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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
dc.rights.license | Atribución-NoComercial-SinDerivadas 4.0 Internacional |
dc.contributor.advisor | Hurtado Heredia, Rafael German |
dc.contributor.author | Saavedra Moreno, Carolina |
dc.date.accessioned | 2023-06-05T15:32:01Z |
dc.date.available | 2023-06-05T15:32:01Z |
dc.date.issued | 2022-08-29 |
dc.identifier.uri | https://repositorio.unal.edu.co/handle/unal/83962 |
dc.description | ilustraciones |
dc.description.abstract | El 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.abstract | The 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 system |
dc.format.extent | 109 páginas |
dc.format.mimetype | application/pdf |
dc.language.iso | spa |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ |
dc.title | 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 |
dc.type | Trabajo de grado - Doctorado |
dc.type.driver | info:eu-repo/semantics/doctoralThesis |
dc.type.version | info:eu-repo/semantics/acceptedVersion |
dc.publisher.program | Amazonía - Amazonía - Doctorado en Estudios Amazónicos |
dc.contributor.supervisor | Velasco Rodríguez, Nubia Milena |
dc.description.degreelevel | Doctorado |
dc.description.researcharea | Econofísica y Sociofísica |
dc.identifier.instname | Universidad Nacional de Colombia |
dc.identifier.reponame | Repositorio Institucional Universidad Nacional de Colombia |
dc.identifier.repourl | https://repositorio.unal.edu.co/ |
dc.publisher.faculty | Facultad de Administración |
dc.publisher.branch | Universidad Nacional de Colombia - Sede Bogotá |
dc.relation.references | Abebe, F., Schneider, M., Asrat, B., & Ambaw, F. (2020). Multimorbidity of chronic non-communicable diseases in low- and middle-income countries: A scoping review. Journal of Comorbidity, 10, 2235042X2096191. https://doi.org/10.1177/2235042x20961919 |
dc.relation.references | Alfonso-Sierra, E., Arcila, A., Bonilla, J., Latorre, M., Porras, A., & Urquijo, L. (2016). Situación de multimorbilidad en Colombia 2012-2016. |
dc.relation.references | Almagro, P., Ponce, A., Komal, S., De La Asunción Villaverde, M., Castrillo, C., Grau, G., Simon, L., & De La Sierra, A. (2020). Multimorbidity gender patterns in hospitalized elderly patients. PLoS ONE, 15(1), 1–15. https://doi.org/10.1371/journal.pone.0227252 |
dc.relation.references | Arah, O. A., Westert, G. P., Hurst, J., & Klazinga, N. S. (2006). A conceptual framework for the OECD Health Care Quality Indicators Project. International Journal for Quality in Health Care, 18(SUPPL. 1), 5–13. https://doi.org/10.1093/intqhc/mzl024 |
dc.relation.references | Barabási, A. (2016). Network Science. Cambridge: Cambridge University Press. http://networksciencebook.com/ |
dc.relation.references | Barclay, M., Dixon-Woods, M., & Lyratzopoulos, G. (2019). The problem with composite indicators. BMJ Quality and Safety, 28(4), 338–344. https://doi.org/10.1136/bmjqs-2018-007798 |
dc.relation.references | Barón-Esquivias, G., Gómez-Moreno, S., Sainz-Hidalgo, I., Gómez-Barrado, J. J., Sayago, I., Martín-Santana, A. M., Sánchez-Brotons, J. A., Romero-Rodríguez, R., Fernández-Romero, A., Amo-Fernández, C., & Aguilera-Saborido, A. (2021). Clinical characteristics of patients suffering atrial fibrillation and diabetes mellitus. The attitude of the clinical cardiologist. Medicina Clínica Práctica, 4(2), 100188. https://doi.org/10.1016/j.mcpsp.2020.100188 |
dc.relation.references | Bennett, S., & Peters, D. H. (2015). Assessing National Health Systems: Why and How. Health Systems & Reform, 1(1), 9–17. https://doi.org/10.1080/23288604.2014.997107 |
