Analytics

Predict readmissions, detecting early cancer among the results of several case studies detailed at the Machine Learning & AI event.

With predictive and cognitive technologies advancing, reaching patients outside of care settings is only going to get more important.

America’s former CTO says healthcare can learn from creative approaches in both the public and private sectors.

Building on the success of its EMR Adoption Model, otherwise known as EMRAM, HIMSS Analytics is introducing new models for infrastructure and supply chain and expanding its Digital Imaging Adoption Model. Much like EMRAM was a guidepost hospitals use when gearing up for an EHR go-live, the new models are designed to help users understand how to optimize infrastructure, supply chain and enterprise imaging. “Early infrastructure models were built around EHRs and on-site data centers but as cloud, telehealth and personalized medicine continue advancing, the infrastructure demands on a hospital have changed,” said Blain Newton, Executive Vice President of HIMSS Analytics. “Being able to understand how to adapt to that from disparate locations and access patient generated data is a very different game than when all you had to do was setup a server farm.” To that end, HIMSS Analytics built the Infrastructure Maturity Model, INFRAM, in collaboration with Cisco. Likewise, HIMSS Analytics partnered with Scan Health to create the H-SIMM. “When you think of supply chain, the real value is integration with clinical systems to reduce variability and cost of care,” Newton said. “If you have that integration, hospitals can achieve all kinds of financial benefits immediately from reducing waste and variability and the long-term play is very significant impact on clinical effectiveness.” Whereas INFRAM and H-SIMM are new models, HIMSS Analytics is working to bring its Digital Imaging Adoption Model (DIAM) to the United States and expand it to include Enterprise Imaging. “With the advancement of imaging technology and infrastructure to support large-scale data storage and transport, and AI to automate interpretation of images, we’re seeing an explosion in this space,” Newton said. Right now, leading systems such as the Mayo Clinic are leveraging heavy AI-enabled image reading and analysis but the question has become whether or not rural facilities can use technology, infrastructure and access to information in similar ways. “You have to be setup from a technology and workflow perspective,” Newton said. The new maturity models will be available in the summer of 2018. HIMSS Analytics is in Booth 1338. .jumbotron{ background-image: url("http://www.himss.org/sites/himssorg/files/u351641/HIMSS-sign5-jumbotron.jpg"); background-size: cover; color: white; } .jumbotron h2{ color: white; } HIMSS18 Preview An inside look at the innovation, education, technology, networking and key events at the HIMSS18 global conference in Las Vegas.

LOGIQ E10 offers 48 times the data throughput and 10 times the processing power of previous systems, officials say.

Over the course of year, the health system has cut hospital length of stay and saved $62 million with help from the company's remote care platform.

Its new risk score harnesses clinically-validated information from non-clinical settings, enabling health systems to better manage their 30-day readmission risks.

Actionable insights and intelligent health care experiences lead to personalized care and improved operations for providers.

New Touchstone tool uses artificial intelligence and machine learning to pinpoint opportunities to improve from claims, CMS, EHRs, genomics and other datasets to make prioritized recommendations hospitals can use to improve.

The company will bring digital health tools for connectivity and applied intelligence to HIMSS18.