Analytics

Anne Snowdon, chief scientific research officer at HIMSS, explains that interoperability is fundamental to enabling data-informed patient care decisions and is required for the use of AI and advanced analytics tools.

Ricardo Jorge Constantino, head of Clinical Innovation Europe at NTT DATA, describes innovation in clinical trials and measures to drive rapid adoption of insights from these trials into clinical practice.

The remote patient monitoring project aims to integrate platforms to equip clinicians with advanced decision support for hospitalized patients in both critical and non-critical care, and develop new AI-enabled predictive analytics.

The American College of Radiology's ARCH-AI initiative is billed as the first-ever such framework, designed to help imaging providers deploy artificial intelligence more safely.

It will identify new risks, such as alcohol or drug misuse, not captured in existing data.

The AWS Imagine Grant is open to registered nonprofit organizations using cloud technology to advance their research across the spectrum of childhood diseases – from heart conditions to genetic disorders.

As clinicians face increased patient volume and a deluge of data, AI technology can help reduce their documentation burden and even support decision-making — with some guidelines in place.

The sophisticated program employing patient monitoring, patient tracking and reporting technologies also has enhanced patient follow-up and engagement and yielded a big win on overall healthcare delivery.

ZeOmega uses AI to identify vulnerable patient populations and suggest ways to improve their health outcomes. Pravin Pant, the company's VP of advanced analytics, and Michael Gould, its associate VP of interoperability strategy, explain.  

Connected care through the Memorial Healthcare System's mobile application gets patients engaged and taking more control of their care, and by feeding data to EHRs, can also help to save nurses time, says Jesus Diaz, director of nursing informatics.