dc.relation.references | Boersma, P., Black, L. I., & Ward, B. W. (2020). Prevalence of multiple chronic conditions among US adults, 2018. Preventing Chronic Disease, 17, 2–5. https://doi.org/10.5888/PCD17.200130 |
dc.relation.references | Bonita, R., Beaglehole, R., & Kjellstrom, T. (2006). Basic epidemiology. In Word Health Organization. WHO Library. https://doi.org/10.1017/CBO9781139696951.003 |
dc.relation.references | Brunson, J. C., & Laubenbacher, R. C. (2017). Applications of network analysis to routinely collected health care data: a systematic review. Journal of the American Medical Informatics Association, 0(0), 1–13. https://doi.org/10.1093/jamia/ocx052 |
dc.relation.references | Capobianco, E., & Lió, P. (2015). Comorbidity networks: beyond disease correlations. Journal of Complex Networks, 1–14. https://doi.org/10.1093/comnet/cnu048 |
dc.relation.references | Ley 1438 del 2011, Congreso de la Republica - Colombia. |
dc.relation.references | Consejo Privado de Competitividad, & Universidad del Rosario. (2022). Índice Departamental de Competitividad 2022. |
dc.relation.references | DANE. (2020). Proyecciones de población. https://www.dane.gov.co/index.php/estadisticas-por-tema/demografia-y-poblacion/proyecciones-de-poblacion |
dc.relation.references | De La Guardia Gutiérrez, M., & Ruvalcaba, J. (2020). Health and its determinants, health promotion and health education. Journal of Negative & Positive Result, 5(1), 81–90. https://doi.org/10.19230/jonnpr.3215 |
dc.relation.references | Dorogovtsev, S., & Mendes, J. F. (2003). Evolution of Networks: From Biological Nets to the Internet and WWW (Oxford Pre). |
dc.relation.references | Estrada, E. (2011). The structure of complex networks - Theory and Applications (Oxford Uni). |
dc.relation.references | Estrada, E., & Knight, P. (2015). A First Course in Network Theory. In ACM International Conference Proceeding Series (Vols. 13-May-201). Oxford University Press. https://doi.org/10.1145/2757218.2757223 |
dc.relation.references | Feinstein, A. R. (1970). The pre-therapeutic classification of co-morbidity in chronic disease. Journal of Chronic Diseases, 23(7), 455–468. https://doi.org/10.1016/0021-9681(70)90054-8 |
dc.relation.references | Fernández-Niño, J. A., & Bustos-Vázquez, E. (2016). Multimorbidity: Conceptual basis, epidemiological models and measurement challenges. Biomédica, 36(2), 188–203. https://doi.org/10.7705/biomedica.v36i2.2710 |
dc.relation.references | Freeman, L. C. (2004). The Development of Social Network Analysis A study in the sociology of science. In ΣP Empirical Press. |
dc.relation.references | GBD. (2018). Global, regional, and national incidence, prevalence, and years lived with disability for 354 Diseases and Injuries for 195 countries and territories, 1990-2017: A systematic analysis for the Global Burden of Disease Study 2017. The Lancet, 392, 1789–1858. https://doi.org/10.1016/S0140-6736(18)32279-7 |
dc.relation.references | Gerring, J., Thacker, S. C., Enikolopov, R., Arévalo, J., & Maguire, M. (2013). Assessing health system performance: A model-based approach. Social Science and Medicine, 93, 21–28. https://doi.org/10.1016/j.socscimed.2013.06.002 |
dc.relation.references | Glicksberg, B. S., Li, L., Badgeley, M. A., Shameer, K., Kosoy, R., Beckmann, N. D., Ma, M., Ayers, K. L., Pho, N., Hoffman, G. E., Li, S. D., Schadt, E. E., Patel, C. J., Chen, R., & Dudley, J. T. (2016). Comparative analyses of population-scale phenomic data in electronic medical records reveal race-specific disease networks. Bioinformatics, 32, 101–110. https://doi.org/10.1093/bioinformatics/btw282 |
