US-based health system Imperial Valley Healthcare District has partnered with healthcare AI platform Notable to streamline and personalise the registration and patient intake process for its roughly 75,000 annual appointments.
Notable's AI platform and Intelligent Agents are designed to automate registration before visits, appointment reminders and clinical intake forms.
They will replace Imperial Valley's current process, which is reportedly often characterised by cumbersome paperwork and long wait times.
The partnership seeks to eliminate the inefficiencies associated with manual administrative tasks, enabling healthcare staff to provide more tailored support and address complex patient inquiries.
Through this, Notable and Imperial Valley aim to ensure that patients face less delays and offer a more streamlined appointment process without the need for additional staff.
Notable chief medical officer Aaron Neinstein said: “There are over two million open administrative roles across the US healthcare system.
“Organisations can’t fill roles fast enough, and patients feel that burden whenever they are greeted with a clipboard instead of a smile or sit in a waiting room well past their appointment time.
"By digitising, personalising, and automating administrative tasks, Notable’s Platform and AI-powered Agents free up staff and clinicians to focus on what’s most important: patient care.”
Based in California, Notable's solutions are designed to offer a secure, comprehensive AI platform that automates manual tasks, enhancing productivity and workforce efficiency while reducing operational expenses.
Earlier this year, Notable introduced the Builders Partner Program, inviting developers, software companies and consultancies to utilise its low-code Flow Builder interface.
This initiative aims to implement custom AI agents to further optimise healthcare systems, as part of Notable's efforts to innovate in the area of healthcare technology.
These AI agents can autonomously perform routine tasks such as claim approvals, patient scheduling and revenue cycle automation, which have historically been carried out manually.
