Healthcare Analytics: Analytics and machine learning - Analytics Magazine

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The U.S. healthcare system is well on its way in the transition to value-based payment models that reward providers for delivering quality outcomes and keeping patients healthy. In fact, as of March 2016, the Department of Health and Human Services reported that an estimated 30 percent of Medicare payments were already tied to these new alternative payment systems. Value-based programs are replacing traditional fee-for-service models that pay providers based on the number of services delivered. The newer models are designed to encourage care that is well-coordinated, cost-effective and lead to quality patient outcomes. In order to achieve new payment objectives, providers are seeking opportunities to engage patients in their own care, improve patient satisfaction and keep patients healthier.


Five big data trends in healthcare

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Healthcare is experiencing a major data transformation through the use of advanced analytics and big data technologies. This transformation is a product of both the move toward evidence-based medicine and changes in payment models. In 2017, the healthcare industry will see the following five big data trends as part of this data transformation. Modern healthcare systems are promoting the meaningful use of health information technology to improve patient outcomes, reduce healthcare costs, and provide support for reformed payment structures. Insurers are shifting from a fee-for-service model to value-based data-driven payments that reward high-quality cost-effective patient care and demonstrate the meaningful use of electronic health records.


How HIEs and AI can work in tandem to boost interoperability ROI

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"We spent all those years adopting EHRs, and now we're wanting to get the most out of them. Now we have the digital data, so it should be more liquid and in control of patients and put to use in the care process, even if I go to multiple sites for my care." As ONC and CMS prepare to digest the voluminous public comment on their proposed interoperability rules, especially the emphasis on exchange specs such as FHIR and open APIs, he sees the future only getting brighter for these types of advances as data flows more freely. "We're in the interoperability business, and we like having data being more available and more liquid, and systems being more open to getting data out of them," Woodlock said. "A lot of customers are starting to embark on their journey with with FHIR, and they're really bullish on this as well: having a standards-based API way to interact with medical record medical record data," he added.


AI, wearables, interoperability new products at HIMSS19

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Health IT vendors galore have been introducing new products this week at HIMSS19. Here is another selection of some of the announcements. AMAX, a global artificial intelligence, deep learning and enterprise IT technology vendor, has launched its AI/Deep Learning Compute Cluster systems and Virtual Desktop Infrastructure platforms for the healthcare industry. The company's AI/Deep-Learning Compute Cluster systems for healthcare are optimized for research, development and large-scale deployments in data centers. Systems address the increasing demand for fully integrated high-performance compute and GPU accelerated compute as well as high-performance storage specific to healthcare applications that are based on AI and deep learning, the company explained.