Identify Potential Product Savings by an Innovative Network Graph Clustering Method
Care Process & Redesign
Technology
Singapore Healthcare Management Congress
Others
31 December 2021
To identify potential savings in medical supply procurement using network graph clustering. The method showcased a scalable approach for supply chain optimization and cost reduction in healthcare settings.
Year Submitted: 2021
Published Date: 31 December 2021
Tags: Technology, Care Process ＆ Redesign, Digital Health, Data Management, Data Analytics, Data Modelling, Operational Management, Financial Management, Supply Chain, Productivity, Cost Saving
About this Content
Aims
To identify potential savings in medical supply procurement using network graph clustering.
Background
Medical supply prices lacked standardization across institutions, leading to inefficiencies.
Methods
Leveraged PO data with graph clustering to compare similar/identical items and identify price variations.
Results
Identified annual potential savings of $3.1 million with 80% accuracy in graph clustering.
Conclusion
The method showcased a scalable approach for supply chain optimization and cost reduction in healthcare settings.
Lessons Learnt
Standardized processes and collaborative data sharing are essential for achieving efficiency.
Additional Information
Singapore Healthcare Management 2021 – 3rd Prize (Supply Chain Management Category).
Keywords
Supply Chain, Data Analytics, Cost Savings
Innovators' Details
Innovators' Details
Healthcare Cluster(s) | Others |
Organization(s) Involved | Agency of Logistics and Procurement Services |
Platform(s) | Singapore Healthcare Management Congress |
Healthcare Professional Group(s) | Healthcare Administration |
Applicable Specialty or Discipline | Healthcare Administrators |
Project Lead(s) | Ge Zhuo Ran |
Project Member(s) | Wang Min Hao |
Connect with this contributor!
Ge Zhuo Ran - singaporehealthcaremanagement@singhealth.com.sg
Project Attachment
C13_ALPS_Pte_Ltd_SHM_2021_Potential_Product_Savings_by_an_Innovative_Network_Graph.pdf