dc.relation.references | Gómez, A. (2015). Clasificación Internacional de Enfermedades (CIE): Descifrando la CIE-10 y esperando la CIE-11. Monitor Estratégico, 7, 66–73. |
dc.relation.references | Guo, M., Yu, Y., Wen, T., Zhang, X., Liu, B., Zhang, J., Zhang, R., Zhang, Y., & Zhou, X. (2019). Analysis of disease comorbidity patterns in a large-scale China population. BMC Medical Genomics, 12(Suppl 12), 1–10. https://doi.org/10.1186/s12920-019-0629-x |
dc.relation.references | Hanauer, D. A., & Ramakrishnan, N. (2012). Modeling temporal relationships in large scale clinical associations. J Am Med Inform Assoc, 1–10. https://doi.org/10.1136/amiajnl-2012-001117 |
dc.relation.references | Hao, T., Wang, Q., Zhao, L., Wu, D., Wang, E., & Sun, J. (2018). Analyzing of Molecular Networks for Human Diseases and Drug Discovery. Current Topics in Medicinal Chemistry, 18(12), 1007–1014. https://doi.org/10.2174/1568026618666180813143408 |
dc.relation.references | Hee, J., Young, K., Wook, D., Hyuk, S., Won, J., Hyun, J., So, M., Heon, E., Hun, K., & Moon, J. (2016). Network analysis of human diseases using Korean nationwide claims data. Journal of Biomedical Informatics, 61, 276–282. https://doi.org/10.1016/j.jbi.2016.05.002 |
dc.relation.references | Hejduková, P., & Kureková, L. (2017). Healthcare systems and performance evaluation: comparison of performance indicators in v4 countries using models of composite indicators. Ekonomika a Management, 20(3), 133–146. https://doi.org/10.15240/tul/001/2017-3-009 |
dc.relation.references | Hernández, B., Reilly, R. B., & Kenny, R. A. (2019). Investigation of multimorbidity and prevalent disease combinations in older Irish adults using network analysis and association rules. Scientific Reports, 9(1), 1–12. https://doi.org/10.1038/s41598-019-51135-7 |
dc.relation.references | Hilarión-Gaitán, L., Díaz-Jiménez, D., Cotes-Cantillo, K., & Castañeda-Orjuela, C. (2019). Desigualdades en salud según régimen de afiliación y eventos notificados al Sistema de Vigilancia (Sivigila) en Colombia, 2015. Biomédica, 39(4), 737–747. https://doi.org/10.7705/biomedica.4453 |
dc.relation.references | Hossain, M. E., Uddin, S., Khan, A., & Moni, M. A. (2020). A framework to understand the progression of cardiovascular disease for type 2 diabetes mellitus patients using a network approach. International Journal of Environmental Research and Public Health, 17(2), 1–17. https://doi.org/10.3390/ijerph17020596 |
dc.relation.references | Huntley, A. L., Johnson, R., Purdy, S., Valderas, J. M., & Salisbury, C. (2012). Measures of Multimorbidity and Morbidity Burden for Use in Primary Care and Community Settings: A Systematic Review and Guide. Annals of Family Medicine, 10(2), 134–141. https://doi.org/10.1370/afm.1363 |
dc.relation.references | Hussain, M. A., Huxley, R. R., & Al Mamun, A. (2015). Multimorbidity prevalence and pattern in Indonesian adults: An exploratory study using national survey data. BMJ Open, 5(12), 1–10. https://doi.org/10.1136/bmjopen-2015-009810 |
dc.relation.references | Jacobs, R., Smith, P., & Goddard, M. (2004). Measuring performance: An examination of composite performance indicators (Issue July). |
dc.relation.references | Jani, B. D., Hanlon, P., Nicholl, B. I., McQueenie, R., Gallacher, K. I., Lee, D., & Mair, F. S. (2019). Relationship between multimorbidity, demographic factors and mortality: Findings from the UK Biobank cohort. BMC Medicine, 17(1), 1–13. https://doi.org/10.1186/s12916-019-1305-x |
dc.relation.references | Jensen, A. B., Moseley, P. L., Oprea, T. I., Ellesøe, S. G., Eriksson, R., Schmock, H., Jensen, P. B., Jensen, L. J., & Brunak, S. (2014). Temporal disease trajectories condensed from population-wide registry data covering 6.2 million patients. Nature Communications, 5(4022), 1–10. https://doi.org/10.1038/ncomms5022 |
