| Team Name | Medicine4Audit |
| Track | Health care & Life Sciences |
| Use Case |
Using text analytics to “cure” labor-intensive audits and lower the burden on care personnel
Challenge Hospitals face a significant administrative burden when reporting clinical outcomes to national quality registries like DICA (Dutch Institute for Clinical Auditing). These forms are often manually filled out by medical professionals, consuming valuable time and resources.
Solution Medicine4Audit proposes an LLM-based extraction pipeline that automates the retrieval of relevant data from clinical texts to populate DICA forms. By leveraging generative AI, the team aims to reduce manual input, improve data quality, and streamline the reporting process.
Impact
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| Technology | SAS Viya (ML, Intelligent Decisioning, Python (Integration)) |
| Region | EMEA |
| Team lead |
Eddy van der Heijde |
| Team members |
Eddy van der Heijde @evdheijde Nikki van Bommel @NikkivB Joran Roor @snljro Karen van der Sleen @kvds Judith Schepers - Vinke @JudithS Peter Schram @pjwschram Eline Witjes-Boksem @EWitjes Debby Vreeken @debby_vreeken Nikki van den Heuvel @NikkiH |
| Social media handles | *all team members' social media links here* |
| Is your team interested in participating in an interview? | Y |
| Optional: Expand on your technology expertise |
Jury Video:
Pitch Video:
This is a strong example of responsible, practical AI in action. Healthcare professionals still spend a significant part of their time on administrative work—sometimes up to a quarter of their workweek. The Medicine4Audit team set out to change that. Using SAS Decision Manager and a Large Language Model, they built an intelligent flow that automatically answers audit questions based on documents from the patient record and presents the results in a single, clear dashboard.
Less manual work means more time for patient care.
Read more in this article https://www.icthealth.nl/nieuws/hoe-generatieve-ai-de-administratieve-last-in-ziekenhuizen-verlicht
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