Application of Semantic Textual Similarity in Contract Review
Care Process & Redesign
Technology
Singapore Healthcare Management Congress
Others
31 December 2021
To improve the Master Agreement review process using AI and natural language processing (NLP). AI-based review systems improve operational efficiency and reduce risks in supply chain management.
Year Submitted: 2021
Published Date: 31 December 2021
Tags: Technology, Care Process ＆ Redesign, Digital Health, Data Management, Data Analytics, Digitalisation, Automation, Artificial Intelligence, Quality Improvement, Job Effectiveness, Operational Management, Legal/Contract Management
About this Content
Aims
To improve the Master Agreement review process using AI and natural language processing (NLP).
Background
Manual reviews of Master Agreements are time-intensive and prone to errors.
Methods
Developed NLP techniques for clause comparison using semantic similarity models.
Results
Reduced review time from hours to 30 minutes; identified 2 significant discrepancies in 22 contracts.
Conclusion
AI-based review systems improve operational efficiency and reduce risks in supply chain management.
Lessons Learnt
NLP significantly enhances the speed and accuracy of document review processes.
Additional Information
SHM 2021 Shortlisted Project
Keywords
Natural Language Processing, Contract Review
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
C_563_ALPS_SHM_2021_Application_of_Semantic_Textual_Similarity_in_Contract_Review.pdf