The offerings centre around consolidating fractured data, increasing the efficacy and value of care.
New AI tools will be launched across Microsoft Fabric and Azure AI to help health organisations leverage data to provide better health outcomes.
According to a Deloitte report, 97% of data generated by hospitals is unused due to the siloed nature of data storing systems.
Microsoft Fabric, a data and analytics platform will help unify separated data by combining data from a variety of sources, including electronic health records, images, lab systems, medical devices and claims systems so that the data is standardised and available in a central location.
Fabric has been trialled in healthcare settings at Northwestern Medicine, Arthur Health and Singhealth in the US.
Doug King, Chief Information officer at Northwestern Medicine, said unifying disparate data would help health organisations improve care and see more patients.
“Data is king now within health care, and that goes from everything from understanding what’s happening in the OR, to how many patients are coming in? How many patients are leaving the house or the hospital? And then how can you get them in faster?” he told CNN.
“The current state of technology and Microsoft Fabric and Azure and generative AI, all of that, it’s going to change the way we live. And it’s going to change the way we take care of patients. And it’s probably one of the best shots that we have to solve some of the biggest problems we have within health care.”
Mr King said Northwestern was considering using the technology to manage patient flow and staffing, as well as integrating wider population health data into its systems, adding that capitalising on the technology’s capabilities could be a “game changer” if done well.
A new generative AI health chatbot will be launched across Microsoft’s Azure AI. The chatbot can extract information from the organisation’s internal data as well as public external sources, such as the Food and Drug Administration and the National Institutes of Health.
Linishya Vaz, principal product manager at Microsoft Health and Life Sciences explained that the chatbot could be used to help staff more effectively treat patients. For example, staff can ask the chatbot clarifying questions regarding a patient’s symptoms and medical terms, and questions regarding internal processes and protocols.
“What’s also really important is that we built in guardrails and safeguards into this process,” Vaz told reporters at a press briefing.
“There’s a way to verify this information, make sure the customer can do an audit of the answers to see that they are credible.”
Microsoft also announced three new models within Azure AI Health insights, including patient timeline, clinical report simplification and radiology insights.
Patient timeline will provide clinicians will a chronological overview of a patient’s medical history; clinical report simplification will be able to simplify medical reports so that a layperson can understand them; and radiology insights will flag errors and inconsistencies that appear across different imaging reports and offer follow up recommendations.
Microsoft also unveiled Text Analytics for Health, which can label and sort through medical information from a variety of unstructured data sources such as clinical documents and notes.