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  • Health IT Headlines for 2018

    January 19, 2018 Editorial Team in Big DataFeaturedMedeAnalytics

    2018 is already off to a strong start with the J.P. Morgan Healthcare Conference and StartUp Health Festival making headlines last week. As 2018 progresses, we want to share the trends that we expect to make headlines this year:

    • Mega merger and acquisition activity – 2017 was filled with notable M&A activity including CVS and Aetna, Humana and Kindred and Optum and AMGA, to name a few. We expect to see this activity continue throughout 2018 as payers, providers, pharmacies and more look for ways to innovate, meet consumer demands and ultimately improve the quality and cost of care. Bruce Carver, associate vice president of payer services at MedeAnalytics, shares additional thoughts on recent merger activity in our blog.
    • Consumerization of healthcare – With consumer-facing companies outside of the traditional healthcare space making moves to enter the industry (like Amazon, Apple and Google), consumer focus is critical. In 2018, this focus will only increase as consumers continue to demand user-friendly and easy to use platforms and interfaces. With all the competition in the industry, healthcare organizations will have to ensure they are keeping the consumer top of mind to stay ahead.
    • Emerging technologies, like AI, will take the stage – In 2017, the adoption of AI technology made headlines across all industries, healthcare included, as organizations looked for innovative ways to leverage this new tool. As we head into 2018, companies like Google will continue to lead the pack by working with startups that are focused on finding ways to leverage this technology to improve care. We recently sat down with our CTO, Tyler Downs, to discuss trends in AI in healthcare and to hear how companies can use AI to power data and analytics.
    • Clarity around industry uncertainty and policy changes – With the Trump administration and new faces in prominent health IT positions, the industry saw major shifts in 2017. According to a recent poll, healthcare is the one topic keeping both Democrats and Republicans up at night. 2018 will hopefully bring some clarity to the shifting tide as policies get ironed out and the state of Obamacare is decided. Regardless of these policy changes, providing patients with the best quality care should remain the industry’s top priority.

    With all the new trends, emerging innovations, policy changes and more, is your organization prepared? Check out our solutions page to learn how MedeAnalytics can help you find success in the new year or contact us for additional information. 

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  • A Year In Review – Our Top Blogs from 2017

    January 8, 2018 Editorial Team in Big DataEnterprise AnalyticsFeaturedMedeAnalytics

    As snow starts to fall across the country and temperatures decline, winter and 2018 are here! 2017 was a busy year for the healthcare industry, from the new administration, ground breaking treatment advancements, the potential of artificial intelligence and most recently, the CVS and Aetna health merger. 2017 has also been a busy year for us at MedeAnalytics with new hires, customer announcements, speaking sessions and more! As we gear up for the new year, we’re looking back and highlighting our top three blog posts from 2017:

    Meet MedeAnalytics’ new CEO, Paul Kaiser – In May, we were excited to announce our new CEO, Paul Kaiser, and in June, we had a chance to connect with him to learn more about his background, his company observations thus far and his future plans for the company. Our blog outlines the opportunities our CEO sees for Mede clients and how we can continue to support them amidst the everchanging healthcare landscape.

    Enterprise Analytics and Beyond: A Q&A with our Vice President of Healthcare Provider Solutions – In March, our blog explored top provider concerns and offered insight from a Mede executive on the challenges that lay ahead and continued importance of investing in an Enterprise Analytics (EA) strategy. The post outlined proactive approaches for providers to take to ensure a seamless EA strategy, including training and educating clinical leadership, establishing realistic goals and empowering self-service. The post concluded by outlining how analytics’ role in reporting and identifying care and cost improvement opportunities will only grow in importance in the years ahead.

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  • Machine Learning: A Q&A with CTO Tyler Downs

    December 19, 2017 in FeaturedMedeAnalytics

    We recently sat down with Tyler Downs, CTO of MedeAnalytics to discuss trends in machine learning in healthcare. He offered insights into how MedeAnalytics is using machine learning to power data analytics and what’s in store for the future of the technology.

    Q: What exactly is machine learning?

    A: In layman’s terms, machine learning is the application of artificial intelligence that enables computers to automatically learn and improve from experience without being explicitly programmed. It’s all about developing computer programs that can access data and learn from it themselves.

    Machine learning is used every day in social networking, commuting apps, and online shopping. Think of Facebook. When you upload photos to Facebook, it automatically highlights faces and suggests friends to tag. Facebook also uses algorithms to personalize your newsfeed and ensure you’re seeing posts that interest you. Google Maps analyzes the speed of traffic at any given time. And on Amazon, you see recommendations for products you might be interested in, displaying “customers who bought this item also bought…”. These all use forms of machine learning.

    Q: How is machine learning being used in healthcare?

    A: Think about the huge volumes of data being generated in healthcare. Machine learning can be trained to look at structured and unstructured data (images, video, audio files), identify anomalies, and point to areas that need attention.

