Problem statement: The current cancer diagnostic pathway is a manual, lengthy, multi-hand-off process with many bottlenecks and data silos. This causes delays to definitive diagnosis and staging that severely impact patient treatment and survivorship outcomes.
How do we create an “intelligent system”, ie humans supported by AI / digital technologies, working together to improve the cancer care pathway by addressing system bottlenecks.
How is GE Healthcare solving this?
Healthcare globally is facing its biggest challenges ever. Rising demand, particularly in this COVID world, is stretching already scarce resources to breaking point. Our strategy aims to start to address those challenges, by using enabling digital technologies and AI used in other industries (Retail, Aviation), to support a move away from traditional (one-size fits all) models of care to one that is more precise and tailored to the specific consumer ie personalised care.
AI has the potential to aid decision making and automate operational processes to improve efficiency, reduce costs and ultimately improve health outcomes. Our digital technology and products (EDISON) orchestrate AI apps, such as “GEHC Smart Scheduling” across operational processes to automate our GEHC Rapid Diagnostic Centre (RDC) model. We want to adopt an “Innovation ecosystem”, enterprise-level approach by bringing together our healthcare & technology partners with innovative AI start-ups to trial the use of operational AI apps in real world healthcare settings.
We are looking for EMEA start-ups / SMEs who can work with us to bring additional beneficial capability around our EDISON offerings. Problem areas of interest could include, but are not limited to:
· Risk stratification and prioritisation
· Process automation ie referral management, scheduling, booking, batching / carve out, resource allocation etc
· Proven, scalable data interoperability and consolidation methods toolkit (national standards adherence) and compliance with GDPR which can integrate with the EdisonTM Platform and create a cloud-based set of meta-data to enable evidence-based benchmarking between different sites, regions, or countries (cancer focus)
· Clinical Decision Support solutions that can be applied within the cancer pathway to suggest diagnostic options based on clinical guidelines and /or can auto-complete and/or auto-triage referrals to diagnostic services
· Proven application of NLP tools/ apps that can improve and automate referrer experience; data quality, patient choices and preferences; completion of pre- acquisition patient safety advice and criteria
· Auto-scheduling tools based on optimised booking rules to reduce costs, automate process, reduce manual intervention and optimise diary utilisation and available capacity
· Conversational AI platforms and chatbot functionality to improve collaboration and improve adherence to operational protocols by the healthcare professional
· Predictive / prescriptive apps covering novel & innovative use cases in the Oncology and Radiology domain with a unique, differentiated and market leading value proposition
Contact Thomas Bastien to learn more about the programme and solutions that we are looking for.
