Blog

Featured Post
A Year In Review – Our Top Blogs from 2017

January 8, 2018 Editorial Team in Big DataEnterprise AnalyticsFeaturedMedeAnalytics

Read More

More Posts
  • 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).

    Read More

  • 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.

    Read More

  • 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.

    Read More

  • 2017 Payer Solutions Summit: Bringing Together the MedeAnalytics Payer Community

    November 15, 2017 Editorial Team in FeaturedMedeAnalytics

    From October 25-27, the MedeAnalytics payer community came together at La Cantera Resort and Spa in San Antonio, Texas for the 2017 Payer Solutions Summit. The event gave attendees the opportunity to collaborate to better understand how to keep up with the growth and evolution of the industry, with the support of MedeAnalytics’ solutions and thought leaders.

    Our very own CEO, Paul Kaiser, kicked off the event, introducing himself and discussing his aspirations for the company. Kaiser highlighted how impressed he was with our committed associates, fantastic clients and great technology offerings. He realized how special of a company MedeAnalytics was within the first five months of his new role. Kaiser concluded his presentation by outlining his hopes for MedeAnalytics, which include continuing to evolve, innovate and scale in terms of client value management and transparency.

    In addition to our CEO, Scott Hampel, SVP of product and strategy, and Tyler Downs, CTO, took the stage to discuss product innovation alignment and the payer portfolio. They also explored the company’s technology strategy and plans for growth, including platform innovations, machine learning, guided analysis, third-party integration and more.

    In addition to key thought leaders within the company, several payer clients also delivered presentations that demonstrated their unique use of the MedeAnalytics platform and the results they achieved. Some of the representatives included Mississippi Division of Medicaid, St. Joseph Hospital, part of Covenant Health, Presbyterian Healthcare Services, MVP Health Care, and Kaiser Permanente.

    Read More