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Ambient AI is helping to restore how clinicians connect with patients at the point of care and it's also reducing their after-hours documentation burden, according to Julie Frey, Wolters Kluwer VP of provider product.

More than half of nurses say they experience burnout most days, a new survey shows, with 61% planning to change jobs or departments, seek a hybrid position, work as travelers or make other career changes.

Despite years of investment, many hospitals remain digitally fragmented. A command centre approach offers a practical way forward, integrating data and decision-making in real time to enhance operational and surgical performance – and patient care.

Before implementing AI tools, leaders must ensure data flows freely between their EHR and practice management systems, and that they know how the tool will fit into existing procedures, says Matt Murren, CEO of True North ITG.

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.

When health systems upgrade their IT infrastructure, they should also train staff to use AI and other new technologies, says Dr. Guido Giunti, chief data officer at Dublin, Ireland's St James's Hospital.

The technology it's using to reach patients has not only improved clinical outcomes but is also providing tangible financial benefits, while ensuring patients can easily access the care they need.

Ever since financial institutions have significantly increased their security preparedness, bad actors have turned to healthcare organizations, seeing them as more vulnerable – and lucrative – targets, says Dr. Eric Liederman, CEO of CyberSolutionsMD.

The artificial intelligence agent texts patients to schedule their follow-ups – presenting options for provider availability, booking their choice and then confirming appointment details.

The radiologist shortage and increasing imaging demand are two intertwined challenges that can benefit from large language models. Penn Medicine is showing how.