No abstract

No abstract

No abstract

Since 2001, Mexico has been designing, legislating, and implementing a major health-system reform. A key component was the creation of Seguro Popular, which is intended to expand insurance coverage over seven years to uninsured people, nearly half the total population at the start of 2001. The reform included five actions: legislation of entitlement per family affiliated which, with full implementation, will increase public spending on health by 0.8-1.0% of gross domestic product; creation of explicit benefits packages; allocation of monies to decentralised state ministries of health in proportion to number of families affiliated; division of federal resources flowing to states into separate funds for personal and non-personal health services; and creation of a fund to protect families against catastrophic health expenditures. Using the WHO health-systems framework, a wide range of datasets to assess the effect of this reform on different dimensions of the health system was used. Key findings include: affiliation is preferentially reaching the poor and the marginalised communities; federal non-social security expenditure in real per-head terms increased by 38% from 2000 to 2005; equity of public-health expenditure across states improved; Seguro Popular affiliates used more inpatient and outpatient services than uninsured people; effec- ResumenA partir de 2001 se inicia en México un proceso de diseño, legislación e implementación de la Reforma Mexicana de Salud. Un componente clave de ésta fue la creación del Seguro Popular, que pretende extender la cobertura de aseguramiento médico por siete años a la población que no cuenta con seguridad social, la cual constituía en ese momento casi la mitad de la población total. La reforma incluyó cinco acciones: modificar la ley para garantizar el derecho a la protección a la salud para las familias afiliadas, lo cual al ser implantado completamente incrementará el gasto público en salud entre 0.8 y 1.0% del PIB; la creación de un paquete de servicios de salud explícito; la asignación de recursos a secretarías estatales de salud descentralizadas, proporcional al número de familias incorporadas; la división de los recursos federales destinados a los estados en fondos independientes para servicios de salud personales y no personales; así como la creación de un fondo para garantizar recursos cuando se presentan eventos catastróficos en salud. Mediante el uso del marco conceptual de los sistemas de salud de la OMS, se han examinado diversos conjuntos de datos para evaluar el impacto de esta reforma en distintas dimensiones del sistema de salud. Entre los principales hallazgos clave se encuentran que: la afiliación alcanza de manera preferente a Traducción publicada con permiso. La versión original en inglés se encuentra en : Lancet 2006;368:1920-1935 (1) Iniciativa Harvard para la Salud Global,

BackgroundCause-of-death data for many developing countries are not available. Information on deaths in hospital by cause is available in many low- and middle-income countries but is not a representative sample of deaths in the population. We propose a method to estimate population cause-specific mortality fractions (CSMFs) using data already collected in many middle-income and some low-income developing nations, yet rarely used: in-hospital death records.Methods and FindingsFor a given cause of death, a community's hospital deaths are equal to total community deaths multiplied by the proportion of deaths occurring in hospital. If we can estimate the proportion dying in hospital, we can estimate the proportion dying in the population using deaths in hospital. We propose to estimate the proportion of deaths for an age, sex, and cause group that die in hospital from the subset of the population where vital registration systems function or from another population. We evaluated our method using nearly complete vital registration (VR) data from Mexico 1998–2005, which records whether a death occurred in a hospital. In this validation test, we used 45 disease categories. We validated our method in two ways: nationally and between communities. First, we investigated how the method's accuracy changes as we decrease the amount of Mexican VR used to estimate the proportion of each age, sex, and cause group dying in hospital. Decreasing VR data used for this first step from 100% to 9% produces only a 12% maximum relative error between estimated and true CSMFs. Even if Mexico collected full VR information only in its capital city with 9% of its population, our estimation method would produce an average relative error in CSMFs across the 45 causes of just over 10%. Second, we used VR data for the capital zone (Distrito Federal and Estado de Mexico) and estimated CSMFs for the three lowest-development states. Our estimation method gave an average relative error of 20%, 23%, and 31% for Guerrero, Chiapas, and Oaxaca, respectively.ConclusionsWhere accurate International Classification of Diseases (ICD)-coded cause-of-death data are available for deaths in hospital and for VR covering a subset of the population, we demonstrated that population CSMFs can be estimated with low average error. In addition, we showed in the case of Mexico that this method can substantially reduce error from biased hospital data, even when applied to areas with widely different levels of development. For countries with ICD-coded deaths in hospital, this method potentially allows the use of existing data to inform health policy.