<?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>2007-7459</journal-id>
<journal-title><![CDATA[Horizonte sanitario]]></journal-title>
<abbrev-journal-title><![CDATA[Horiz. sanitario]]></abbrev-journal-title>
<issn>2007-7459</issn>
<publisher>
<publisher-name><![CDATA[Universidad Juárez Autónoma de Tabasco, División Académica de Ciencias de la Salud]]></publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id>S2007-74592022000300495</article-id>
<article-id pub-id-type="doi">10.19136/hs.a21n3.4588</article-id>
<title-group>
<article-title xml:lang="es"><![CDATA[Simulación y optimización de sistemas de vacunación con capacidad finita]]></article-title>
<article-title xml:lang="en"><![CDATA[Simulation and optimization of systems vaccination with finite capacity]]></article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Hernández-González]]></surname>
<given-names><![CDATA[Salvador]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Jiménez-García]]></surname>
<given-names><![CDATA[José Alfredo]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Hernández-Ripalda]]></surname>
<given-names><![CDATA[Manuel Darío]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[de-la-Cruz-Madrigal]]></surname>
<given-names><![CDATA[Israel]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
</contrib-group>
<aff id="Af1">
<institution><![CDATA[,Instituto Tecnológico de Celaya  ]]></institution>
<addr-line><![CDATA[Celaya Guanajuato]]></addr-line>
<country>Mexico</country>
</aff>
<aff id="Af2">
<institution><![CDATA[,Instituto Tecnológico de Celaya  ]]></institution>
<addr-line><![CDATA[Celaya Guanajuato]]></addr-line>
<country>Mexico</country>
</aff>
<aff id="Af3">
<institution><![CDATA[,Instituto Tecnológico de Celaya  ]]></institution>
<addr-line><![CDATA[Celaya Guanajuato]]></addr-line>
<country>Mexico</country>
</aff>
<aff id="Af4">
<institution><![CDATA[,Instituto Tecnológico de Celaya  ]]></institution>
<addr-line><![CDATA[Celaya Guanajuato]]></addr-line>
<country>Mexico</country>
</aff>
<pub-date pub-type="pub">
<day>00</day>
<month>12</month>
<year>2022</year>
</pub-date>
<pub-date pub-type="epub">
<day>00</day>
<month>12</month>
<year>2022</year>
</pub-date>
<volume>21</volume>
<numero>3</numero>
<fpage>495</fpage>
<lpage>503</lpage>
<copyright-statement/>
<copyright-year/>
<self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_arttext&amp;pid=S2007-74592022000300495&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_abstract&amp;pid=S2007-74592022000300495&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_pdf&amp;pid=S2007-74592022000300495&amp;lng=en&amp;nrm=iso"></self-uri><abstract abstract-type="short" xml:lang="es"><p><![CDATA[Resumen  Objetivo: Caracterizar y optimizar el flujo de pacientes dentro de un centro de vacunación, para los casos donde debe tomarse en cuenta que existe una capacidad finita en las colas frente a las estaciones.  Materiales y Métodos: Se asume que los sistemas de vacunación se comportan como una red cerrada de colas con capacidad finita; para caracterizar el flujo de pacientes, se aplica simulación y un diseño experimental Box-Bhenken, donde las variables son las capacidades en las colas (buffer); posteriormente se obtienen los metamodelos del tiempo de ciclo y del número de pacientes vacunados, finalmente se calcula la asignación óptima de los lugares en las colas aplicando programación matemática.  Resultados: Las colas de llenado de formatos, entrega de información y vacunación son las de mayor efecto sobre el tiempo de estadía; las colas de vacunación y el Triage son las de mayor efecto sobre la cantidad de pacientes vacunados.Si se maximiza la salida de pacientes, la mayor cantidad de lugares deben asignarse a la estación de vacunación y el resto de los espacios se distribuyen en las demás estaciones; por otra parte, si se minimiza el tiempo de estadía, entonces la mayor parte de los lugares se asignan a la estación Triage y a continuación a la estación de Vacunación, el resto de los espacios se asignarán dependiendo de la capacidad total del sistema.  Conclusiones: Los responsables de administrar esta clase de sistemas deben definir el criterio bajo el cual deben cuantificar el desempeño del sistema de vacunación y a partir de este, gestionar y controlar el proceso. Cuando la demanda supera las expectativas y no es viable incrementar la capacidad, entonces la alternativa es optimizar el flujo controlando la cantidad de personas dentro del sistema.]]></p></abstract>
<abstract abstract-type="short" xml:lang="en"><p><![CDATA[Abstract  Objective: Characterize and optimize the flow of patients within a vaccination center, for cases where it must be consider that there is a finite capacity in the queues in front of the stations.  Materials and Methods: Vaccination systems are assumed to behave as a closed queue network with finite capacity; To characterize the flow of patients, simulation and a Box-Bhenken experimental design are applied, where the variables are the capacities in the queues (buffer); Subsequently, the metamodels of the cycle time and the number of vaccinated patients are obtained. Finally, the optimal allocation of places in the queues is calculated by applying mathematical programming.  Results: The queues for filling out forms, delivery of information and vaccination are the ones with the greatest effect on the length of stay; the vaccination and triage queues have the greatest effect on the number of vaccinated patients. If the output of patients is maximized, the greatest number of places should be assigned to the vaccination station and the rest of the spaces are distributed in the other stations; On the other hand, if the length of stay is minimized, then most of the places are assigned to the Triage station and then to the Vaccination station, the rest of the spaces will be assigned depending on the total capacity of the system.  Conclusions: Those responsible for managing this class of systems must define the criteria under which they must quantify the performance of the vaccination system and, based on this, manage and control the process. When demand exceeds expectations and increasing capacity is not feasible, then the alternative is to optimize flow by controlling the number of people within the system.]]></p></abstract>
<kwd-group>
<kwd lng="es"><![CDATA[Vacunación masiva]]></kwd>
<kwd lng="es"><![CDATA[Utilización de Servicios de Salud]]></kwd>
<kwd lng="es"><![CDATA[Tecnología para la Reducción de los Tiempos de Espera]]></kwd>
<kwd lng="es"><![CDATA[Simulación por Computador]]></kwd>
<kwd lng="es"><![CDATA[Análisis de Regresión]]></kwd>
<kwd lng="en"><![CDATA[Mass vaccination]]></kwd>
<kwd lng="en"><![CDATA[Health Services]]></kwd>
<kwd lng="en"><![CDATA[Technology Applied to Waiting Lists]]></kwd>
<kwd lng="en"><![CDATA[Computer Simulation]]></kwd>
<kwd lng="en"><![CDATA[Regression Analysis]]></kwd>
</kwd-group>
</article-meta>
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