Welcome!

Machine Learning Authors: Corey Roth, Yeshim Deniz, Pat Romanski, Elizabeth White, Liz McMillan

News Feed Item

Argus Announces Next Generation Pharmacy Claims Processing Solution

Argus delivers RxNova™; flexible, configurable, extensible, auditable, reliable, scalable and intuitively usable

KANSAS CITY, Mo., Nov. 28, 2012 /PRNewswire/ -- Argus Health Systems, Inc., a leading transparent pharmacy benefits administrator, today announced its next-generation claims processing engine, RxNova™. 

From 2011 through 2020, the Centers for Medicare and Medicaid Services projects an 86% increase in prescription drug spending. Also, as predicted by the Affordable Care Act, the number of insured Americans could rise by as many as 33 million over the next decade. This changing market, along with new Health Care Reform regulations and broader coverage requirements, means that health plans must have increasingly flexible tools with comprehensive capabilities to support increasingly complex, customized benefit designs. In this time of rapid market change, health plans must accelerate their product development and personalize benefit designs to satisfy today's members and tomorrow's prospective members. Successful pharmacy benefit administration and management companies must be prepared with advanced technology, significant flexibility and rapid time-to-market solutions to enable their customers to adapt to changing member demographics, external demands, and expected outcomes.

RxNova™ is a technology- and business-driven initiative that began when the company made the strategic decision to invest in our already reliable, functionally-rich claims processing system. This investment to enhance the user experience was a multi-year project to transform the underlying architecture, business design and rules structure of our claims processing technology to create a best-in-breed, highly flexible, highly extensible, easy-to-use, web-based benefit management solution.  The culmination of this effort is RxNova™, the convergence of our customer collaboration and insight with Argus innovation and delivery.  

"Argus has embraced a 'listen first, then act' approach in its system enhancement efforts, ensuring that the resources devoted to this effort have been focused on solving real-world customer issues as opposed to producing technologies in search of a business need, as sometimes happens when companies eschew listening to their customers," stated Mary Ellen Mitchell, COO, Excelsior Solutions, LLC, a pharmaceutical and healthcare consulting firm. "The fact that such material amounts of innovation have occurred without sacrificing the quality of the core service delivery to customers is a testimony to the technical sophistication of Argus."

RxNova™ provides Argus customers with a robust system designed to allow the user to control benefit development through an intuitive protocol that gives the user increased control of their benefit design and exposure to their data without the need for hard coding. This initiative includes a user interface with an intuitive rules-based architecture to engage with the software, delivering greater ease of use, and flexibility in customized benefit design.

To facilitate increased benefit complexities, enhancements to the benefit auditability include customized messaging and tagging options within the benefit rules structure. Embedded into this component is Benefit Validator™, documentation and analytics that provide a real-time accountability trail and audit feature that supports and augments evidence of coverage at the pharmacy-benefit level. Enhancements to claim inquiry include detailed data enrichment that provides a decision flow of the adjudicated claim, including each of the decision points or rules utilized during the adjudication process. The increased visibility into these decision points includes a historical audit perspective that identifies messages associated with the claim as it was adjudicated, such as error exceptions and overrides. Historically, several hours could be spent on pharmacy claim research to determine why and how a particular claim derived its resultant financial and clinical outcome; RxNova™ has built-in data enrichment capability that provides the user a logical view of the executed rules and illuminates the entire picture of the adjudication process from beginning to end.

"Increasing market complexities in the healthcare industry, combined with stringent government regulations and guidance, have compelled businesses that support healthcare to significantly expand their functionality to harness the possibilities created by these trends," said Jonathan Boehm, president and CEO, Argus Health Systems. "Our focus has always been on our customers and offering them the most efficient solutions to meet their business needs. RxNova™ is a culmination of the synergistic relationship we are fortunate to enjoy with our customers. We have integrated new functionality, design flexibility, and powerful rules configuration with robust, reliable and resilient technical infrastructure that allows our customers to confidently deliver their benefit designs in an online fashion, presenting clear visibility into their outcomes based on their business and clinical decisions. We have accomplished this without sacrificing the reliability and scalability they have come to expect with Argus. RxNova™ provides superior navigation, testing, analytic and reporting capabilities, and enables customization at a very granular level. These enhancements also allow our customers to be more competitive related to time to market, help them increase efficiencies, and enable them to take advantage of an integrated claims-benefit management solution. This is an exciting time to be an Argus customer as we continue to focus on our customers and their business demands in this period of rapid change and opportunity."

