Compliance Review enabled with Data Analytics (CReDA)
Technology
National Healthcare Innovation and Productivity Medals
National University Health System
31 December 2024
Automate compliance review of vendor performance through data analytics, reducing manual effort and improving accuracy. CReDA has been successfully scaled across NUHS, demonstrating the benefits of automation.
Year Submitted: 2024
Published Date: 31 December 2024
Tags: Technology, Digitalisation, Automation, Robotics Process Automation
About this Content
Aims
Automate compliance review of vendor performance through data analytics, reducing manual effort and improving accuracy.
Background
Healthcare organizations rely on third-party vendors for labor-intensive functions. Manual compliance review processes are time-consuming and prone to errors, affecting vendor management efficiency.
Methods
CReDA was developed using VBA in Excel to automate compliance reviews, ensuring accuracy, scalability, and ease of adoption by end-users.
Results
Review time reduced by over 90%, saving 2,960 man-hours annually. The system flags operational anomalies, enabling proactive investigations and data-driven decisions.
Conclusion
CReDA has been successfully scaled across NUHS, demonstrating the benefits of automation. Future applications include broader adoption in compliance-related functions.
Lessons Learnt
Automation significantly improves compliance efficiency and accuracy. Scalability allows expansion into areas like patient billing, IT security, and financial planning.
Keywords
Manpower Shortage, Compliance Review, Vendor-Reported KPI, Data Analytics Tool, Accuracy, Scalability, Repetitive Tasks, CReDA Tools
Innovators' Details
Innovators' Details
Healthcare Cluster(s) | National University Health System |
Organization(s) Involved | Not Applicable |
Platform(s) | National Healthcare Innovation and Productivity Medals |
Healthcare Professional Group(s) | Healthcare Administration |
Applicable Specialty or Discipline | Healthcare Administrators |
Project Lead(s) | Daniel Tan Kwan Wei |
Project Member(s) |
Connect with this contributor!
Soo Jie Yi - jie_yi_soo@nuhs.edu.sg
Project Attachment
429_NUHS_NHIP_2024_Compliance_Review_enabled_with_Data_Analytics_CReDA.pdf