dc.relation.references | Jones, I., Cocker, F., Jose, M., Charleston, M., & Neil, A. L. (2022). Methods of analysing patterns of multimorbidity using network analysis: a scoping review. Journal of Public Health (Germany), 0123456789. https://doi.org/10.1007/s10389-021-01685-w |
dc.relation.references | Kalgotra, P., Sharda, R., & Croff, J. M. (2017). Examining health disparities by gender: A multimorbidity network analysis of electronic medical record. International Journal of Medical Informatics, 108(September), 22–28. https://doi.org/10.1016/j.ijmedinf.2017.09.014 |
dc.relation.references | Kalgotra, P., Sharda, R., & Croff, J. M. (2020). Examining multimorbidity differences across racial groups: a network analysis of electronic medical records. Scientific Reports, 10(1), 1–9. https://doi.org/10.1038/s41598-020-70470-8 |
dc.relation.references | Kestenbaum, B. (2009). Measures of Disease Frequency. In Springer Science+Business Media (Ed.), Epidemiology and Biostatistics: An Introduction to Clinical Research (pp. 3–12). https://doi.org/10.1007/978-3-319-27347-1_14 |
dc.relation.references | Khan, A., Uddin, S., & Srinivasan, U. (2018). Comorbidity network for chronic disease: A novel approach to understand type 2 diabetes progression. International Journal of Medical Informatics, 115(April), 1–9. https://doi.org/10.1016/j.ijmedinf.2018.04.001 |
dc.relation.references | Kullback, S., & Leibler, R. A. (1951). On Information and Sufficiency. Ann. Math. Statist., 22(1), 79–86. https://doi.org/10.1214/aoms/1177729694 |
dc.relation.references | Latora, V., Nicosia, V., & Russo, G. (2017). Complex Networks: principles, methods and applications. Cambridge: Cambridge University Press. https://doi.org/10.1017/9781316216002 |
dc.relation.references | Lee, Y., Kim, H., Jeong, H., & Noh, Y. (2020). Patterns of multimorbidity in adults: An association rules analysis using the Korea health panel. International Journal of Environmental Research and Public Health, 17(2618). https://doi.org/10.3390/ijerph17082618 |
dc.relation.references | Leva, F., & Bitonti, D. (2018). Network analysis of comorbidity patterns in heart failure patients using administrative data. Epidemiology Biostatistics and Public Health, 15(2), 1–6. https://doi.org/10.2427/12779 |
dc.relation.references | Lipsitz, L. (2012). Understanding Health Care as a Complex System: The Foundation for Unintended Consequences. Journal of the American Medical Association, 308(3), 243–244. https://doi.org/10.1001/jama.2012.7551.Understanding |
dc.relation.references | Liu, J., Ma, J., Wang, J., Zeng, D. D., Song, H., Wang, L., & Cao, Z. (2016). Comorbidity analysis according to sex and age in hypertension patients in China. International Journal of Medical Sciences, 13(2), 99–107. https://doi.org/10.7150/ijms.13456 |
dc.relation.references | Luke, D. A., & Stamatakis, K. A. (2012). Systems Science Methods in Public Health: Dynamics, Networks, and Agents. Annual Review of Public Health, 33, 357–376. https://doi.org/10.1146/annurev-publhealth-031210-101222 |
dc.relation.references | Ministerio de Salud. (2021). Aseguramiento al sistema general de salud. https://www.minsalud.gov.co/proteccionsocial/Regimensubsidiado/Paginas/aseguramiento-al-sistema-general-salud.aspx |
dc.relation.references | Ministerio de Salud y Protección Social. (2017). Actualización de la Clasificación Única de Procedimientos en Salud (CUPS). |
