Decision Support
A decade-long study just published in JAMA finds a wide variance in the safety performance of operational EHR systems, especially when it comes to reducing adverse drug events.
John Halamka describes how clinicians at Mayo are benefiting from machine learning-powered approaches to imaging, predictive analytics and other types of decision support – and using machine learning to mine historical data for new treatments.
In this special report, three IT experts describe technologies and strategies to boost quality improvement efforts and put patient safety at the center of the equation.
A drop in blood pressure can be hard to predict using standard clinical measurements such as heart rate or cardiac output – but experts say a new AI tool could give clinicians a valuable 15-minute lead time.
Rapid opioid withdrawal can present severe symptoms in patients, but effective drawing down of dosage often presents a challenge for clinicians.
By using real-world patient information, the agency hopes to research population health trends and medication efficacy.
The concept for the New Zealand Algorithm Hub was initially developed through the Precision Driven Health research partnership between Orion Health and partners.
Billed by the software giant as its first industry-specific cloud product, the newly-launched platform is also aimed at enhancing patient engagement, improving provider communication and boosting analytics.
POCUS technology from Butterfly Network expands screening capabilities, offering "an immediate and clear picture of what’s happening in a patient’s lungs."
The New York-based company claims its platform can be used to more accurately monitor efficacy of immunotherapy.