Decision Support

Data from the accelerometers allowed researchers to correctly rank the mortality risk using 30-40 percent more accuracy than when using data about smoking status or a patient's stroke or cancer history.

Partnering with two firms focused on lab analytics and building a High-Value Care program, the health system within 15 months reduced unnecessary potassium tests by 63%, unnecessary magnesium tests by 40%, and unnecessary lipid panels by 40%.

Real-world evidence drawn from unstructured clinical notes was more accurate in algorithmic prediction of coronary artery disease than structured data, a new study in JAMIA shows.

Genomic medicine researchers at the laboratory have been using artificial intelligence, developed as part of Microsoft's Project Hanover, to help manage the vast amount of research data needed to power its precision oncology initiatives.

The leading-edge technology could provide vastly faster power and processing speeds, and enable fundamentally different algorithmic search and data homogenization strategies.

Experienced professionals in the area of nursing informatics from Singapore recently shared their lessons learnt at the Hillrom Dialogue Series.

The edge computing technology's neural network algorithms can help drive workflow efficiency, detect gaps in care and deliver real-time intelligent notifications to staff, the AI developers say.

More than 30% of the health system’s employees have signed up for a precision medicine program that helps get predictive genomics data straight to frontline caregivers.

Its care innovations have helped nurses spend 3,000 more hours at the bedside – leading to a 58% improvement in care efficiency and a 19% reduction in HAIs.

The technology examines vital signs and other biomarkers to predict the likelihood of infection up to 48 hours ahead of clinical suspicion.