Nalashaa Healthcare Blogs
Payer organizations deal with data, day in and day out. It is not enough that payers fulfill their roles in the healthcare revenue ecosystem through claim management, credentialing, code entry,…
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From member enrollment, eligibility checks, and provider network management to billing and collection, healthcare payers are involved in handling and reporting sensitive healthcare data. The healthcare payer process is drawn out and cumbersome, with human errors resulting in penalties and loss of revenue, and must be automated…
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Today, data is everywhere and in many forms. The processing power to crunch huge amounts of data and get analytical insights is exponentially increasing. Cloud technologies are boosting the effective…
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Although at the beginning of the 21st century, many businesses had started to focus on data, the COVID–19 pandemic has forced organizations to develop and adapt to a must–have data-driven culture at all levels. Data was once a business byproduct for many organizations. Now, data itself is a key driver for…
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The health of your organization is directly dependent on the health of the members enrolled with it. A holistic view of your members gives you a complete status of their…
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The 21st Century Cures Act Final rule was introduced on May 1, 2020. It institutes crucial changes to the definition of Certified Electronic Health Record Technology (CEHRT). This means the…
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For a data-intensive industry like healthcare sector, blockchain is a reforming technology, which could revolutionize the way data is managed. The traditional way of a centralized database system is vulnerable…
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So far we have discussed the challenges and solutions of MU3 implementation and the process of the certification. To discuss further and to impart knowledge, Nalashaa HealthCare is organizing a…
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In the previous section, we have discussed the challenges while implementing MU3 and the how to solve them like an expert. Now that we have an understanding of the challenges…
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Researchers at University of Washington Tacoma have developed a machine-learning predictive analytics tool that forecasts with 82 percent accuracy the probability a patient will be readmitted within 30 days. In…
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