dc.relation.references | Ministerio de Salud y Protección Social. (2019a). Lineamiento Técnico para el Registro y envío de los datos del Registro Individual de Prestaciones de Salud – RIPS, desde las Instituciones Prestadoras de Servicios de Salud a las EAPB Oficina de Tecnología de la Información y la Comunicación – OTIC. |
dc.relation.references | Ministerio de Salud y Protección Social. (2019b). ¿Qué es SISPRO? SISPRO- Sistema Integrado de Información de La Protección Social. https://www.sispro.gov.co/Pages/Home.aspx |
dc.relation.references | Ministerio de Salud y Protección Social. (2022). Mortalidad en Colombia periodo 2020-2021. |
dc.relation.references | Montgomery, D., & Runger, G. (2003). Applied Statistics and Probability for Engineers. In John Wiley & Sons, Inc. |
dc.relation.references | Newman, M. E. J. (2010). Networks an Introduction (Oxford Uni). |
dc.relation.references | Ng, S. K., Tawiah, R., Sawyer, M., & Scuffham, P. (2018). Patterns of multimorbid health conditions: A systematic review of analytical methods and comparison analysis. International Journal of Epidemiology, 47(5), 1687–1704. https://doi.org/10.1093/ije/dyy134 |
dc.relation.references | Nicholson, K., Almirall, J., & Fortin, M. (2019). The measurement of multimorbidity. Health Psychology, 38(9), 783–790. https://doi.org/10.1037/hea0000739 |
dc.relation.references | Nicholson, K., Makovski, T. T., Griffith, L. E., Raina, P., Stranges, S., & van den Akker, M. (2019). Multimorbidity and comorbidity revisited: refining the concepts for international health research. Journal of Clinical Epidemiology, 105, 142–146. https://doi.org/10.1016/j.jclinepi.2018.09.008 |
dc.relation.references | Nunes, B. P., Thumé, E., & Facchini, L. A. (2015). Multimorbidity in older adults: Magnitude and challenges for the Brazilian health system Chronic Disease epidemiology. BMC Public Health, 15(1), 1–11. https://doi.org/10.1186/s12889-015-2505-8 |
dc.relation.references | OCDE. (2017). Health at a Glance 2017: OECD Indicators. https://doi.org/Please cite this publication as: OECD (2017), Health at a Glance 2017: OECD Indicators, OECD Publishing, Paris. http://dx.doi.org/10.1787/health_glance-2017-en |
dc.relation.references | OMS. (2000). The World Health Report 2000. Health Systems: improving performance. https://doi.org/10.1146/annurev.ecolsys.35.021103.105711 |
dc.relation.references | OMS. (2007). Everybody’s business: strengthening health systems to improve health outcomes: WHO’s framework for action. https://doi.org/10 July 2012 |
dc.relation.references | OMS. (2009). Aplicación del pensamiento sistémico al fortalecimiento de los servicios de salud. 115. |
dc.relation.references | OMS. (2010). Monitoring the building blocks of health systems: a handbook of indicators and their measurement strategies. Who, 1–92. https://doi.org/10.1146/annurev.ecolsys.35.021103.105711 |
dc.relation.references | OMS. (2018a). Global Reference List of 100 Core Health Indicators (plus health-related SDGs). https://doi.org/WHO/HIS/HSI/2015.3 |
dc.relation.references | OMS. (2018b). Sistemas de Salud. Temas de Salud. http://www.who.int/topics/health_systems/es/ |
dc.relation.references | OMS. (2018c). World health statistics 2018: monitoring health for the SDGs, sustainable development goals. |
dc.relation.references | OMS. (2019). Determinantes sociales de la salud. Organización Mundial de La Salud. https://www.who.int/social_determinants/es/ |
dc.relation.references | OPS. (2012). Salud en las Américas: panorama general y perfiles de país. |
dc.relation.references | OPS. (2018). Indicadores de Salud. Aspectos conceptuales y operativos. In Organización Panamericana de la Salud. |
