OrboNation Blog
It’s a safe bet to say that making a … safe bet during an unprecedented pandemic is not the easiest thing in the world. All the same, Becker’s Health IT got 20 healthcare executives and leaders to commit to posterity one health IT industry prediction for the next five years, and the answers are interesting,…
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Predicting an economic recovery in today’s COVID-19 environment is far more complex than reading traditional individual economic indicators. As seen by the recent run in the stock market, there are certain market components somewhat disassociated from traditional indicators, i.e. unemployment rate, GDP growth, etc.
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In a little over a month, OrboGraph will host the ORBOIMPACT Virtual Conference: AI Innovation for Check Payments, Check Fraud, and Healthcare Remittance Automation.
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In a little over a month, OrboGraph will be hosting it’s first virtual conference since 2014: ORBOIMPACT Virtual Conference: AI Innovation for Check Payments, Check Fraud, and Healthcare Remittance Automation.
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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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A common misconception, especially in revenue cycle management (RCM), is that automating processes by integrating technologies like Artificial Intelligence and Machine Learning technologies will replace employees and eliminate jobs. This perception can be traced all the way back to when machines replaced labor in many manufacturing jobs like the automotive industry and is continually being fueled by the media with the story lines such as AI-powered trucks will replace truck drivers.
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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.