Technology
Revenue Cycle of the Future…something we have heard on several occasions. But what does it actually look like? In a recent article, HealthLeaders highlights a roundtable discussion sponsored by our friends at Waystar, bringing together a group of leaders in revenue cycle management to gather their thoughts on what they believe is important for the revenue cycle of the future.
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Rachel Woolley, global director of Financial Crime at Fenergo, tells FinTech Futures that penalties against financial institutions have come “fast and furious” over the past few years.
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Alpha Health recently released results of a national survey designed to examine and assess the impact of COVID-19 on revenue cycle operations at health systems and hospitals across the U.S. The survey was fielded between May 19, 2020 and June 22, 2020 among 587 chief financial officers and revenue cycle leaders at hospitals and health systems across the United States. The survey has a confidence level of 95 percent with a margin of error of plus or minus 5 percent.
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In a summary of Mercator Advisory Group’s new Insight Summary Report, 2020 Small Business PaymentsInsights, COVID-19 and B2B Payments & Cards – The Result of the Pandemic, PaymentsJournal.com summarizes their findings.
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By now, many of you have heard of the arguments between utilize GPU vs CPU. towardsdatascience.com provides a simple explanation on the reasoning behind the need for GPUs for machine learning:
GPUs are optimized for training artificial intelligence and deep learning models as they can process multiple computations simultaneously.
They have a large number of cores, which allows for better computation of multiple parallel processes. Additionally, computations in deep learning need to handle huge amounts of data — this makes a GPU’s memory bandwidth most suitable.
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Technology just keeps getting better and better, right? Not always. A recent survey of health IT leaders reveals that they are most often unhappy with their electronic health record (EHR) packages. Healthcare IT Today reports on a survey 108 healthcare leaders about their use of analytics platforms. It starts out with some fairly positive data:
90% of these organizations reported using the analytics in their EHRs.
Check writers and depositors have become accustomed to a next day or two day check clearing process for the majority of items. But when an extended clearing process does happen, i.e. 2-3 days, it becomes a real inconvenience, especially for millennials accustomed to instant digital payments, or for those folks who still get payroll checks. There are many other examples.
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The New Yorker Magazine takes a close look (via Clifford Marks, an emergency-medicine resident at the Icahn School of Medicine at Mount Sinai) at how primary care practices and physicians are taking it on the chin due to the effects of the Coronavirus pandemic.
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Pymnts.com explores the various hurdles banks face when taking that big — and increasingly necessary — step. They note that migrating to the cloud is a vital tool traditional financial institutions (FIs’) will need in order to compete with digital-native FinTechs.
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To the layman, much of the language in the AI space can be mystifying, particularly in deep learning. Take for example one of the core elements; the node. A deep learning node is “a computational unit that has one or more weighted input connections, a transfer function that combines the inputs in some way, and an output connection. Nodes are then organized into layers to comprise a network.”
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