dc.relation.references | Papanicolas, I., & Cylus, J. (2017). The challenges of using cross-national comparisons of efficiency to inform health policy. Eurohealth:Quarterly of the European Observatory on Health Systems an Policies, 23(2), 8–11. |
dc.relation.references | Papanicolas, I., & Smith, P. C. (2013). Health System Performance Comparison. An agenda for policy, information and research. In Mc Graw Hill (Ed.), European Observatory on Health Systems and Policies Series (The Europe). |
dc.relation.references | Peixoto, M. G. M., Musetti, M. A., & Mendonça, M. C. A. (2018). Multivariate analysis techniques applied for the performance measurement of Federal University Hospitals of Brazil. Computers and Industrial Engineering, 126(July), 16–29. https://doi.org/10.1016/j.cie.2018.09.020 |
dc.relation.references | Pengpid, S., & Peltzer, K. (2017). Multimorbidity in chronic conditions: Public primary care patients in four greater mekong countries. International Journal of Environmental Research and Public Health, 14(9). https://doi.org/10.3390/ijerph14091019 |
dc.relation.references | Perić, N., Hofmarcher-Holzhacker, M. M., & Simon, J. (2017). Health system performance assessment landscape at the EU level: A structured synthesis of actors and actions. Archives of Public Health, 75(1), 1–10. https://doi.org/10.1186/s13690-016-0173-5 |
dc.relation.references | Perić, N., Hofmarcher-Holzhacker, M. M., & Simon, J. (2018). Headline indicators for monitoring the performance of health systems: Findings from the european Health Systems_Indicator (euHS_I) survey. Archives of Public Health, 76(1), 1–17. https://doi.org/10.1186/s13690-018-0278-0 |
dc.relation.references | Pettey, W. B. P., Toth, D. J. A., Redd, A., Carter, M. E., Samore, M. H., & Gundlapalli, A. V. (2016). Using network projections to explore co-incidence and context in large clinical datasets: Application to homelessness among U.S. Veterans. Journal of Biomedical Informatics, 61, 203–213. https://doi.org/10.1016/j.jbi.2016.03.023 |
dc.relation.references | Prados-Torres, A., Calderón-Larrañaga, A., Hancco-Saavedra, J., Poblador-Plou, B., & Van Den Akker, M. (2014). Multimorbidity patterns: A systematic review. Journal of Clinical Epidemiology, 67(3), 254–266. https://doi.org/10.1016/j.jclinepi.2013.09.021 |
dc.relation.references | Rentería-Ramos, R., Hurtado-Heredia, R., & Urdinola, P. (2019). Morbi-mortality of the victims of internal conflict and poor population in the Risaralda Province, Colombia. International Journal of Environmental Research and Public Health, 16(1644), 1–8. https://doi.org/10.3390/ijerph16091644 |
dc.relation.references | Reyes, E., González, W., Suárez, B., & Egüez, H. (2011). Caracterización clínico-epidemiológica de los pacientes con artritis reumatoide. Hospitl Universitario Arnaldo Milián Castro. Revista Cubana de Reumatología, 8(1817–5996), 8. |
dc.relation.references | Ricci-Cabello, I., Violán, C., Foguet-Boreu, Q., Mounce, L. T. A., & Valderas, J. M. (2015). Impact of multi-morbidity on quality of healthcare and its implications for health policy, research and clinical practice. A scoping review. European Journal of General Practice, 21(3), 192–202. https://doi.org/10.3109/13814788.2015.1046046 |
dc.relation.references | Rouse, W. B. (2008). Health Care as a Complex Adaptive System: Implications for Design and Management. Organization Science, 38(1), 17. https://doi.org/10.1177/1538574411407082 |
dc.relation.references | Schäfer, I., Kaduszkiewicz, H., Wagner, H. O., Schön, G., Scherer, M., & Van Den Bussche, H. (2014). Reducing complexity: A visualisation of multimorbidity by combining disease clusters and triads. BMC Public Health, 14(1), 1–14. https://doi.org/10.1186/1471-2458-14-1285 |
