Radiology practices using AI and NLP to boost MIPS payments


Positive or negative Medicare payment adjustments in 2019 will depend on performance to quality and other measures in 2017 under a new program called the Merit-based Incentive Payment System. Doing well on quality measures is important because they comprise 60 percent of a provider's total MIPS score – possibly 85 percent for certain specialties such as radiology.

CIOs must manage data for AI to deliver on data-driven healthcare


Data-driven healthcare is something of a buzzword, but it's an important one, a concept many hospitals are striving to bring to life to enhance care and trim costs. And it's dependent in a big way on healthcare CIOs and their abilities to work with data and artificial intelligence tools.

Microsoft, Humana ink 7-year strategic partnership to leverage cloud, AI and voice technologies


Insurance giant Humana and Microsoft announced a seven-year strategic partnership to use cloud and artificial intelligence technologies to build predictive solutions and intelligent automation to support Humana members and their care teams. Humana plans to use Microsoft's technology muscle, specifically its Azure cloud, Azure AI and Microsoft 365 collaboration technologies, as well as interoperability standards like Fast Healthcare Interoperability Resources (FHIR) to provide care teams with real-time access to information through a cloud platform, the companies said. Providers can use these technology tools to have a more holistic view of their patients to enable better preventive care, keep up with patients' medication schedules and refills and identify social barriers to health such as food insecurity, loneliness and social isolation, Humana said. Humana's goal is to leverage technology to improve members' health outcomes and make their healthcare experiences simpler to navigate. The partnership will address two core innovation areas for Humana.

Data Science and Machine Learning in Healthcare - Population Health M…


Population Health Management Report • Insight into the population served • Insights into the quality of care provided • Monitor, trend and benchmark critical measures • Create intervention profiles • Proactive measures to reduce length of stay • Identify conditions with most readmissions • Identify gaps in services • Identify areas for improvement and cost savings 11.

Rush using ML, analytics on images and unstructured data


Rush University Medical Center is adopting machine learning and analytics technologies from two companies to process patient information, including from imaging studies and other sources, with hopes of customizing patient treatment and delivering precision medicine. The Chicago-based academic medical center is using a combination of technology from Cloudera and MetiStream, which are working together on products that providers can use to improve patient outcomes. Cloudera offers a platform for machine learning and analytics optimized for the cloud, while MetiStream develops healthcare analytics solutions. MetiStream offers an interactive analytics platform for healthcare and life science industries built on Cloudera's machine learning platform. By combining machine learning and analytics from Cloudera Enterprise and Cloudera Data Science Workbench, MetiStream contends its Ember product can deliver insights across massive volumes of handwritten clinical notes as well as genomic data.