Tumor Zentrum Aargau is a large private competence centre for oncology, haematology and palliative care in Switzerland, with a long history of implementing digital solutions to improve cancer care. Given the complexity of cancer care, the centre sought a practical solution to understand how AI could be adapted to meet the diverse documentation requirements and workflow needs of multidisciplinary cancer teams.
Having previously collaborated with Lauri Sippola and Henri Viertolahti as an early adopter of the KAIKU ePROM Platform, Dr Razvan Popescu was immediately interested in piloting Gosta. What stood out early were its oncology-specific workflows and flexible customization, which enabled tailored use while delivering highly accurate consultation summaries. This led to rapid and widespread adoption across the centre.
The collaboration began with a detailed analysis of daily clinical workflows at Tumor Zentrum Aargau. The focus was twofold: understanding how consultations unfolded across the patient journey, and identifying where information became fragmented or time was lost. In parallel, the team explored how structured real-world data capture and outcomes monitoring could be integrated into routine oncology care without disrupting clinical flow.
Based on these insights, a tailored implementation of the Gosta AI Operating System for oncology was developed. Rather than introducing a separate tool, Gosta was embedded directly into existing workflows and continuously refined through feedback from multidisciplinary teams. What started with oncology consultations quickly expanded to palliative care and specialized nursing visits, ensuring consistent support across the entire patient journey.
As the system evolved, so did the experience for clinicians. With a single click, clinicians were able to access relevant patient background information, providing context needed for AI-supported documentation in real time. Clinical notes were automatically generated, validated, and seamlessly transferred into the electronic medical record system (EMR).
By integrating directly with existing systems, Gosta reduced documentation friction and enabled additional time savings beyond what standalone solutions typically achieved.
The impact of real-time AI support became evident quickly and was later confirmed by real-world data collected at the centre. During routine oncology consultations, Gosta generated structured, EMR-ready clinical notes in real time. Oncologists were able to review and finalize follow-up notes in a median time of under two minutes, cutting documentation time by more than two-thirds per patient.
Beyond documentation, the underlying models were trained to classify unstructured clinical content - such as consultation notes, patient discussions, and other forms of unstructured clinical documentation - into structured outcomes data. This enabled the automatic identification and classification of key clinical parameters, such as ECOG performance status and adverse effects of cancer treatments, effectively turning routine care into a source of structured, research-grade data.
"This technology is significantly reshaping our clinical workflows. The ability to instantly produce structured, accurate notes and automatically classify key clinical parameters frees oncologists to spend their time where it matters most - with their patients. In practice, this has already reduced documentation time by over two-thirds for each patient visit at our cancer center."
- Dr. Razvan Popescu, Medical Director at Tumor Zentrum Aargau.