dc.relation.references | Schwartz, R., & Deber, R. (2016). The performance measurement-management divide in public health. Health Policy, 120(3), 273–280. https://doi.org/10.1016/j.healthpol.2016.02.003 |
dc.relation.references | Secretaria Distrital de Salud de Bogotá. (2019). Documento de Análisis de Situación de Salud con el Modelo de los Determinantes Sociales de Salud para el Distrito Capital. In Secretaría Distrital de Salud de Bogotá. |
dc.relation.references | Shannon, C. E. (1948). A Mathematical Theory of Communication. Bell System Technical Journal, 27(4), 623–656. https://doi.org/10.1002/j.1538-7305.1948.tb00917.x |
dc.relation.references | Sierra, J., & Quintero, J. (2019). Alteraciones tiroideas en diabetes mellitus tipo 2. Revista Latinoamericana de Hipertensión, 14(5), 579–581. |
dc.relation.references | Sturmberg, J., & Lanham, H. J. (2014). Understanding health care delivery as a complex system: Achieving best possible health outcomes for individuals and communities by focusing on interdependencies. Journal of Evaluation in Clinical Practice, 20(6), 1005–1009. https://doi.org/10.1111/jep.12142 |
dc.relation.references | Sun, D., Ahn, H., Lievens, T., & Zeng, W. (2017). Evaluation of the performance of national health systems in 2004-2011: An analysis of 173 countries. PLoS ONE, 12(3), 1–13. https://doi.org/10.1371/journal.pone.0173346 |
dc.relation.references | Trninic, V., Jelaska, I., & Stalec, J. (2012). Appropriateness and limitations of factor analysis methods utilized in psychology and kinesiology: Part I. Fizicka Kultura, 66(2), 77–87. https://doi.org/10.5937/fizkul1202077t |
dc.relation.references | Valderas, J. M., Starfi, B., Sibbald, B., Salisbury, S., & Roland, M. (2009). Defining comorbidity: implications for understanding health and health services. Annals of Family Medicine, 7(4), 357–363. https://doi.org/10.1370/afm.983.Martin |
dc.relation.references | Valdés, E., & Bencosme, N. (2009). Frecuencia de la hipertensión arterial y su relación con algunas variables clínicas en pacientes con diabetes mellitus tipo 2. Revista Cubana de Endocrinología, 20(3), 77–88. |
dc.relation.references | Valente, 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-031816-044528 |
dc.relation.references | Vinjerui, 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-2020-036851 |
dc.relation.references | Wasserman, S., & Faust, K. (1994). Social Network Analysis Methods and applications. Cambridge University Press. |
dc.relation.references | Wei, 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.16310 |
dc.relation.references | Zavala, C., & Florenzano, F. (2015). Diabetes y Corazón. Revista Clínica Las Condes, 26(2), 175–185. https://doi.org/10.1016/j.rmclc.2015.04.006 |
dc.rights.accessrights | info:eu-repo/semantics/openAccess |
dc.subject.decs | Enfermedades individuales |
dc.subject.decs | Individual Diseases |
dc.subject.decs | Encuestas de morbilidad |
dc.subject.decs | Morbidity Surveys |
dc.subject.decs | Indicadoresd emorbimortalidad |
dc.subject.decs | Indicators of Morbidity and Mortality |
dc.subject.proposal | Sistema de Salud |
dc.subject.proposal | Morbilidad |
dc.subject.proposal | Multimorbilidad |
dc.subject.proposal | Análisis de Redes |
dc.subject.proposal | Evaluación del Desempeño |
dc.title.translated | A 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.type.coar | http://purl.org/coar/resource_type/c_db06 |
dc.type.coarversion | http://purl.org/coar/version/c_ab4af688f83e57aa |
dc.type.content | Text |
dc.type.redcol | http://purl.org/redcol/resource_type/TD |
oaire.accessrights | http://purl.org/coar/access_right/c_abf2 |
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