Technical Efficiency of Mexico's Public Health System in the Delivery of Obstetric Care, during 2012-2018.

The objective of this study was to evaluate the technical efficiency of Mexico's public health system in the delivery of obstetric care from 2012 to 2018. A multi-stage quantitative study of the public health institutions responsible for 95% of the system's obstetric services was conducted using data envelopment analysis. The efficiency of state-level productive units (decision-making units, or DMUs) was calculated and juxtaposed with the DMUs' maximum (0.82) and minimum (0.22) scores. Using the outcomes of the initial stage, the average technical efficiency of each institution at the national level was estimated and compared. The results were also utilized to estimate and compare the average efficiency of each state-level health system based on economic characteristics (state GDP per capita). Outputs included prenatal visits and deliveries, while inputs comprised gynecologists, exam rooms, and delivery rooms. Institutional efficiency ranged from 0.16 to 0.82, with an average of 0.417. The Ministry of Health (0.82) and the Mexican Social Security Institute (0.747) exhibited the highest efficiency scores, while the remaining institutions (Institute for Social Security and Services for State Workers [ISSSTE]; Mexican Petroleum [PEMEX]; the Secretary of National Defense [SEDENA]; and the Navy [SEMAR]) scored below the health system average. Of the 153 DMUs, 20% surpassed the maximum (0.82) and 40.6% fell below the minimum (0.22). These findings indicate that 80% of DMUs have unused operational capacity that could be utilized to enhance technical efficiency. No relationship was found between efficiency and the GDP of Mexico's 32 politico-administrative divisions. The efficiency gap between institutions (0.66) shows that while some DMUs are saturated (exhibiting high efficiency scores), the majority have unused operational capacity. Leveraging this untapped capacity could address the needs of vulnerable populations facing restricted access due to health system fragmentation.

Neighborhood features and depression in Mexican older adults: A longitudinal analysis based on the study on global AGEing and adult health (SAGE), waves 1 and 2 (2009-2014).

A growing body of literature shows that neighborhood characteristics influence older adults' mental health. Therefore, the aim of this study was to examine the association between structural and social characteristics of the neighborhood, and depression in Mexican older adults. A longitudinal study was conducted based on waves 1 (2009-2010) and 2 (2014) of the Mexican sample from the Study on global AGEing and adult health (SAGE). A street-network buffer around each participant's household was used to define neighborhood, so that built environment and social characteristics were assessed within it. Depression was ascertained by using an algorithm based on the Composite International Diagnostic Interview. In the analysis, multilevel logistic regression models were constructed separately for each built and social environments measurement, adjusted for socioeconomic, demographic and health-related covariates, and stratified by area of residence (urban versus rural). The results showed that a length of space between 15-45 meters restricted to vehicles was significantly associated with a lower risk of depression in older adults from the urban area (OR: 0.44; IC 95% 0.23-0.83) and the protective association appeared to be larger with increasing space with this restriction, although it lacked significance. Contrarily, the built environment measures were not predictive of depression in the rural setting. On the other hand, none of the variables from the social environment had a significant association, although safety appeared to behave as a risk factor in the overall (OR: 1.48; CI 95% 0.96-2.30; p = 0.08) and rural (OR: 3.44; CI 95% 0.95-12.45; p = 0.06) samples, as it reached marginal significance. Research about neighborhood effects on older adults' mental health is an emergent field that has shown that depression might be treated not only from the individual-level, but also from the neighborhood-level. Additionally, further research is needed, especially in low- and middle-income countries, to help guide neighborhood policies.

A Multisite Study of Environmental Correlates of Active Commuting to School in Mexican Children.

