<?xml version="1.0" encoding="ISO-8859-1"?><article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">
<front>
<journal-meta>
<journal-id>0213-9111</journal-id>
<journal-title><![CDATA[Gaceta Sanitaria]]></journal-title>
<abbrev-journal-title><![CDATA[Gac Sanit]]></abbrev-journal-title>
<issn>0213-9111</issn>
<publisher>
<publisher-name><![CDATA[Sociedad Española de Salud Pública y Administración Sanitaria (SESPAS)]]></publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id>S0213-91112019000100006</article-id>
<article-id pub-id-type="doi">10.1016/j.gaceta.2017.05.017</article-id>
<title-group>
<article-title xml:lang="es"><![CDATA[Análisis poblacional del gasto en servicios sanitarios en Cataluña (España): ¿qué y quién consume más recursos?]]></article-title>
<article-title xml:lang="en"><![CDATA[Population-based analysis of the Healthcare expenditure in Catalonia (Spain): what and who consumes more resources?]]></article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Vela]]></surname>
<given-names><![CDATA[Emili]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Clèries]]></surname>
<given-names><![CDATA[Montse]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Vella]]></surname>
<given-names><![CDATA[Vincenzo Alberto]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Adroher]]></surname>
<given-names><![CDATA[Cristina]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[García-Altés]]></surname>
<given-names><![CDATA[Anna]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
<xref ref-type="aff" rid="Aaf"/>
<xref ref-type="aff" rid="A a"/>
<xref ref-type="aff" rid="A4"/>
</contrib>
</contrib-group>
<aff id="Af1">
<institution><![CDATA[,Servei Català de la Salut  ]]></institution>
<addr-line><![CDATA[Barcelona ]]></addr-line>
<country>Spain</country>
</aff>
<aff id="Af2">
<institution><![CDATA[,Agència de Qualitat i Avaluació Sanitàries de Catalunya  ]]></institution>
<addr-line><![CDATA[Barcelona ]]></addr-line>
<country>Spain</country>
</aff>
<aff id="Af3">
<institution><![CDATA[,Centro de Investigación Biomédica en Red Epidemiología y Salud Pública  ]]></institution>
<addr-line><![CDATA[ ]]></addr-line>
<country>España</country>
</aff>
<aff id="Af4">
<institution><![CDATA[,Institut d&#8217;Investigació Biomèdica  ]]></institution>
<addr-line><![CDATA[Barcelona ]]></addr-line>
<country>Spain</country>
</aff>
<pub-date pub-type="pub">
<day>00</day>
<month>02</month>
<year>2019</year>
</pub-date>
<pub-date pub-type="epub">
<day>00</day>
<month>02</month>
<year>2019</year>
</pub-date>
<volume>33</volume>
<numero>1</numero>
<fpage>24</fpage>
<lpage>31</lpage>
<copyright-statement/>
<copyright-year/>
<self-uri xlink:href="http://scielo.isciii.es/scielo.php?script=sci_arttext&amp;pid=S0213-91112019000100006&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://scielo.isciii.es/scielo.php?script=sci_abstract&amp;pid=S0213-91112019000100006&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://scielo.isciii.es/scielo.php?script=sci_pdf&amp;pid=S0213-91112019000100006&amp;lng=en&amp;nrm=iso"></self-uri><abstract abstract-type="short" xml:lang="es"><p><![CDATA[Resumen  Objetivo Analizar la distribución del gasto sanitario según el ámbito asistencial y las características de los pacientes, utilizando microdatos del uso de servicios sanitarios del total de la población de Cataluña (España).  Método Se ha aplicado una tarifa o un gasto indirecto a todos los actos sanitarios financiados por CatSalut durante 2014, computando el gasto sanitario realizado por cada persona y sumando para todos los habitantes de Cataluña.  Resultados La suma del gasto sanitario realizado por todos los habitantes de Cataluña representa el 97,0% del presupuesto de CatSalut. La mitad de la población origina el 3,6% del gasto sanitario total (71 &#8364; por persona); un 1% de la población gastó el 23% del gasto (22.852 &#8364; por persona). El gasto medio más elevado, tanto en mujeres como en hombres, se da entre los 80 y los 89 años de edad. La población con una enfermedad crónica tiene un gasto medio anual de 413 &#8364;; con cinco, de 2413 &#8364;; y con 10, de 9626&#8364;. El gasto medio varía según patologías, desde los 2854 &#8364; en los pacientes con depresión grave a los 8097 &#8364; de los pacientes con infección por el virus de la inmunodeficiencia humana/sida.  Conclusiones Los resultados son sumamente útiles para la planificación de los servicios sanitarios y para la priorización de intervenciones de política sanitaria en los colectivos con más necesidades.]]></p></abstract>
<abstract abstract-type="short" xml:lang="en"><p><![CDATA[Abstract  Objective To analyse the distribution of the expenditure according to the healthcare services and characteristics of patients, using the microdata of the Catalan population's use of healthcare services.  Methods A fee or an indirect cost has been applied to all healthcare activities financed by CatSalut during 2014, computing the health expenditure made up by each person and adding it all up for the inhabitants of Catalonia (Spain).  Results The sum of the healthcare expenditure made by all the inhabitants of Catalonia represents 97.0% of the CatSalut budget. Half of the population accounts for 3.6% of total healthcare expenditure (71&#8364; per person); 1% of the population spends 23% of the expenditure (22,852&#8364; per person). The highest average expenditure, in both women and men, occurs between the age of 80 and 89. The population with a chronic disease has an average annual expenditure of 413&#8364;, with 5 of 2,413&#8364;, and 10 of 9,626&#8364;. The average cost varies according to pathologies, from 2,854&#8364; in patients with severe depression to 8,097&#8364; in patients with HIV-AIDS.  Conclusions The results are extremely useful for healthcare planning and for the prioritization of health policy interventions in groups with most needs.]]></p></abstract>
<kwd-group>
<kwd lng="es"><![CDATA[Gasto sanitario]]></kwd>
<kwd lng="es"><![CDATA[Política sanitaria]]></kwd>
<kwd lng="es"><![CDATA[Planificación sanitaria]]></kwd>
<kwd lng="es"><![CDATA[Poblacional]]></kwd>
<kwd lng="es"><![CDATA[Estado de salud]]></kwd>
<kwd lng="en"><![CDATA[Health care cost]]></kwd>
<kwd lng="en"><![CDATA[Health policy]]></kwd>
<kwd lng="en"><![CDATA[Health planning]]></kwd>
<kwd lng="en"><![CDATA[Population-based]]></kwd>
<kwd lng="en"><![CDATA[Health status]]></kwd>
</kwd-group>
</article-meta>
</front><back>
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