Healthcare
AI-Powered Patient Feedback Analysis
Leiden University Medical Center (LUMC)
Patient comments contain insights that traditional surveys often leave hidden. AI-PREM helps LUMC organize open-ended feedback by topic and sentiment, giving care teams a clear view of recurring experiences and the underlying comments. The approach grew from one pilot to eight care pathways, making the patient voice easier to act on at scale.
Impact at a glance
- 8
- care pathways reachedThe wider AI-PREM implementation scaled from one pilot care pathway to eight.
- 4
- enterprise systems integratedCastor, BeterMeter, SQL Server, and Power BI were connected to the AI workflow.
The engagement
AI-PREM turns open patient responses into practical insight for quality-improvement teams. Feedback moves from established collection systems into a consistent analysis and reporting process, where recurring topics and sentiment become visible without losing access to the original comments. Care teams can explore patterns, understand the experiences behind them, and bring stronger evidence into improvement discussions. Expansion from one pilot to eight care pathways demonstrates an approach that can be adopted across clinical services while remaining connected to existing hospital reporting.