Modelo para evaluar el desempeño de un sistema de salud desde el análisis de redes: un enfoque basado en los patrones de morbilidad y su relación con los servicios de salud

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dc.contributor.advisorHurtado Heredia, Rafael German
dc.contributor.authorSaavedra Moreno, Carolina
dc.contributor.supervisorVelasco Rodríguez, Nubia Milena
dc.date.accessioned2023-06-05T15:32:01Z
dc.date.available2023-06-05T15:32:01Z
dc.date.issued2022-08-29
dc.descriptionilustracionesspa
dc.description.abstractEl objetivo general de un sistema de salud es promover, restaurar y mantener la salud de la población, así como influir en los determinantes en salud. Para evaluar el grado de cumplimiento de este objetivo es necesario conocer el estado de salud de las poblaciones y para ello uno de los enfoques es el estudio de la morbilidad poblacional, el cual vincula información de uno o varios diagnósticos de manera independiente y cuyos indicadores en general son fragmentados. Teniendo en cuenta que es posible utilizar enfoques relacionales como el del Análisis de Redes para estudiar los patrones de morbilidad, en esta tesis se proponen representaciones relacionales para caracterizar los patrones de morbilidad y su relación con el componente de prestación de servicios del sistema, considerando los determinantes de salud de edad, sexo y condición socioeconómica. A partir de la aplicación de estas representaciones en esta tesis se propone un conjunto de medidas de red que brindan información sobre la estructura y la dinámica de los sistemas de salud que, en conjunto, configuran el modelo conceptual para evaluar el desempeño de los sistemas estudiados. (texto tomado de la fuente)
dc.description.abstractThe primary objective of a healthcare system is to promote, restore, and maintain the health of the population, as well as to influence the factors that affect health. The extent to which this objective is achieved can be evaluated by examining the health status of the population. One method of measuring health status is to analyze morbidity within a population, typically by gathering information on one or more diagnoses independently. This thesis proposes the use of relational representations through the Network Analysis approach to characterize morbidity patterns and their correlation with healthcare services, considering age, sex, and socioeconomic stratification as determinants of health. By employing relational representations in multiple populations, we propose a set of network measures that offer insights into the structure and dynamics of these patterns. These measures form a conceptual model for evaluating the performance of a healthcare systemeng
dc.description.degreelevelDoctoradospa
dc.description.researchareaEconofísica y Sociofísicaspa
dc.format.extent109 páginasspa
dc.format.mimetypeapplication/pdfspa
dc.identifier.instnameUniversidad Nacional de Colombiaspa
dc.identifier.reponameRepositorio Institucional Universidad Nacional de Colombiaspa
dc.identifier.repourlhttps://repositorio.unal.edu.co/spa
dc.identifier.urihttps://repositorio.unal.edu.co/handle/unal/83962
dc.language.isospaspa
dc.publisher.branchUniversidad Nacional de Colombia - Sede Bogotáspa
dc.publisher.facultyFacultad de Administraciónspa
dc.publisher.programAmazonía - Amazonía - Doctorado en Estudios Amazónicosspa
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dc.relation.referencesValente, T. W., & Pitts, S. R. (2017). An Appraisal of Social Network Theory and Analysis as Applied to Public Health: Challenges and Opportunities. Annual Review of Public Health, 38, 1–16. https://doi.org/10.1146/annurev-publhealth-031816-044528spa
dc.relation.referencesVinjerui, K. H., Bjerkeset, O., Bjorngaard, J. H., Krokstad, S., Douglas, K. A., & Sund, E. R. (2020). Socioeconomic inequalities in the prevalence of complex multimorbidity in a Norwegian population: Findings from the cross-sectional HUNT Study. BMJ Open, 10(6), 1–9. https://doi.org/10.1136/bmjopen-2020-036851spa
dc.relation.referencesWasserman, S., & Faust, K. (1994). Social Network Analysis Methods and applications. Cambridge University Press.spa
dc.relation.referencesWei, M. Y., Ratz, D., & Mukamal, K. J. (2020). Multimorbidity in Medicare Beneficiaries: Performance of an ICD-Coded Multimorbidity-Weighted Index. Journal of the American Geriatrics Society, 68(5), 999–1006. https://doi.org/10.1111/jgs.16310spa
dc.relation.referencesZavala, C., & Florenzano, F. (2015). Diabetes y Corazón. Revista Clínica Las Condes, 26(2), 175–185. https://doi.org/10.1016/j.rmclc.2015.04.006spa
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dc.rights.licenseAtribución-NoComercial-SinDerivadas 4.0 Internacionalspa
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/spa
dc.subject.decsEnfermedades individualesspa
dc.subject.decsIndividual Diseaseseng
dc.subject.decsEncuestas de morbilidadspa
dc.subject.decsMorbidity Surveyseng
dc.subject.decsIndicadoresd emorbimortalidadspa
dc.subject.decsIndicators of Morbidity and Mortalityeng
dc.subject.proposalSistema de Saludspa
dc.subject.proposalMorbilidadspa
dc.subject.proposalMultimorbilidadspa
dc.subject.proposalAnálisis de Redesspa
dc.subject.proposalEvaluación del Desempeñospa
dc.titleModelo para evaluar el desempeño de un sistema de salud desde el análisis de redes: un enfoque basado en los patrones de morbilidad y su relación con los servicios de salud
dc.title.translatedA model to assess the performance of a health system from the network analysis perspective: an approach based in morbidity patterns and their relation with health services
dc.typeTrabajo de grado - Doctoradospa
dc.type.coarhttp://purl.org/coar/resource_type/c_db06spa
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dc.type.driverinfo:eu-repo/semantics/doctoralThesisspa
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dc.type.versioninfo:eu-repo/semantics/acceptedVersionspa
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