Automating Oslo: how advanced content management is paving the way for AI

Expanding the role of advanced medical content in clinical outcome improvement is at the heart of a cooperation between Oslo University Hospital and Olympus, which will also build the foundation for the development of AI in digital health solutions.
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Credit: Olympus

Timely access to critical information is more important than ever as enhanced collaboration among different specialties becomes increasingly crucial to delivering optimised patient care. At Oslo University Hospital (OUH), an advanced mechanism for labelling and editing recorded procedures has been developed in partnership with Olympus to support the standardisation of procedures and enhance teaching workflows for surgeons.

COOPERATION BENEFITS DIGITAL HEALTH

In addition to supporting teaching workflows, the Vaultstream Medical Content Management System gives healthcare teams real-time access to clear visual information and collaborative insights across the wider hospital environment.

There are 24 Olympus nCare medical recorders integrated into the system in 22 operating rooms and two surgical ENT rooms at OUH. Video footage can be adjusted before submission. The AutoClip feature allows users to edit procedure clips for length and focus, while AutoLabel enables standardised labelling, helping to make data readily available for reference and analysis.

Dag Tidemann Førland, chief surgeon at OUH, says: “We like the standardisation of the procedure, and that bookmarks can be made stepwise. Residents can easily bookmark specific parts and later compare these steps with previous procedures, for a shorter and rapid learning curve and to become more confident – in the end, to ensure the safety of the patient, which is the main goal.”

PAVING THE WAY FOR AI

Projects such as this OUH/Olympus partnership are helping to transform operating rooms into valuable data sources, which in turn can be used in the development of AI solutions without requiring further editing or labelling.

This is a significant benefit. McKinsey recently identified data labelling as one of the most challenging aspects of AI adoption for many industries, including healthcare. Removing this expensive and time-consuming barrier with a simple, automated tool will help to build a foundation for future AI solutions that improve patient safety, clinical outcomes and the efficiency of surgical procedures.

Åse Schiefloe, project leader at OUH, says: “I think we have finally found a system that is going to match our needs. We have been searching for a good system for our surgeons for quite a long time.”

OUH will now be a Reference Centre for Olympus. For further information, visit Olympus Europa.

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