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Clinical decision support technology has enabled automatic inclusion of risk results in the health system's reports. Among many other improvements, the ability to stratify patients earlier and more accurately allows staff to provide additional care before cancer is detected.

The 13-hospital network's CDS system also maintained stable patient experience scores – and data validated that cost reduction was achieved without compromising quality of care.

In a letter to the FDA, members of Congress cite confusion over providers' deployment of clinical decision support software that is exempt from medical device regulations and call for clarity from its Center for Devices and Radiological Health.

From EHR optimization to AI-enabled CDS, big advancements are happening with biomedical informatics. Chris Harle, researcher at Regenstrief Institute and professor at Indiana University, discusses data science, provider experience, patient safety and more.

"AI can fundamentally change the physician experience with an EHR by making it an intelligent partner for the clinician," says Paul Brient, chief product officer of athenahealth.

Despite broad concern by health IT developers and owners, some deadlines have been pushed out in HTI-1, the new federal rule governing certification, AI transparency and other standards, while those for decision support algorithms have not.

When patients feel welcomed, treatment adherence improves.

Give clinicians and care teams real-time, accurate information and alerts.

Detect critical illness more quickly and reduce waiting time for care.

Real-world examples from Premier Inc. showcase how machine learning and natural language processing are helping providers use structured and unstructured data to drive more efficient operations, innovate care delivery and improve patient experience.