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A new role for primary care teams in the United States after “Obamacare:” Track and improve health insurance coverage rates

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      Abstract

      Maintaining continuous health insurance coverage is important. With recent expansions in access to coverage in the United States after “Obamacare,” primary care teams have a new role in helping to track and improve coverage rates and to provide outreach to patients. We describe efforts to longitudinally track health insurance rates using data from the electronic health record (EHR) of a primary care network and to use these data to support practice-based insurance outreach and assistance. Although we highlight a few examples from one network, we believe there is great potential for doing this type of work in a broad range of family medicine and community health clinics that provide continuity of care. By partnering with researchers through practice-based research networks and other similar collaboratives, primary care practices can greatly expand the use of EHR data and EHR-based tools targeting improvements in health insurance and quality health care.

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      Most cited references 41

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      Big data analytics in healthcare: promise and potential

      Objective To describe the promise and potential of big data analytics in healthcare. Methods The paper describes the nascent field of big data analytics in healthcare, discusses the benefits, outlines an architectural framework and methodology, describes examples reported in the literature, briefly discusses the challenges, and offers conclusions. Results The paper provides a broad overview of big data analytics for healthcare researchers and practitioners. Conclusions Big data analytics in healthcare is evolving into a promising field for providing insight from very large data sets and improving outcomes while reducing costs. Its potential is great; however there remain challenges to overcome.
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        The causal effect of health insurance on utilization and outcomes in adults: a systematic review of US studies.

        No current consensus exists on the causal effect of gaining or losing health insurance on health care utilization and health outcomes. To systemically search and review available evidence of estimated causal effects of health insurance on health care utilization and/or health outcomes among nonelderly adults in the United States. A systematic search of 3 electronic databases (PubMed, JSTOR, EconLit) was performed. To be included in the review, studies had to have a publication date after 1991; a population of nonelderly adults; analyses comparing an uninsured group to an appropriate control group; and 1 of 3 study designs that account for potential reverse causality and provide estimates of causal effects (longitudinal cohort, instrumental variable analysis, or quasi-experimental design). A total of 9701 studies, including duplicates, were primarily screened. Fourteen studies fulfilled the criteria to be included in this review-4 longitudinal cohort studies using standard regression or fixed effects analysis, 5 longitudinal cohort studies using instrumental variable regression analysis, and 5 quasi-experimental studies. Results of our review of empirical studies that estimate causal relationships between health insurance and health care utilization and/or health outcomes consistently show that health insurance increases utilization and improves health. Specifically, health insurance had substantial effects on the use of physician services, preventive services, self-reported health status, and mortality conditional on injury and disease. These results both confirm and contradict comparable results from the RAND Health Insurance Experiment, the gold standard on relationships between health insurance, utilization, and health.
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          Changes in mortality after Massachusetts health care reform: a quasi-experimental study.

          The Massachusetts 2006 health care reform has been called a model for the Affordable Care Act. The law attained near-universal insurance coverage and increased access to care. Its effect on population health is less clear.
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            Author and article information

            Affiliations
            1Oregon Health and Science University, Portland, OR, USA
            2OCHIN, Inc, Portland, OR, USA
            3Kaiser Permanente Center for Health Research Northwest Region, Portland, OR, USA
            Author notes
            CORRESPONDING AUTHOR: Heather Angier, MPH, Oregon Health and Science University, 3181 SW Sam Jackson Park Road, Portland, OR 97239-3098, USA, Tel.: +1-503-3496362, Fax: +1-503-4942746, E-mail: angierh@123456ohsu.edu
            Journal
            FMCH
            Family Medicine and Community Health
            FMCH
            Compuscript (Ireland)
            2009-8774
            2305-6983
            December 2016
            December 2016
            : 4
            : 4
            : 63-67
            Copyright © 2016 Family Medicine and Community Health

            This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 Unported License (CC BY-NC 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. See https://creativecommons.org/licenses/by-nc/4.0/.

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            Self URI (journal page): http://fmch-journal.org/
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