Applicability of machine learning algorithm to predict the therapeutic intervention success in Brazilian smokers.

Smoking cessation is an important public health policy worldwide. However, as far as we know, there is a lack of screening of variables related to the success of therapeutic intervention (STI) in Brazilian smokers by machine learning (ML) algorithms. To address this gap in the literature, we evaluated the ability of eight ML algorithms to correctly predict the STI in Brazilian smokers who were treated at a smoking cessation program in Brazil between 2006 and 2017. The dataset was composed of 12 variables and the efficacies of the algorithms were measured by accuracy, sensitivity, specificity, positive predictive value (PPV) and area under the receiver operating characteristic curve. We plotted a decision tree flowchart and also measured the odds ratio (OR) between each independent variable and the outcome, and the importance of the variable for the best model based on PPV. The mean global values for the metrics described above were, respectively, 0.675±0.028, 0.803±0.078, 0.485±0.146, 0.705±0.035 and 0.680±0.033. Supporting vector machines performed the best algorithm with a PPV of 0.726±0.031. Smoking cessation drug use was the roof of decision tree with OR of 4.42 and importance of variable of 100.00. Increase in the number of relapses also promoted a positive outcome, while higher consumption of cigarettes resulted in the opposite. In summary, the best model predicted 72.6% of positive outcomes correctly. Smoking cessation drug use and higher number of relapses contributed to quit smoking, while higher consumption of cigarettes showed the opposite effect. There are important strategies to reduce the number of smokers and increase STI by increasing services and drug treatment for smokers.

Correction: Applicability of machine learning technique in the screening of patients with mild traumatic brain injury.

[This corrects the article DOI: 10.1371/journal.pone.0290721.].

Machine learning models to predict traumatic brain injury outcomes in Tanzania: Using delays to emergency care as predictors.

Constraints to emergency department resources may prevent the timely provision of care following a patient's arrival to the hospital. In-hospital delays may adversely affect health outcomes, particularly among trauma patients who require prompt management. Prognostic models can help optimize resource allocation thereby reducing in-hospital delays and improving trauma outcomes. The objective of this study was to investigate the predictive value of delays to emergency care in machine learning based traumatic brain injury (TBI) prognostic models. Our data source was a TBI registry from Kilimanjaro Christian Medical Centre Emergency Department in Moshi, Tanzania. We created twelve unique variables representing delays to emergency care and included them in eight different machine learning based TBI prognostic models that predict in-hospital outcome. Model performance was compared using the area under the receiver operating characteristic curve (AUC). Inclusion of our twelve time to care variables improved predictability in each of our eight prognostic models. Our Bayesian generalized linear model produced the largest AUC, with a value of 89.5 (95% CI: 88.8, 90.3). Time to care variables were among the most important predictors of in-hospital outcome in our best three performing models. In low-resource settings where delays to care are highly prevalent and contribute to high mortality rates, incorporation of care delays into prediction models that support clinical decision making may benefit both emergency medicine physicians and trauma patients by improving prognostication performance.

Applicability of machine learning technique in the screening of patients with mild traumatic brain injury.

Even though the demand of head computed tomography (CT) in patients with mild traumatic brain injury (TBI) has progressively increased worldwide, only a small number of individuals have intracranial lesions that require neurosurgical intervention. As such, this study aims to evaluate the applicability of a machine learning (ML) technique in the screening of patients with mild TBI in the Regional University Hospital of Maringá, Paraná state, Brazil. This is an observational, descriptive, cross-sectional, and retrospective study using ML technique to develop a protocol that predicts which patients with an initial diagnosis of mild TBI should be recommended for a head CT. Among the tested models, he linear extreme gradient boosting was the best algorithm, with the highest sensitivity (0.70 ± 0.06). Our predictive model can assist in the screening of mild TBI patients, assisting health professionals to manage the resource utilization, and improve the quality and safety of patient care.

Antivenom access impacts severity of Brazilian snakebite envenoming: A geographic information system analysis.

