Graduate Certificate in Health Informatics
The fields of health informatics and analytics improve healthcare processes and solutions through the collection, organisation and analysis of health data. It drives the transformation of public health, health care and health research, and plays a critical role in collaboration among healthcare providers.
Programme Structure
| Programme Requirements | Complete 12 Modular Credits (MCs) (Students must obtain at least 75% attendance for each module) |
|---|---|
| Modules | SPH5104 Analytics for Better Health (4 MCs) SPH5411 Information Technology in Healthcare (4 MCs) SPH5414 Informatics for Health (4 MCs) |
| Maximum Candidature | Part-time: 3 years |
| Completion Requirements | Cumulative Average Point (CAP) of at least 2.00 (equivalent to an average of ‘C’) |
For more information on Modular Credits (MCs) and Cumulative Average Point (CAP), please refer to: https://www.nus.edu.sg/registrar/academic-information-policies/graduate/modular-system
Admission Requirement
A Bachelor’s degree. Candidates with other qualifications and relevant work experience may be considered on a case-by-case basis.
Note: Meeting the admission requirement does not imply an automatic admission into the programme.
Modules
Dates: 19 January – 19 April 2024, every Friday
Time: 6pm – 9pm (SGT)
Venue: MD1 Tahir Foundation Building, National University of Singapore
SSG Course Code: TGS-2020507482
Find out more about this module here.
Dates: 13 – 17 May 2024
Time: 9am – 6pm
Venue: MD1 Tahir Foundation Building, National University of Singapore
SSG Course Code: TGS-2020507485
Health informatics transforms health care by analysing, designing, implementing, and evaluating information and communication systems that enhance individual and population health outcomes, improve care, and strengthen the clinician-patient relationship.
Learning Outcomes
To equip students with use knowledge of patient care combined with understanding of informatics concepts, methods, and tools to:
- Assess information and knowledge needs of health care professionals and patients;
- Characterise, evaluate, and refine clinical processes;
- Develop, implement, and refine clinical decision support systems, and participate in the procurement, customisation, development, implementation, management, evaluation, and continuous improvement of clinical information systems.
Who Should Attend?
Participants interested in understanding the roles of IT and Data analytics in healthcare, and in applying domain knowledge and skills to promote public health and improve patient care in their workplace.
Course Instructors
Assistant Professor Ling Zheng Jye
Dr Ling is a health informatician working in public sector healthcare. His interests are in Healthcare Management, Clinical Decision Support, Design Thinking, Public Health, Primary Care physician in the Intermediate & Long Term Care sector, especially nursing homes and primary care clinics. He is involved with undergraduate and postgraduate teaching for medical informatics. Dr Ling enjoys helping his colleagues deliver care more effectively and happily via tailoring products to fit the local workflow.
Assistant Professor Feng Mengling
Dr Feng’s research is to develop effective data analytics and Artificial Intelligence (AI) solutions to extract actionable knowledge to improve the quality of care. His research brings together concepts and tools across machine learning, optimization, signal processing, statistical causal inference and big data management. In particular, he has been publishing on physiological signal forecasting, modeling of disease progress trajectory, dynamic patient phenotyping, statistical understanding of treatment effects and management of heterogeneous medical big data. Dr Feng works closely with clinicians around the world, and he also collaborates with major healthcare and IT companies, such as MSD, Philips and SAP. Dr Feng’s work was recognised by both well-established journals, such as Science Translational Medicine, JAMA, Intensive Care Medicine and top international conferences, such as KDD, AAAI and AMIA.
View his full profile here.
Fees and Funding Per Module
| Subsidy available | Fee payable after subsidy* | |
| International Participant | – | S$8257.68 |
| Singapore Citizen aged 39 years & below / Permanent Resident | SSG Funding | S$2477.30 |
| Singapore Citizen aged 40 years & above | SSG Funding & Mid-Career Enhanced Subsidy | S$948.10 |
| Singapore Citizen / Permanent Resident Sponsored by SMEs | SSG Funding & Enhanced Training Support for SMEs | S$948.10 |
Remarks:
- All enrolled candidates will also be required to pay a Student Services Fee of S$25.46*.
- Self-Sponsored participants can use their SkillsFuture Credits to pay for or offset course fees. SkillsFuture Credit claim has to be submitted to SkillsFuture Singapore (SSG) within 60 days before course commencement. SSG will not allow claims to be made after the first day of the course.
- The University reserves the right to review and adjust the course fees and make changes to the programme structure and requirements as necessary and accordingly without prior notice.
*Prices stated above are inclusive of 8% GST.
Application
- Application closes on 05 November 2023
- For more information on this programme, please contact us at sph_cpe@nus.edu.sg.
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