Level: Intermediate
Duration: 1 day
Venue: HMI Institute
Minimum number to run: 10 participants
This program provides an in-depth appreciation on the application of big data in healthcare supply chain. Upon completion of this program, participants will learn how to use descriptive, diagnostic, predictive and prescriptive analytics to uncover insights in the Healthcare Supply Chain Environment. Participants will gain understanding of the future opportunities of integrating AI and analytics in healthcare services and the positive impacts it will have on healthcare operations.
Professionals, managers and executives (PMEs) who are entering the healthcare industry as well as healthcare professionals who aspire to move into a management role.
- What is Artificial Intelligence, Business Intelligence and Big Data in Hospitals?
- Applications of Business Intelligence in Hospitals
- Best practices for analyzing healthcare data
- Key challenges in hospital SCM
- Application of big data for fact-based decision making during:
a) Value Analysis
b) Sourcing and Procurement
c) ERP Implementation
d) Process Improvement
e) Inventory Management - How to establish effective analytics and align to business goals
- Application of AI for demand driven material requirements planning
- Practicum – Designing and the application of supply chain data analytics dashboard
A. Knowledge and Understanding (Theory Component)
At the end of this course, participants should be able to:
- Identify opportunities for the application of data analytics in Healthcare SCM
- Identify areas in their own environment to apply descriptive, diagnostic, predictive and prescriptive analytics
- Understand the important role of logistics, pharmacy operations management, inventory management and supply chain management in healthcare operations
B. Key Skills (Practical Component)
At the end of this course, participants should be able to:
- Learn how to effectively execute data analytics that will capture and integrate large complex data sets
- Deploy big data technology to manage the data effectively and efficiently
| Time | Agenda |
|---|
| 08:30 - 09:00 | Introduction to Healthcare Supply Chain Management |
| 09:00 - 10:00 | What is AI, BI and Business Applications in Hospitals |
| 10:00 - 10:30 | Best Practices for Analyzing Healthcare Data |
| 10:30 - 11:00 | Break |
| 11:00 - 11:30 | Key Supply Chain Challenges |
| 11:30 - 12:00 | Application of big data and AI in Healthcare SCM |
| 12:00 - 12:30 | How to establish effective analytics and align to business goals |
| 12.30 - 13:00 | Importance of Supply Chain Management in healthcare operations |
| 13:00 - 14:00 | Lunch |
| 14:00 - 16:00 | Designing and the application of supply chain data analytics dashboard |
- Possess at least two years of working experience.
Lawrence Koh
Lawrence is a healthcare supply chain professional with 30 years of experience working in various hospitals and clinics in South East Asia, China and the Middle East. He last served as the Executive Director of Supply Chain at Cleveland Clinic Abu Dhabi, managing a team of 100 logisticians, procurement specialists and data analyst, before returning to Singapore.
He is a Supply Chain consultant with Intermedika Consulting (USA), a hospital management company; a senior advisor with TVM Capital Healthcare (SEA), a venture capital company and at the same time operating his own consultancy business at Asia Healthcare Logistics in Singapore.
Lawrence received his Bachelor of Business degree with distinction in Transport and Logistics Management from the Royal Melbourne Institute of Technology, Australia. He is a citizen of Singapore and a Certified Materials & Resource Professional with the American Hospital Association USA.
Please submit the following documents to cet@suss.edu.sg:
- Coloured copy (back and front) of NRIC for Singaporeans and PRs, or "Employment"/"S" Pass for foreign applicant
- Recent payslip or income statement (For WTS scheme only)
- Application form
| International Participants | S'poreans (aged below 40) and PRs | SkillsFuture Mid-Career Enhanced Subsidy1
(S'poreans aged 40 and above) | Workfare Training Support2
(S'poreans aged 35 and above, and earn ≤ $2,000 per month) | Enhanced Training Support for SMEs3 |
|---|
| Full Course fee (A) | $850 | $850 | $850 | $850 | $850 |
| SSG grant (70%) (B) | - | ($595) | ($595) | ($595) | ($595) |
| Nett course fee (A) - (B) = (C) | $850 | $255 | $255 | $255 | $255
|
| 7% GST on nett course fee (D) | $59.50 | $17.85 | $17.85 | $17.85 | $17.85 |
| Total nett course fee payable, including GST (C) + (D) = (E) | $909.50 | $272.85 | $272.85 | $272.85 | $272.85 |
| Less additional funding if eligible under various schemes (F) | - | - | ($170) | ($212.50) | ($170) |
| Total nett course fee payable, including GST, after additional funding from the various funding schemes (E) - (F) = (G) | $909.50 | $272.85 | $102.85 | $60.35 | $102.85 |
1 Mid-Career Enhanced Subsidy: Singaporeans aged 40 and above may enjoy subsidies up to 90% of the course fees.
2 Workfare Training Support: Singaporeans aged 35 and above (13 years and above for Persons with Disabilities) and earning not more than $2,000 per month may enjoy subsidies up to 95% of the course fees.
3 Enhanced Training Support for SMEs: SME-sponsored employees (Singaporean Citizens and PRs) aged 21 and above may enjoy subsidies up to 90% of the course fees.
- Participants are required to achieve at least 75% attendance and/or sit and pass any prescribed examinations/assessments or submit any course/project work (if any) under the course requirement.
- Participants are required to complete all surveys and feedback related to the course.
- The course fees are reviewed annually and may be revised. The University reserves the right to adjust the course fees without prior notice. Singapore University of Social Sciences reserves the right to amend and/or revise the above schedule without prior notice.
For clarification, please contact the Centre for Continuing and Professional Education (CCPE) via the following:
Telephone: +65 6248 0263
Email:
CET@suss.edu.sg