BACKGROUND: Snakebite envenoming (SBE) is a neglected tropical disease capable of causing both significant disability and death. The burden of SBE is especially high in low- and middle-income countries. The aim of this study was to perform a geospatial analysis evaluating the association of sociodemographics and access to care indicators on moderate and severe cases of SBE in Brazil. METHODS: We conducted an ecological, cross-sectional study of SBE in Brazil from 2014 to 2019 using the open access National System Identification of Notifiable Diseases (SINAN) database. We then collected a set of indicators from the Brazil Census of 2010 and performed a Principal Component Analysis to create variables related to health, economics, occupation, education, infrastructure, and access to care. Next, a descriptive and exploratory spatial analysis was conducted to evaluate the geospatial association of moderate and severe events. These variables related to events were evaluated using Geographically Weighted Poisson Regression. T-values were plotted in choropleth maps and considered statistically significant when values were <-1.96 or >+1.96. RESULTS: We found that the North region had the highest number of SBE cases by population (47.83/100,000), death rates (0.18/100,000), moderate and severe rates (22.96/100,000), and proportion of cases that took more than three hours to reach healthcare assistance (44.11%). The Northeast and Midwest had the next poorest indicators. Life expectancy, young population structure, inequality, electricity, occupation, and more than three hours to reach healthcare were positively associated with greater cases of moderate and severe events, while income, illiteracy, sanitation, and access to care were negatively associated. The remaining indicators showed a positive association in some areas of the country and a negative association in other areas. CONCLUSION: Regional disparities in SBE incidence and rates of poor outcomes exist in Brazil, with the North region disproportionately affected. Multiple indicators were associated with rates of moderate and severe events, such as sociodemographic and health care indicators. Any approach to improving snakebite care must work to ensure the timeliness of antivenom administration.

The covid-19 pandemic and hospital morbidity due to mental and behavioral disorders in Brazil: an interrupted time series analysis, from January 2008 to July 2021.

OBJECTIVE: to analyze records of hospitalizations due to mental and behavioral disorders before and after the beginning of the covid-19 pandemic in Brazil, from January 2008 to July 2021. METHODS: this was a descriptive ecological interrupted time series study, using secondary data retrieved from the Brazilian National Health System Hospital Information System; a time series analysis of hospitalizations was conducted based on a population-weighted Poisson regression model; relative risk (RR) and respective 95% confidence intervals (95%CI) were calculated. RESULTS: we identified 6,329,088 hospitalizations due to mental and behavioral disorders; hospitalization rates showed an 8% decrease (RR = 0.92; 95%CI 0.91;0.92) after the start of the pandemic, compared to the pre-pandemic period. CONCLUSION: the pandemic changed the trend of hospitalizations due to mental and behavioral disorders in Brazil; the drop observed in the period is evidence that the pandemic affected the mental health care network.

River dataset as a potential fluvial transportation network for healthcare access in the Amazon region.

Remote areas, such as the Amazon Forest, face unique geographical challenges of transportation-based access to health services. As transportation to healthcare in most of the Amazon Forest is only possible by rivers routes, any travel time and travel distance estimation is limited by the lack of data sources containing rivers as potential transportation routes. Therefore, we developed an approach to convert the geographical representation of roads and rivers in the Amazon into a combined, interoperable, and reusable dataset. To build the dataset, we processed and combined data from three data sources: OpenStreetMap, HydroSHEDS, and GloRiC. The resulting dataset can consider distance metrics using the combination of streets and rivers as a transportation route network for the Amazon Forest. The created dataset followed the guidelines and attributes defined by OpenStreetMap to leverage its reusability and interoperability possibilities. This new data source can be used by policymakers, health authorities, and researchers to perform time-to-care analysis in the International Amazon region.

Using the Pan American Health Organization Digital Conversational Agent to Educate the Public on Alcohol Use and Health: Preliminary Analysis.

BACKGROUND: There is widespread misinformation about the effects of alcohol consumption on health, which was amplified during the COVID-19 pandemic through social media and internet channels. Chatbots and conversational agents became an important piece of the World Health Organization (WHO) response during the COVID-19 pandemic to quickly disseminate evidence-based information related to COVID-19 and tobacco to the public. The Pan American Health Organization (PAHO) seized the opportunity to develop a conversational agent to talk about alcohol-related topics and therefore complement traditional forms of health education that have been promoted in the past. OBJECTIVE: This study aimed to develop and deploy a digital conversational agent to interact with an unlimited number of users anonymously, 24 hours a day, about alcohol topics, including ways to reduce risks from drinking, that is accessible in several languages, at no cost, and through various devices. METHODS: The content development was based on the latest scientific evidence on the impacts of alcohol on health, social norms about drinking, and data from the WHO and PAHO. The agent itself was developed through a nonexclusive license agreement with a private company (Soul Machines) and included Google Digital Flow ES as the natural language processing software and Amazon Web Services for cloud services. Another company was contracted to program all the conversations, following the technical advice of PAHO staff. RESULTS: The conversational agent was named Pahola, and it was deployed on November 19, 2021, through the PAHO website after a launch event with high publicity. No identifiable data were used and all interactions were anonymous, and therefore, this was not considered research with human subjects. Pahola speaks in English, Spanish, and Portuguese and interacts anonymously with a potentially infinite number of users through various digital devices. Users were required to accept the terms and conditions to enable access to their camera and microphone to interact with Pahola. Pahola attracted good attention from the media and reached 1.6 million people, leading to 236,000 clicks on its landing page, mostly through mobile devices. Only 1532 users had a conversation after clicking to talk to Pahola. The average time users spent talking to Pahola was 5 minutes. Major dropouts were observed in different steps of the conversation flow. Some questions asked by users were not anticipated during programming and could not be answered. CONCLUSIONS: Our findings showed several limitations to using a conversational agent for alcohol education to the general public. Improvements are needed to expand the content to make it more meaningful and engaging to the public. The potential of chatbots to educate the public on alcohol-related topics seems enormous but requires a long-term investment of resources and research to be useful and reach many more people.

