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    GNS, Cambia Use Big Data to Study Medication Adherence, Health Costs

    Written by

    Brian T. Horowitz
    Published July 1, 2013
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      Amid big data analytics’ increasing role in health care, software developer GNS Healthcare and nonprofit health plan provider Cambia Health Solutions announced June 27 that they will build a medication adherence platform to allow health professionals to study the causal relationship between adhering to medication routines and reducing health care costs.

      Called Medication Adherence, the platform will use big data analytics platform from GNS to analyze health data from Cambia, a nonprofit that offers medical insurance plans in the Northwest and Intermountain regions.

      Poor medication adherence results in about $100 billion to $289 billion in annual health care costs, according to a study in the Annals of Internal Medicine. Patients not taking their medication also leads to 125,000 deaths each year, according to the publication.

      GNS’ Reverse Engineering and Forward Simulation (REFS) modeling framework in the Medication Adherence platform will allow researchers to study how medication use relates to health care expenses, Carol McCall, chief strategy officer of GNS, told eWEEK in an email.

      The REFS framework is powered by a cloud-based scalable supercomputer and generates causal network models to study relationships in disparate data types.

      Advanced machine-learning algorithms in REFS enables health care professionals to understand relationships in large data sets, such as whether taking certain medications will affect health outcomes and expenses, McCall said.

      REFS is also used by researchers to study the causal relationship between a patient’s genotype and medical history.

      “Health plans have the ability to take their own members’ data and use it to predict which patients are most at risk for low adherence, which medications most need to be adhered to and which interventions will produce the most meaningful changes in costs and outcomes,” McCall said.

      Big data helps providers understand personalized health patterns for individual patients. By spotting relationships between medication adherence and medical costs, health plans will be able to tailor clinical programs to individual members, Dr. Richard Popiel, executive vice president of health care services and chief medical officer for Cambia Health Solutions, said in a statement.

      Cambia will accumulate the data for the big data platform from pharmacy, medical and laboratory claims information. Researchers will de-identify the data to conform with the Health Insurance Portability and Accountability Act (HIPAA), McCall noted.

      After incorporating patient data into the platform, medical researchers can run simulations to see how different levels of medical adherence affect health care costs and outcomes.

      In addition to medication adherence, GNS is also using the REFS platform to craft a computer model to fight Huntington’s disease, a debilitating neurodegenerative disorder. The nonprofit scientific research organization CHDI Foundation will work with GNS to study disease progression and drug response.

      Depending on the information gleaned from the data-modeling platform, Cambia could “intervene” with members and providers to improve a patient’s drug adherence by changing a co-payment amount, scheduling follow-up visits or providing guidance on why they should take their medication, according to McCall.

      Health plans would communicate this information to members through text messages, phone call reminders and face-to-face counseling sessions with pharmacists, she said.

      Brian T. Horowitz
      Brian T. Horowitz
      Brian T. Horowitz is a technology and health writer as well as a copy editor. Brian has worked on the tech beat since 1996 and covered health care IT and rugged mobile computing for eWEEK since 2010. He has contributed to more than 20 publications, including Computer Shopper, Fast Company, FOXNews.com, More, NYSE Magazine, Parents, ScientificAmerican.com, USA Weekend and Womansday.com, as well as other consumer and trade publications.

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