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      Evaluación del desempeño de servicios de Atención Primaria en Salud: experiencia en municipios rurales en Santander, Colombia Translated title: Evaluation of the performance of Primary Health Care Services: experience in rural municipalities in Santander, Colombia

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          Abstract

          Objetivo Evaluar el desempeño de los servicios públicos de salud de seis municipios del departamento de Santander, Colombia, respecto al desarrollo de los atributos de la Atención Primaria en Salud, en el marco de la implementación de esta estrategia en este territorio. Métodos Evaluación rápida de desempeño de los servicios de salud por medio de un diseño comparativo trasversal, basada en metodología propuesta por Starfield. Se entrevistaron usuarios, profesionales y decisores de tres municipios con mayor desarrollo del modelo basado en atención primaria y tres municipios con menor desarrollo, todos ellos de predominio rural. Se calcularon propensity scores para ajustar por diferencias basales de los grupos comparados y mediante un análisis multivariado se determinó el efecto del nivel de desarrollo del modelo sobre el índice global de desempeño de los servicios calificado por los usuarios. Resultados Se encontraron mejores puntuaciones en el índice global de desempeño en usuarios de los municipios con mayor desarrollo del modelo. Los atributos con menores calificaciones de desempeño fueron enfoque familiar, orientación comunitaria y acceso. Conclusiones A pesar que el mayor desarrollo del modelo de atención primaria se relaciona con mejor desempeño de los servicios de salud, los atributos de acceso, enfoque familiar y orientación comunitaria son los menos desarrollados.

          Translated abstract

          Objective Public health services performance in Primary Health Care was evaluated in six municipalities from Santander, Colombia, after the development of a Primary Health Care program at the state level. Methods A cross-sectional, comparative study design was developed using a rapid assessment methodology, designed by Starfield. Patients, professionals and decision-makers were interviewed in three municipalities with higher development of the program and compared with three municipalities with lower development, all six predominantly rural areas. Propensity scores were calculate to equalize basal characteristics of groups being compared and multivariate analysis was used to evaluate the effect of the level of development of the program in the global performance index by patients. Results Higher total scores in the global performance index were found in patients in municipalities with higher development programs. Family-focus, Community orientation and Access were dimensions with lower scores. Higher model development was associated with higher performance index scores by patients. Conclusions In spite of higher primary health care model development was associated with best global performance scores, access, family focus and community orientation are attributes less developed.

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          Most cited references71

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          Contribution of primary care to health systems and health.

          Evidence of the health-promoting influence of primary care has been accumulating ever since researchers have been able to distinguish primary care from other aspects of the health services delivery system. This evidence shows that primary care helps prevent illness and death, regardless of whether the care is characterized by supply of primary care physicians, a relationship with a source of primary care, or the receipt of important features of primary care. The evidence also shows that primary care (in contrast to specialty care) is associated with a more equitable distribution of health in populations, a finding that holds in both cross-national and within-national studies. The means by which primary care improves health have been identified, thus suggesting ways to improve overall health and reduce differences in health across major population subgroups.
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            Invited commentary: propensity scores.

            The propensity score is the conditional probability of exposure to a treatment given observed covariates. In a cohort study, matching or stratifying treated and control subjects on a single variable, the propensity score, tends to balance all of the observed covariates; however, unlike random assignment of treatments, the propensity score may not also balance unobserved covariates. The authors review the uses and limitations of propensity scores and provide a brief outline of associated statistical theory. They also present a new result of using propensity scores in case-cohort studies.
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              Are propensity scores really superior to standard multivariable analysis?

              Clinicians often face difficult decisions despite the lack of evidence from randomized trials. Thus, clinical evidence is often shaped by non-randomized studies exploiting multivariable approaches to limit the extent of confounding. Since their introduction, propensity scores have been used more and more frequently to estimate relevant clinical effects adjusting for established confounders, especially in small datasets. However, debate persists on their real usefulness in comparison to standard multivariable approaches such as logistic regression and Cox proportional hazard analysis. This holds even truer in light of key quantitative developments such as bootstrap and Bayesian methods. This qualitative review aims to provide a concise and practical guide to choose between propensity scores and standard multivariable analysis, emphasizing strengths and weaknesses of both approaches. Copyright © 2011 Elsevier Inc. All rights reserved.
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                Author and article information

                Journal
                rsap
                Revista de Salud Pública
                Rev. salud pública
                Instituto de Salud Publica, Facultad de Medicina - Universidad Nacional de Colombia (Bogotá, DF, Colombia )
                0124-0064
                April 2013
                : 15
                : 2
                : 183-195
                Affiliations
                [01] orgnameUniversidad Industrial de Santander orgdiv1Departamento de Salud Pública Colombia laurovi@ 123456uis.edu.co
                Article
                S0124-00642013000200001 S0124-0064(13)01500200001
                55f7d8c5-2e0e-44d3-82d2-57ca9bfd4162

                This work is licensed under a Creative Commons Attribution 4.0 International License.

                History
                : 19 July 2012
                : 20 June 2012
                : 10 May 2012
                Page count
                Figures: 0, Tables: 0, Equations: 0, References: 27, Pages: 13
                Product

                SciELO Colombia

                Self URI: Texto completo solamente en formato PDF (ES)

                Colombia,health policy,health services evaluation,Primary health care,política de salud,evaluación de servicios de salud,Atención primaria de salud

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