Snakebite envenoming in Brazilian children: clinical aspects, management and outcomes.

Snakebite envenoming is currently considered a neglected tropical disease, which affects over 5 million people worldwide, and causes almost 150 000 deaths every year, as well as severe injuries, amputations and other sequelae. Snakebite envenoming in children, although proportionally less frequent, is generally more severe, and represents an important challenge for pediatric medicine, since they often result in worse outcomes. In Brazil, given its ecological, geographic and socioeconomic characteristics, snakebites are considered an important health problem, presenting approximately 30 000 victims per year, approximately 15% of them in children. Even with low snakebite incidence, children tend to have higher snakebite severity and complications due to the small body mass and same venom volume inoculated in comparison to adults, even though, due to the lack of epidemiological information about pediatric snakebites and induced injuries, it is difficult to measure the treatment effectiveness, outcomes and quality of emergency medical services for snakebites in children. In this review, we report how Brazilian children are affected by snakebites, describing the characteristics of this affected population, clinical aspects, management, outcomes and main challenges.

River dataset as a potential fluvial transportation network for healthcare access in the amazon region

Remote areas, such as the Amazon Forest, face unique geographical challenges of transportation-based access to health services. As transportation to healthcare in most of the Amazon Forest is only possible by rivers routes, any travel time and travel distance estimation is limited by the lack of data sources containing rivers as potential transportation routes. Therefore, we developed an approach to convert the geographical representation of roads and rivers in the Amazon into a combined, interoperable, and reusable dataset. To build the dataset, we processed and combined data from three data sources: OpenStreetMap, HydroSHEDS, and GloRiC. The resulting dataset can consider distance metrics using the combination of streets and rivers as a transportation route network for the Amazon Forest. The created dataset followed the guidelines and attributes defined by OpenStreetMap to leverage its reusability and interoperability possibilities. This new data source can be used by policymakers, health authorities, and researchers to perform time-to-care analysis in the International Amazon region.

A pandemia de covid-19 e a morbidade hospitalar por transtorno mental e comportamental no Brasil: uma análise de série temporal interrompida, janeiro de 2008 a julho de 2021 / La pandemia de covid-19 y la morbilidad hospitalaria por trastornos mentales y del comportamiento en Brasil: un análisis de series temporales interrompidas, de enero de 2008 a julio de 2021 / The covid-19 pandemic and hospital morbidity due to mental and behavioral disorders in Brazil: an interrupted time series analysis, from January 2008 to July 2021

Objective: to analyze records of hospitalizations due to mental and behavioral disorders before and after the beginning of the covid-19 pandemic in Brazil, from January 2008 to July 2021. Methods: this was a descriptive ecological interrupted time series study, using secondary data retrieved from the Brazilian National Health System Hospital Information System; a time series analysis of hospitalizations was conducted based on a population-weighted Poisson regression model; relative risk (RR) and respective 95% confidence intervals (95%CI) were calculated. Results: we identified 6,329,088 hospitalizations due to mental and behavioral disorders; hospitalization rates showed an 8% decrease (RR = 0.92; 95%CI 0.91;0.92) after the start of the pandemic, compared to the pre-pandemic period. Conclusion: the pandemic changed the trend of hospitalizations due to mental and behavioral disorders in Brazil; the drop observed in the period is evidence that the pandemic affected the mental health care network.

