Companies all across the healthcare industry are looking to scale their AI abilities, often striking multi-year collaborations with Big Tech players.
This week, Quest Diagnostics made one of those deals. The diagnostics giant announced a new partnership with Google Cloud that aims to deliver new AI capabilities — including predictive population health analytics, customized physician results reporting and individualized patient engagement.
Under the collaboration, Quest will use Google Cloud’s data analytics and generative AI technologies — including Google Agentspace, a platform that uses generative AI to surface data and automate tasks.
One of the collaboration’s goals is to generate personalized health insights for patients.
“We are still exploring potential applications for generative AI and the implications this new relationship might have for patients. One potential use case involves reminding a patient to schedule a follow-up or annual appointment if data shows they are due but have not yet done so,” said Mark Clare, Quest’s chief data officer.
The collaboration also seeks to give clinicians ready access to comprehensive laboratory data, he noted.
Laboratory testing and results can provide clinicians with important insights into a patient’s health, helping to guide the treatment plan, Clare pointed out.
“A complete picture of a patient’s lab data helps physicians provide the best care possible. Trends over time and correlations between different lab results help physicians form a complete picture of their patient’s health,” he declared.
One of the key metrics Quest will use to gauge the success of its collaboration with Google Cloud will be the degree to which a typical business user can obtain a sophisticated report generated through a natural-language prompt, Clare stated.
He said this will reduce the time analysts spend creating ad-hoc reports, giving them more to dedicate to “real data science efforts.”
Google Cloud’s generative AI has many applications in the diagnostics world, pointed out Shweta Maniar, the company’s global director of healthcare and life sciences.
“It can process, analyze and reduce silos in the enormous and complex datasets generated in modern healthcare — from genomic information to medical images — far more efficiently than humans, which can help providers understand what kinds of additional diagnostics might be required. This leads to faster and more accurate diagnoses, enabling earlier interventions and better patient outcomes,” she explained.
AI can also flag subtle patterns and anomalies in data that might evade the human eye, potentially uncovering new insights into disease and predicting individual risk, Maniar said.
She also highlighted AI’s role in personalizing medicine, saying that the technology can help tailor treatments and preventive strategies to each patient based on their unique characteristics and data.
Photo: Galeanu Mihai, Getty Images