About Argus Health Systems, Inc.
Argus is a leading independent provider of healthcare information management services supporting commercial, Medicaid and Medicare Part D with a business model that provides full disclosure and transparency. Argus serves a wide range of clients and key healthcare organizations, including managed care organizations, pharmacy benefit managers and pharmaceutical manufacturers. Argus is a wholly-owned subsidiary of DST Systems, Inc. For more information, please visit http://argushealth.com.

About DST Systems, Inc.

DST Systems, Inc. provides sophisticated information processing solutions and services to support the global asset management, insurance, retirement, brokerage, and healthcare industries. In addition to technology products and services, DST also provides integrated print and electronic statement and billing solutions through DST Output. DST's world-class data centers provide technology infrastructure support for financial services and healthcare companies around the globe. Headquartered in Kansas City, MO., DST is a publicly traded company on the New York Stock Exchange.

MEDIA CONTACT:
Larry Stephenson
816-843-9087

The information and comments in this press release may include forward-looking statements respecting DST and its businesses. Such information and comments are based on DST's views as of today, and actual actions or results could differ. There could be a number of factors, risks, uncertainties or contingencies that could affect future actions or results, including but not limited to those set forth in DST's periodic reports (Forms 10-K or 10-Q) filed from time to time with the Securities and Exchange Commission. All such factors should be considered in evaluating any forward-looking statements. The Company undertakes no obligation to update any forward-looking statements in this press release to reflect future events. Brand, service or product names or marks in this press release are trademarks or service marks, registered or otherwise, of DST Systems, Inc., DST subsidiaries or affiliates, or third parties.

The information and comments above may include forward-looking statements respecting DST and its businesses. Such information and comments are based on DST's views as of today, and actual actions or results could differ. There could be a number of factors affecting future actions or results, including those set forth in DST's latest periodic financial report (Form 10-K or 10-Q) filed with the Securities and Exchange Commission. All such factors should be considered in evaluating any forward-looking comment. The Company will not update any forward-looking statements in this press release to reflect future events.

SOURCE Argus Health Systems, Inc.

More Stories By PR Newswire

Copyright © 2007 PR Newswire. All rights reserved. Republication or redistribution of PRNewswire content is expressly prohibited without the prior written consent of PRNewswire. PRNewswire shall not be liable for any errors or delays in the content, or for any actions taken in reliance thereon.

CloudEXPO Stories
The deluge of IoT sensor data collected from connected devices and the powerful AI required to make that data actionable are giving rise to a hybrid ecosystem in which cloud, on-prem and edge processes become interweaved. Attendees will learn how emerging composable infrastructure solutions deliver the adaptive architecture needed to manage this new data reality. Machine learning algorithms can better anticipate data storms and automate resources to support surges, including fully scalable GPU-centric compute for the most data-intensive applications. Hyperconverged systems already in place can be revitalized with vendor-agnostic, PCIe-deployed, disaggregated approach to composable, maximizing the value of previous investments.
Wooed by the promise of faster innovation, lower TCO, and greater agility, businesses of every shape and size have embraced the cloud at every layer of the IT stack – from apps to file sharing to infrastructure. The typical organization currently uses more than a dozen sanctioned cloud apps and will shift more than half of all workloads to the cloud by 2018. Such cloud investments have delivered measurable benefits. But they’ve also resulted in some unintended side-effects: complexity and risk. End users now struggle to navigate multiple environments with varying degrees of performance. Companies are unclear on the security of their data and network access. And IT squads are overwhelmed trying to monitor and manage it all.
Machine learning provides predictive models which a business can apply in countless ways to better understand its customers and operations. Since machine learning was first developed with flat, tabular data in mind, it is still not widely understood: when does it make sense to use graph databases and machine learning in combination? This talk tackles the question from two ends: classifying predictive analytics methods and assessing graph database attributes. It also examines the ongoing lifecycle for machine learning in production. From this analysis it builds a framework for seeing where machine learning on a graph can be advantageous.'
With more than 30 Kubernetes solutions in the marketplace, it's tempting to think Kubernetes and the vendor ecosystem has solved the problem of operationalizing containers at scale or of automatically managing the elasticity of the underlying infrastructure that these solutions need to be truly scalable. Far from it. There are at least six major pain points that companies experience when they try to deploy and run Kubernetes in their complex environments. In this presentation, the speaker will detail these pain points and explain how cloud can address them.
When applications are hosted on servers, they produce immense quantities of logging data. Quality engineers should verify that apps are producing log data that is existent, correct, consumable, and complete. Otherwise, apps in production are not easily monitored, have issues that are difficult to detect, and cannot be corrected quickly. Tom Chavez presents the four steps that quality engineers should include in every test plan for apps that produce log output or other machine data. Learn the steps so your team's apps not only function but also can be monitored and understood from their machine data when running in production.