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All qualifications and part qualifications registered on the National Qualifications Framework are public property. Thus the only payment that can be made for them is for service and reproduction. It is illegal to sell this material for profit. If the material is reproduced or quoted, the South African Qualifications Authority (SAQA) should be acknowledged as the source. |
| SOUTH AFRICAN QUALIFICATIONS AUTHORITY |
| REGISTERED QUALIFICATION: |
| Master of Health Data Analytics |
| SAQA QUAL ID | QUALIFICATION TITLE | |||
| 122901 | Master of Health Data Analytics | |||
| ORIGINATOR | ||||
| University of the Western Cape | ||||
| PRIMARY OR DELEGATED QUALITY ASSURANCE FUNCTIONARY | NQF SUB-FRAMEWORK | |||
| CHE - Council on Higher Education | HEQSF - Higher Education Qualifications Sub-framework | |||
| QUALIFICATION TYPE | FIELD | SUBFIELD | ||
| Master's Degree | Field 10 - Physical, Mathematical, Computer and Life Sciences | Mathematical Sciences | ||
| ABET BAND | MINIMUM CREDITS | PRE-2009 NQF LEVEL | NQF LEVEL | QUAL CLASS |
| Undefined | 180 | Not Applicable | NQF Level 09 | Regular-Provider-ELOAC |
| REGISTRATION STATUS | SAQA DECISION NUMBER | REGISTRATION START DATE | REGISTRATION END DATE | |
| Registered | EXCO 0527/24 | 2024-10-03 | 2027-10-03 | |
| LAST DATE FOR ENROLMENT | LAST DATE FOR ACHIEVEMENT | |||
| 2028-10-03 | 2031-10-03 | |||
| In all of the tables in this document, both the pre-2009 NQF Level and the NQF Level is shown. In the text (purpose statements, qualification rules, etc), any references to NQF Levels are to the pre-2009 levels unless specifically stated otherwise. |
This qualification does not replace any other qualification and is not replaced by any other qualification. |
| PURPOSE AND RATIONALE OF THE QUALIFICATION |
| Purpose:
The purpose of the Master of Health Data Analytics is to develop skills in health data analytics to address the growing burden of noncommunicable and communicable diseases in low- and middle-income countries. Thus, the course aims to develop a critical mass of professionals and build capacity in the African continent borne out of a need highlighted by 120 participants from different countries in Africa, who attended the summer/winter schools in data analytics. The need for the skills has also been highlighted by the Western Cape Government Department of Health and Wellness data centre, which requires individuals with specific skills in health data analytics. Given the location, the institution is firmly placed to contribute the requisite skills to the department. This qualification will be implemented online at the institution and other Sub-Saharan universities through joint research collaboration. It envisages improving the online academic skills, offerings, and competitiveness of participating institutions by including online qualifications in the basket of offerings (flexible learning offering). The qualification will advance the collaboration between the government (Health Sector), industry, and universities for mutual benefits and contribute to national imperatives using applied research. Applied research that makes an immediate contribution to business and society is a strategic drive for the institutions. The qualification also benefits from extending the university's intellectual footprint in both the African and European countries where the partnering institutions are based. Rationale: There is a rapid growth in demand for Data Scientists globally with an estimated shortfall of two million skilled workers in 2017. Institutions are positioning themselves to offer training and research leadership required to take advantage of data analytics. The need to train professionals to close the gap in health data analytics has also been identified. An increasing amount of personal and population data has led to a need for complex analytical techniques to make sense of these data. Although many institutions 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 in health. These new foci present several critical challenges in the global south. Firstly, there is limited capacity to train, teach, research and deploy the right techniques for health data analytics in many 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. The COVID-19 pandemic demonstrated the need for individuals who are skilled in data analytics. Indeed, in the global south, most healthcare organisations do not have the necessary skills to capture, analyse, and synthesize the valuable information and knowledge that can be derived from big data. Currently, and to the best of our knowledge, there are no health data analytics programmes offered online in Africa. This qualification is targeted at graduates both from the healthcare professions and the sciences who are interested in expanding their knowledge and skills in data analytics. The online nature of this programme allows for access to individuals across the African continent and beyond. Due to the nature of the offering of this programme, individuals who are often in permanent positions will also have access. Graduates from this Programme would be able to source employment from health data centres in their specific countries, as well as the private and educational sectors. |
| LEARNING ASSUMED TO BE IN PLACE AND RECOGNITION OF PRIOR LEARNING |
| Recognition of Prior Learning (RPL):
The institution's RPL policy for postgraduate study makes provision for RPL for advanced standing on a case-by-case basis. Each application is considered and approved in collaboration with the relevant Faculty, supervisor (content specialist/academic), RPL Unit and the institution's Quality Assurance office. Relevant research experience and formal and non-formal learning are evaluated. RPL for access: Access to postgraduate studies through Senate discretion is common practice at many universities. It usually entails candidates producing evidence of relevant learning achievement through work and/or other experience. Each application is considered and approved in collaboration with the relevant faculty, supervisor (content specialist/academic), RPL Unit and the Quality Assurance Office. Relevant research experience, formal and non-formal learning, current research as well as conferences attended are evaluated. The Final decision rests with the Senate Higher Degrees Committee in terms of its standing Orders on recommendation from the Faculty Higher Degrees Committee which it is awarded and accepted. Entry Requirements: The minimum entry requirement for this qualification is: Or Or Or Or Or Or Or Or |
| RECOGNISE PREVIOUS LEARNING? |
| Y |
| QUALIFICATION RULES |
| This qualification consists of the following compulsory modules at NQF Level 9 totalling 180 Credits.
