AI Against Healthcare Fragmentation
With hundreds of disconnected systems creating delays and errors, how does medical-context AI remove admin work and improve patient flow?
This video discusses the widespread challenge of system fragmentation in healthcare, exemplified by managing 800 separate systems in the south of Sweden, which causes extensive manual work and makes digital patient support impossible.
Niklas Sundler of Avenga explains how their collaboration with Corti addresses this technical debt by building purpose-built AI that is trained with medical context.
The current project focuses on automating the administrative flow for private healthcare insurance, encompassing multiple steps:
- Validation: Ensuring patients are booked with the correct resource (doctor, nurse, or physical therapist).
- Authorization: Reading documentation to secure approval for bigger activities like surgery.
- Billing: Suggesting correct items and codes for invoicing based on historical agreements.
The goal is to achieve substantial automation within a year, reducing the administrative burden and eliminating patient-facing problems like being booked to the wrong specialist or facing delays due to manual errors.
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