    There are clinical, financial, and operational applications of machine learning in healthcare. In the clinical realm, Google has developed a machine learning algorithm to aid in tumor-detection on mammograms. Stanford is using algorithms to identify skin cancer.

    In the revenue cycle, machine learning can be used to predict denials, improve point-of-service collections, and identify a patient’s propensity to pay their bills. This enables the health system to increase reimbursement, reduce the cost collect, reduce bad debt, and more.

    For healthcare operations, machine learning enables providers to improve throughput in the OR and ED, assess the risk of no-shows, identify trends in patient volumes, determine the appropriate appointment length, and enable schedulers to allocate the right amount of time for procedures based on the individual patient and physician. These capabilities drive down costs, which is important considering the average cost of an OR can be as much as $60-80 per minute (Stanford).

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  • Mississippi Division of Medicaid Establishes Its Second Real-Time Clinical Data Exchange

    December 11, 2017 Editorial Team in Big DataClinical Data InfrastructureFeaturedMedeAnalyticsMedicare/Medicaid

    Just last month, MedeAnalytics announced that the Mississippi Division of Medicaid (DOM) continued to build its data exchange within the state by connecting with the Hattiesburg Clinic (Hattiesburg). This is the second such clinical exchange and the second largest provider of Mississippi Medicaid beneficiaries. DOM built its first connection with the largest provider, the University of Mississippi Medical Center (UMMC), which resulted in more than two million clinical summaries.

    On Aug. 1, DOM successfully linked its beneficiary data-analysis system with Hattiesburg’s electronic health record (EHR). MedeAnalytics established DOM’s Medicaid Enterprise Master Patient Index (EMPI) back in 2014 as the core identity management system to allow easy management of a Medicaid patient’s longitudinal record. From there, they worked with DOM to standardize the Medicaid clinical EMPI to support a clinical data interface with its external stakeholders. Since the connection, both DOM and Hattiesburg have shared clinical information on 20,000 individual Medicaid patients, or 100,000 total shared clinical reports. Mississippi is the first state in the nation to establish this method for leveraging Medicaid technology and resources to directly benefit the doctor/patient experience.

    Our very own CEO, Paul Kaiser, noted that: “DOM is a model example for Medicaid interoperability and how other agencies across the nation can leverage data to improve beneficiary care. MedeAnalytics has powered the Division’s first major provider data connection since 2016 and we look forward to continually supporting their efforts to expand connectivity with other providers across the state of Mississippi.”

    The continued partnership is driving change in healthcare – from informed delivery of care to fueling overall value-based goals and progress. Looking ahead, DOM plans to continue integration with Medicaid-focused health systems, Health Information Exchanges and state and federal agencies. In fact, just last month they went live with their third clinical data exchange connection – Singing River Health System. For additional insights on how MedeAnalytics can help create connectivity, visit our solutions for state government page here. To learn more about our relationship with DOM see here and here.

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  • What Would the CVS/Aetna Merger Mean for Healthcare?

    November 21, 2017 Editorial Team in FeaturedMedeAnalytics

    Despite the uncertainty surrounding the industry, healthcare mergers and acquisitions, like the proposed CVS Health/Aetna deal, continue to occur. Healthcare is leading other industries in high-grade M&A activity and, according to a PwC report, the health care industry has initiated more than 200 deals per quarter for 12 straight quarters since 2015.

    If the CVS and Aetna deal is approved, the acquisition will be the largest healthcare insurance deal on record based on Aetna’s market capitalization. How could this impact the healthcare industry as a whole? Bruce Carver, associate vice president of payer services, recently connected with Managed Healthcare Executive to share his thoughts. Here are three key implications outlined from the discussion:

    • Impact on Industry Competition – If the merger is approved, healthcare executives will likely need to rethink traditional industry competitors as this would establish market competition against national payer UnitedHealth Group and its ownership of OptumRx.
    • Greater Transparency From Pharmacy Benefit Managers (PBMs) - PBMs have historically been viewed as the drug purchasing middlemen to negotiate lower prices. However, questions have arisen as to whether the savings have actually been passed on to employers and/or consumers. As a result, the market is demanding more pricing transparency. New integrated models, similar to the one created by the CVS and Aetna merger, will help facilitate that transparency.
    • Give Employers and Consumers More Control – By allowing employers and consumers to own more of their healthcare and pharmacy benefits, the industry could save millions. For example, by creating pharmacy benefits that incentivize people with chronic conditions (e.g. diabetes, high blood pressure) to fill and adhere to their medications, the industry could prevent avoidable hospital admissions that cost over $100 billion a year. An integrated insurer, like CVS and Aetna, could establish such incentives.

    To read more insights from Bruce, and other industry experts, check out the full Managed Healthcare Executive articles here and here. If you’re looking for a partner to help your organization manage the shifting healthcare landscape, contact us here.

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