Objetivo: analizar las hospitalizaciones por trastornos mentales y del comportamiento antes y después del inicio de la pandemia de covid-19 en Brasil, desde enero 2008 hasta julio 2021. Método: estudio ecológico descriptivo de series temporales interrumpidas, con datos registrados en el Sistema de Informações Hospitalares del Sistema Único de Saúde; se realizó un análisis de series temporales de hospitalizaciones basado en modelo de regresión de Poisson, ponderado por la población; calculado el riesgo relativo (RR), con intervalo de confianza del (IC95%). Resultados: se identificaron 6.329.088 hospitalizaciones por trastornos mentales y del comportamiento; las tasas de hospitalización mostraron disminución del 8% (RR = 0,92; IC95% 0,91;0,92) tras el inicio de la pandemia, en relación con el periodo prepandémico. Conclusión: la pandemia cambió la tendencia de hospitalizaciones por trastornos mentales y del comportamiento en Brasil; la caída observada en el período evidencia que la pandemia afectó la cadena asistencial estructurada para la salud mental.

Objetivo: analisar as internações por transtorno mental e comportamental, antes e após o início da pandemia de covid-19 no Brasil, de janeiro de 2008 a julho de 2021. Métodos: estudo ecológico descritivo de série temporal interrompida, com dados registrados no Sistema de Informações Hospitalares do Sistema Único de Saúde (SIH/SUS); realizada análise da série temporal das internações baseada em um modelo de regressão de Poisson, ponderado pela população; calculado o risco relativo (RR), com intervalo de confiança de 95% (IC95%). Resultados: foram identificadas 6.329.088 internações por transtornos mentais e comportamentais; as taxas de internação apresentaram um decréscimo de 8% (RR = 0,92; IC95% 0,91;0,92) após o início da pandemia, em relação ao período pré-pandemia. Conclusão: a pandemia modificou a tendência das internações por transtornos mentais e comportamentais no Brasil; a queda observada no período é evidência de que a pandemia afetou a cadeia de cuidado estruturada para saúde mental.

Bolsa Família Program and deaths from oral cancer in Brazil: an ecological study.

Objective: To assess the effect of coverage of the Bolsa Família Program (BFP) on oral cancer mortality rates in Brazil between 2005 and 2017, adjusting for health care coverage and socioeconomic characteristics of the Brazilian federative units. Methods: This is an ecological study using annual data (2005-2017) from all the Brazilian federative units. The dependent variable for this study was the oral cancer mortality rate, standardized by gender and age using the direct standardization technique. BFP coverage was the main independent variable, calculated as the ratio of the number of BFP beneficiaries to those families that should potentially be entitled to this conditional cash transfer. Socioeconomic background and health care coverage were covariables. Choropleth maps were drawn, and space-time cube analysis was used to assess changes in the spatiotemporal distribution of BFP and oral cancer mortality rates. Mixed-effects linear regression analysis estimated the coefficients (ß) and 95% confidence intervals (CI) for the association between BFP coverage and oral cancer mortality rates. Results: BFP coverage trends increased and oral cancer mortality rate trends stabilized in Brazilian federative units, except for Maranhão, Goiás, and Minas Gerais, where the oral cancer mortality rates have increased. In the adjusted model, greater BFP coverage was associated with lower oral cancer mortality rates (ß -2.10; 95% CI [-3.291, -0.919]). Conclusions: Egalitarian strategies such as BFP can reduce the oral cancer mortality rate. We recommend the follow-up of families benefiting from conditional cash transfer program by oral health teams to reduce the oral cancer mortality rate.

Bolsa Família Program and deaths from oral cancer in Brazil: an ecological study

[ABSTRACT]. Objective. To assess the effect of coverage of the Bolsa Família Program (BFP) on oral cancer mortality rates in Brazil between 2005 and 2017, adjusting for health care coverage and socioeconomic characteristics of the Brazilian federative units. Methods. This is an ecological study using annual data (2005–2017) from all the Brazilian federative units. The dependent variable for this study was the oral cancer mortality rate, standardized by gender and age using the direct standardization technique. BFP coverage was the main independent variable, calculated as the ratio of the number of BFP beneficiaries to those families that should potentially be entitled to this conditional cash transfer. Socioeconomic background and health care coverage were covariables. Choropleth maps were drawn, and space-time cube analysis was used to assess changes in the spatiotemporal distribution of BFP and oral cancer mortality rates. Mixed-effects linear regression analysis estimated the coefficients (β) and 95% confidence intervals (CI) for the association between BFP coverage and oral cancer mortality rates. Results. BFP coverage trends increased and oral cancer mortality rate trends stabilized in Brazilian federative units, except for Maranhão, Goiás, and Minas Gerais, where the oral cancer mortality rates have increased. In the adjusted model, greater BFP coverage was associated with lower oral cancer mortality rates (β –2.10; 95% CI [–3.291, –0.919]). Conclusions. Egalitarian strategies such as BFP can reduce the oral cancer mortality rate. We recommend the follow-up of families benefiting from conditional cash transfer program by oral health teams to reduce the oral cancer mortality rate.

