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<journal-meta>
<journal-id journal-id-type="publisher">global-journal-of-human-social-science-h-interdisciplinary</journal-id>
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<journal-title>Global Journal of Human-Social Science - H: Interdisciplinary</journal-title>
</journal-title-group>
<issn publication-format="print">0975-587X</issn>
<issn publication-format="electronic">2249-460X</issn>
<publisher><publisher-name>Global Journals Publishing Group Incorporated</publisher-name></publisher>
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<article-id pub-id-type="publisher-id">115597</article-id>
<title-group>
<article-title>Using Data Envelope Analysis to Examine US State Health Efficiencies over 2008-2015</article-title>
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<contrib-group>
<contrib contrib-type="author"><name><surname>Putzer</surname><given-names>Dr. Gavin</given-names></name><xref ref-type="aff" rid="aff1" />
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<aff id="aff1">UNITED STATES, Stetson University</aff>
<pub-date publication-format="electronic" date-type="pub" iso-8601-date="2017-01-15">
<day>15</day>
<month>01</month>
<year>2017</year>
</pub-date>
<volume>17</volume>
<issue>H2</issue>
<abstract><p>Health spending in the United States (US) has been steadily rising over the past several decades. The Affordable Care Act (ACA) became law in 2010, but was not operational until 2014. The principal intention of the legislation was to provide insurance coverage to millions of US citizens who previously did not possess health insurance to improve Americans’ health. In our study, we compare the efficiency of health care resources on a state-by-state population basis in the US between the years of 2008-2015. Efficiencies are calculated using Data Envelopment Analysis (DEA). DEA can be defined as a non-parametric technique that uses linear programming (lp) to compare the relative efficiencies of homogenous Decision Making Units (DMU) in transforming inputs into outputs. In this case, the DMUs represent the states. DEA uses lp models to build an efficiency frontier. The efficiency frontier is determined by the most efficient states (i.e., DMUs). Therefore the efficiency of each state can be compared against the frontier and therefore against the most efficient ones.</p></abstract>
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<p>Health spending in the United States (US) has been steadily rising over the past several decades. The Affordable Care Act (ACA) became law in 2010, but was not operational until 2014. The principal intention of the legislation was to provide insurance coverage to millions of US citizens who previously did not possess health insurance to improve Americans’ health. In our study, we compare the efficiency of health care resources on a state-by-state population basis in the US between the years of 2008-2015. Efficiencies are calculated using Data Envelopment Analysis (DEA). DEA can be defined as a non-parametric technique that uses linear programming (lp) to compare the relative efficiencies of homogenous Decision Making Units (DMU) in transforming inputs into outputs. In this case, the DMUs represent the states. DEA uses lp models to build an efficiency frontier. The efficiency frontier is determined by the most efficient states (i.e., DMUs). Therefore the efficiency of each state can be compared against the frontier and therefore against the most efficient ones.</p>
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