Design health management reports.

Entry level requirements

• Selection - applicants will be subject to a selection procedure determined by the Faculty.
• Candidates who have completed an undergraduate degree or equivalent (NQF Level 7) in cognate disciplines.

Planned course dates

Applications are open. Application deadline: 21 July 2024

Course Coordinator

Lukhanyo Nyati
Lukhanyo Nyati

Assessment criteria

The participants will complete a comprehensive assignment (Continuous Final Assessment, CFA) to assess knowledge, understanding and application. Participants will be required to prepare a management report demonstrating at least three of the following:
a) Analysis of health data and information with recommended lines of action or interventions
b) Epidemiological and biostatistical implications of the analysed data
c) The use of Omics data in creating a treatment plan for a given condition
d) Text analysis of health data and information
e) Develop a management dashboard to monitor health-related information.

Assessment methods

Continuous Final Assessment:
• Submission of mini-tasks/milestones or building blocks towards the main assignment based on each unit, including individual and/or group assignments, practical applications, presentations, case studies, attendance and the completion of a comprehensive assignment.

Teaching & learning strategies

The specific strategies to be used are:
• Seminars and presentations including pre-recorded videos
• Online facilitation
• Practical applications and sessions
• Take-home assignments
• Discussion forums
• Self-paced reflections
• Reflective summaries
• Opinion pieces

Course material & equipment

The instructional and learning material that will be used will include:
• Online platform (Learning Management System, i.e., Aspire)
• Industry and open-sources health-related datasets and case studies
• Computer applications and statistical packages (Power BI for visualisation, R for programming, SPSS, among others)
• Online conferencing platforms (Zoom and Google Meet)
• Reading material (books, articles and power point presentations)

Modes of delivery

Flexible modes of delivery will be implemented (hybrid, blended and online).
Online conferencing platforms such as Zoom and Google Meet will be used for synchronous sessions and discussion forums.

Participants should have:
• Stable internet connectivity
• Laptop with the capacity to handle complex data analysis

Course venue

Online and/or in-person. In person lectures will take place at the Faculty of Community and Health Sciences, Bellville Campus.

Alignment with UWC mission & strategic initiatives

The program is aligned to the following IOP goals:
Goal Area 1:
The Student Experience seeks to provide students with a meaningful and stimulating university experience through strategic approaches to co-curricular support, student engagement strategies and enrolment management, geared towards achieving the University’s medium- to long-term ambitions for its size and shape.

Goal Area 2:
Learning and Teaching aims to provide students with research-led teaching that is contextually responsive, embedded in a relevant and dynamic curriculum and supported by diverse assessment approaches, aligned to achieving the desired learning outcomes.

Furthermore, the CE Course meets the cross-cutting theme of internationalization since the course is a collaborative effort across four different universities in four countries, including the University of the Western Cape, The Kenya Methodist University, Muhimbili University of Health and Allied Sciences, and Neu-Ulm University of Applied Sciences.

These goals further align with the following SDG goals:
• Goal 4:
Ensure inclusive and equitable quality education and promote life-long learning opportunities for all. The course promotes continuous learning opportunities for professionals.
• Goal 17:
Strengthen the means of implementation and revitalize the global partnership for sustainable development.
Course Details

Introduction to Health Data Analytics

Course Code: P7CE0005
Faculty of Community and Health Sciences
Inter-Professional Education Unit (IPEU)
Health Data Analytics
Area of Interest
Health information analysis
Certificate of Competence
R4 500