Doncaster and Bassetlaw Teaching Hospitals partners with Annalise.ai to enhance diagnostic services

This collaboration focuses on improving the efficiency of radiology services via the deployment of AI-enabled decision support solutions for chest X-ray and non-contrast CT brain scans, ultimately aiming to enhance patient care and outcomes. The initiative represents a significant advancement in radiology services within the region.

Doncaster and Bassetlaw Teaching Hospitals serves a population of over 440,000 in South Yorkshire, North Nottinghamshire, and neighbouring areas. With three primary hospital sites and a range of ancillary services, the Trust is one of only a small number of teaching hospitals in Yorkshire, and employs around 7,000 health professionals.

Annalise.ai offers CE cleared, comprehensive AI solutions capable of detecting up to 124 findings on chest radiographs and up to 130 findings on non-contrast head CT scans.

These solutions will assist clinicians at DBTH by flagging, highlighting, and prioritising cases based on different urgency levels. Configurable worklist priority categories, including 'critical,' 'high,' 'low,' 'unremarkable,' or 'no abnormality detected,' will enable clinicians to efficiently triage cases.

Sara Elliott, Head of Medical Imaging said, “The integration of Annalise.ai's solutions is expected to streamline turnaround times for critical cases by assigning priority groups. Potentially and depending on the results of the pilot abnormal imaging will be sent to teleradiology for analysis, while normal cases will be reviewed in-house, resulting in significant cost savings. This strategic partnership underscores our commitment to leveraging cutting-edge technology to enhance care for those we serve.”

"We are excited to embark on this transformative journey with NHS Doncaster," said Dimitry Tran, Co-founder and Chief Commercial Officer at Annalise.ai. "This partnership reflects our shared dedication to delivering high-quality, cost-effective healthcare services. By harnessing the power of AI and collaborative innovation, we aim to revolutionise radiology practices and elevate patient outcomes."