BACKGROUND: Mexican children often use active commuting to school (ACS). In order to maintain high levels of ACS it is important to understand correlates of ACS in this population. However, most evidence comes from high-income countries (HICs). We examined multilevel correlates of ACS in children attending public schools in 3 Mexican cities. METHODS: Information on 1191 children (grades 3 to 5) attending 26 schools was retrieved from questionnaires, neighborhood audits, and geographic information systems data. Multilevel logistic modeling was used to explore individual and environmental correlates of ACS at 400-m and 800-m buffers surrounding schools. RESULTS: Individual positive correlates for ACS included age (6-8 years vs 9-11 years, odds ratio [OR] = 1.5; 6-8 years vs ≥12 years: OR = 2.1) and ≥ 6 adults at home (OR = 2.0). At the 400-m buffer, more ACS was associated with lower walkability (OR = 0.87), presence of posted speed limits (< 6% vs > 12%: OR = 0.36) and crossing aids (< 6% vs 6-20%: OR = 0.25; > 20%: OR = 0.26), as well as higher sidewalk availability (< 70% vs > 90%: OR = 4.5). Similar relationships with speed limits and crossing aids were observed at the 800m buffer. CONCLUSIONS: Findings contrast with those reported in HICs, underscoring the importance of considering the local context when developing strategies to promote ACS. Future studies are needed to replicate these relationships and investigate the longitudinal impact of improving active transportation infrastructure and policies.

[Automated geospatial model for health services strategic planning]. / Modelo geoespacial automatizado para la regionalización operativa en planeación de redes de servicios de salud.

OBJECTIVE: To develop an automated model for the operational regionalization needed in the planning of the health service networks proposed by the new Mexican health care model (Modelo Integrador de Servicios de Salud MIDAS). MATERIAL AND METHODS: Using available data for México during 2005 and 2007, a geospatial model was developed to estimate potential catchment areas around health facilities based on access travel time. The results were compared with an operational regionalization (ERO) study manually carried out in Oaxaca with 2005 data. RESULTS: The ERO assigned 48% of villages to health care centers further away than those assigned by the geospatial model, and 23% of these health centers referred patients to more distant hospitals. CONCLUSIONS: The model calculated by this study generated a more efficient regionalization than the ERO model, minimizing travel time to access health services. This model has been adopted by the General Department of Health Planning and Development of the Mexican Ministry of Health for the implementation of the Health Sector Infrastructure Master Plan.

Modelo geoespacial automatizado para la regionalización operativa en planeación de redes de servicios de salud / Automated geospatial model for health services strategic planning

Objetivo. Desarrollar un modelo automatizado de regionalización operativa para la planeación de las redes de servicios de salud propuestas en el Modelo Integrador de Atención a la Salud (MIDAS). Material y métodos. Con información disponible para México en 2005 y 2007 se realizó un modelo geoespacial para estimar el área potencial de influencia alrededor de cada unidad de atención médica, con base en el menor tiempo de viaje. Los resultados se compararon con un Estudio de Regionalización Operativa (ERO) para Oaxaca llevado a cabo en 2005. Resultados. Comparado con el modelo geoespacial, el ERO asignó 48 por ciento de las localidades a centros de salud más lejanos y 23 por ciento de los centros de salud a hospitales más lejanos. Conclusiones. El modelo calculado en este estudio generó una regionalización más eficiente que el ERO de Oaxaca, minimizando el tiempo de viaje para el acceso a los servicios de salud. Este modelo ha sido adoptado por la Dirección General de Planeación y Desarrollo en Salud para la instrumentación del Plan Maestro Sectorial de Recursos para la Atención de la Salud.

Objective. To develop an automated model for the operational regionalization needed in the planning of the health service networks proposed by the new Mexican health care model (Modelo Integrador de Servicios de Salud MIDAS). Material and Methods. Using available data for México during 2005 and 2007, a geospatial model was developed to estimate potential catchment areas around health facilities based on access travel time. The results were compared with an operational regionalization (ERO) study manually carried out in Oaxaca with 2005 data. Results. The ERO assigned 48 percent of villages to health care centers further away than those assigned by the geospatial model, and 23 percent of these health centers referred patients to more distant hospitals. Conclusions. The model calculated by this study generated a more efficient regionalization than the ERO model, minimizing travel time to access health services. This model has been adopted by the General Department of Health Planning and Development of the Mexican Ministry of Health for the implementation of the Health Sector Infrastructure Master Plan.