Compulsory modules, Level 9, 180 Credits: |
| EXIT LEVEL OUTCOMES |
| 1. Demonstrate the ability to engage with health data analytics in creating value-based health systems and policies.
2. Demonstrate the ability to select the appropriate health data. 3. Demonstrate the ability to design methodologies, techniques, processes, or technologies for using health data in complex health decision-making. 4. Demonstrate the ability to engage with current research and practices used in health data analytics. 5. Make autonomous ethical decisions in health data use and integrate and evaluate health data in governance procedures. 6. Conduct and complete a research project using health data analytics. 7. Communicate and defend ideas, and techniques, taking full responsibility for processes or technologies used in health data analytics. 8. Implement health data analytics interventions in their organizations. |
| ASSOCIATED ASSESSMENT CRITERIA |
| Associated Assessment Criteria for Exit Level Outcome 1:
Associated Assessment Criteria for Exit Level Outcome 2: Associated Assessment Criteria for Exit Level Outcome 3: Associated Assessment Criteria for Exit Level Outcome 4: Associated Assessment Criteria for Exit Level Outcome 5: Associated Assessment Criteria for Exit Level Outcome 6: Associated Assessment Criteria for Exit Level Outcome 7: Associated Assessment Criteria for Exit Level Outcome 8: INTEGRATED ASSESSMENT The qualification will use both formative and summative assessments. Formative Assessment: Formative assessment will be continuous, with regular feedback from tutors and lecturers. It will include assignments, presentations, and projects. These activities will be marked by individual lecturers and given different weightings (e.g. 10%) as part of formative assessment. Feedback will be provided to learners to enable them to see their performance and make improvements where necessary. A minimum of two formative assessment tasks will be given in each module which counts at least 60% towards the final assessment mark. Summative Assessment: Summative assessment will occur at the end of each module, at the end of a semester. It will be in the form of various assessment tasks written examinations, presentations, assignments, and case studies usually written or submitted in May/June and in October/November of each year. The summative assessment will contribute 40% to the final assessment mark. In the research methods module, the final assessment task will be in the form of a submission of the proposal. The final assessment task will be in the form of a research report in the mini-thesis research module. The research report will be assessed by two examiners, one of which will be external to the university. This form of assessment will cover the work done in a semester and determine learners' progression from one level to another. Modules with a summative assessment will include a final task geared towards integrating knowledge, skills, and attitudes related to health data analytics education and practice. All summative assessments will be externally moderated. |
| INTERNATIONAL COMPARABILITY |
| While international universities in terms of their National Qualifications Framework are not comparable and country-specific the following needs to be noted.
Country: United Kingdom Institution: The University of Leeds Qualification Title: Data Science and Analytics for Health MRes Duration: 12 months full-time, 24 months part-time Entry requirements: Either a 1st class degree at Bachelor or Masters level or 2:1 (Hons) plus (minimum 3 years) first-hand work-related experience in one or more quantitative science or healthcare settings. Purpose: The Data Science and Analytics for Health MRes provides comprehensive training in the management, modelling and interpretation of health and healthcare data used by clinical, behavioural, and organisational sources. The qualification draws on recent advances in information technology, data management, statistical modelling (for description/classification and prediction), machine learning and artificial intelligence. It's designed to enable you to develop both the technical and applied skills required for addressing real-world challenges in real-world health and healthcare contexts. This qualification recognises and utilises recent advances in information technology, data management, statistical modelling (for description/classification, causal inference, and prediction), machine learning and artificial intelligence. Qualification structure: The qualification consists of the following compulsory and elective modules. Compulsory Modules, 150 Credits: Elective Modules, 30 Credits (Select any two modules): Assessment: Assessments will use a range of techniques including case studies, technical reports, presentations, in-class tests, assignments, and exams. Optional modules may also use alternative assessment methods. Similarities: Country: United States of America Institution: University of Rochester Qualification Title: Master of Science in Data Science Credits: 30 credits Duration: Two to three semesters of full-time study. Entry Requirements: Purpose: The qualification is designed for learners with a background in any field of science, engineering, mathematics, or business. Qualification structure: Compulsory Modules, 20 Credits: Elective Modules, 10 Credits (Select any three modules for a minimum of 10 credits, from the following application areas): Similarities: Differences: |
| ARTICULATION OPTIONS |
| This qualification allows possibilities for both horizontal and vertical articulation.
Horizontal Articulation: Vertical Articulation: Diagonal Articulation There is no diagonal articulation for this qualification. |
| MODERATION OPTIONS |
| N/A |
| CRITERIA FOR THE REGISTRATION OF ASSESSORS |
| N/A |
| NOTES |
| N/A |
| LEARNING PROGRAMMES RECORDED AGAINST THIS QUALIFICATION: |
| NONE |
| PROVIDERS CURRENTLY ACCREDITED TO OFFER THIS QUALIFICATION: |
| This information shows the current accreditations (i.e. those not past their accreditation end dates), and is the most complete record available to SAQA as of today. Some Primary or Delegated Quality Assurance Functionaries have a lag in their recording systems for provider accreditation, in turn leading to a lag in notifying SAQA of all the providers that they have accredited to offer qualifications and unit standards, as well as any extensions to accreditation end dates. The relevant Primary or Delegated Quality Assurance Functionary should be notified if a record appears to be missing from here. |
| 1. | University of the Western Cape |
| All qualifications and part qualifications registered on the National Qualifications Framework are public property. Thus the only payment that can be made for them is for service and reproduction. It is illegal to sell this material for profit. If the material is reproduced or quoted, the South African Qualifications Authority (SAQA) should be acknowledged as the source. |