Quality HealthCare and PolyU School of Accounting and Finance Launch Strategic RPA Internship to Drive Healthcare Innovation and Develop Future Talent
- Written by Media Outreach
HONG KONG SAR - Media OutReach Newswire - 30 October 2025 - Quality HealthCare Medical Services (QHMS), a long-established healthcare provider in Hong Kong, has partnered with School of Accounting and Finance (AF) of The Hong Kong Polytechnic University (PolyU) to launch a strategic internship programme focused on Robotic Process Automation (RPA). The initiative supports internal workflow improvement across QHMS operations while giving undergraduate students real-world experience in digital process transformation. The collaboration reflects QHMS's commitment to fostering future talent and exploring technologies that enhance operational efficiency in healthcare. 
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Quality HealthCare and PolyU School of Accounting and Finance Launch Strategic RPA Internship to Drive Healthcare Innovation and Develop Future Talent
Robotic Process Automation (RPA) uses software robots to automate repetitive, rule-based digital tasks such as data entry, file handling, and system navigation — reducing manual workload and improving consistency across administrative processes. In this internship, six PolyU AF students are working across five QHMS departments to develop and implement nine RPA use cases, with additional projects in reserve. These automations are expected to contribute to a combined monthly saving of approximately 1,600 man-hours1, providing measurable improvements in internal productivity. Key areas of focus of the internship include: - Clinic report digitisation – Automating the generation and handling of internal reports across 20 clinics (approx. 1,320 hours/month1).
- Billing query management – Streamlining billing-related administrative queries (approx. 120 hours/month1).
- Amendment form handling – Automating the processing of 100+ scanned amendment forms from clinics to the billing system.
- Term 1: Initial RPA bots and interim reports
- Term 2: Finalised bots, process documentation, and summary reports
1 The estimated man-hour savings are computed based on internal time-tracking data and average monthly volumes recorded across relevant teams (Q1-2 2025).

