BioBright and Philips Collaborate on New AI to Improve the Patient and Clinician Experience
BioBright, a data and analytics company unlocking the potential of unstructured clinical and research information, announced an agreement with Royal Philips, a global leader in health technology, to develop information solutions that improve the patient and clinician experience across the healthcare continuum. This development collaboration follows the participation of BioBright in the Philips HealthWorks Startup Program in Cambridge, MA.
Today’s healthcare systems are focused on the quadruple aim: supporting population health in the communities they serve, reducing costs, and improving the patient and clinician experience. Successful systems continually strive to increase data usability, streamline workflows, and find new ways to capture and deliver important clinical insights in pursuit of these aims. By combining leading-edge Philips solutions and over a century of healthcare insights with BioBright’s secure voice and data processing technologies, clinicians will have the ability to quickly input and access the patient information they need to make informed care decisions.
“Providing access to data sources in a secure manner that respects patient privacy is still a challenge in healthcare today,” said Charles Fracchia, CEO and founder of BioBright. “Working with a market leader like Philips allows us to better understand these complexities and how we can naturally integrate ambient information into the clinical data environment. This lets us reduce administrative burdens and cognitive demands while putting the patient back at the center of healthcare.”
“Advances in technology have forced clinicians to spend more time on data entry, toggling between disparate systems and chasing down studies instead of focusing on the patient,” said Alberto Prado, Head of Philips HealthWorks. “Our Philips HealthWorks startup program allows us to collaborate with promising young companies like BioBright and find ways to break down data silos, integrating and processing large volumes of data from multiple sources regardless of vendor. We can then present this data back in a manner that makes sense for the clinician, allowing them to get back to basics and giving them more time for human interaction with their patients.”