[RESUMEN]. Objetivo. Evaluar el efecto de la cobertura del Programa Bolsa Família (BFP) en las tasas de mortalidad por cáncer de la cavidad bucal en Brasil entre el 2005 y el 2017, ajustadas por cobertura de atención de salud y características socioeconómicas de las unidades federativas brasileñas. Métodos. Este es un estudio ecológico con datos anuales (2005-2017) de todas las unidades federativas brasileñas. La variable dependiente de este estudio fue la tasa de mortalidad por cáncer de la cavidad bucal, estandarizada por sexo y edad mediante la técnica de estandarización directa. La cobertura del BFP fue la principal variable independiente, calculada como la relación entre el número de beneficiarios del BFP y las familias que podrían tener el derecho a recibir esta transferencia monetaria condicionada. Los antecedentes socioeconómicos y la cobertura de atención de salud fueron covariables. Se trazaron mapas coropléticos y se realizó un análisis con cubos espaciotemporales para evaluar los cambios en la distribución espaciotemporal del BFP y las tasas de mortalidad por cáncer de la cavidad bucal. El análisis de regresión lineal de efectos mixtos calculó los coeficientes (β) y los intervalos de confianza (IC) del 95% para la relación entre la cobertura del BFP y las tasas de mortalidad por cáncer de la cavidad bucal. Resultados. Las tendencias de cobertura del BFP aumentaron y las tendencias de la tasa de mortalidad por cáncer de la cavidad bucal se estabilizaron en las unidades federativas brasileñas, excepto en Maranhão, Goiás y Minas Gerais, donde estas tasas aumentaron. En el modelo ajustado, una mayor cobertura del BFP se asoció con tasas más bajas de mortalidad por cáncer de la cavidad bucal (β –2,10; IC del 95% [–3,291, –0,919]). Conclusiones. Las estrategias igualitarias como el BFP pueden reducir la tasa de mortalidad por cáncer de la cavidad bucal. Recomendamos el seguimiento por parte de los equipos de salud bucodental de las familias que se benefician del programa de transferencias monetarias condicionadas para reducir la tasa de mortali- dad por cáncer de la cavidad bucal.

[RESUMO]. Objetivo. Avaliar o efeito da cobertura do Programa Bolsa Família (PBF) sobre as taxas de mortalidade por câncer bucal no Brasil entre 2005 e 2017, com ajuste para a cobertura de saúde e as características socio- econômicas das unidades federativas brasileiras. Métodos. Este é um estudo ecológico com base em dados anuais (2005-2017) de todas as unidades feder- ativas brasileiras. A variável dependente foi a taxa de mortalidade por câncer bucal, padronizada por sexo e idade pela técnica de padronização direta. A cobertura do PBF foi a principal variável independente, cal- culada como a razão entre o número de beneficiários do PBF e de famílias que deveriam ter direito a essa transferência condicionada de renda. O contexto socioeconômico e a cobertura de saúde foram covariáveis. Elaboraram-se mapas coropléticos e usou-se a análise de cubo espaço-temporal para avaliar variações da distribuição espaço-temporal do PBF e das taxas de mortalidade por câncer bucal. A análise por regressão linear de efeitos mistos estimou os coeficientes (β) e intervalos de confiança (IC) de 95% da associação entre cobertura do PBF e taxas de mortalidade por câncer bucal. Resultados. Houve aumento da tendência de cobertura do PBF e estabilização da tendência da taxa de mortalidade por câncer bucal nas unidades federativas brasileiras, com exceção dos estados de Maranhão, Goiás e Minas Gerais, onde as taxas de mortalidade por câncer bucal aumentaram. No modelo ajustado, a maior cobertura do PBF foi associada a menores taxas de mortalidade por câncer bucal (β -2,10; IC 95% [-3,291, -0,919]). Conclusões. Estratégias igualitárias como o PBF podem reduzir a taxa de mortalidade por câncer bucal. Recomendamos o acompanhamento das famílias beneficiadas por programas de transferência condicionada de renda por equipes de saúde bucal para reduzir a taxa de mortalidade por esse câncer.

Impact of socioeconomic factors and health determinants on preterm birth in Brazil: a register-based study.

BACKGROUND: More than 15 million children are born preterm annually. While preterm survival rates have increased in high-income countries. Low- and middle-income countries, like Brazil, continue to battle high neonatal mortality rates due to a lack of adequate postnatal care. Globally, neonatal mortality is higher for preterm infants compared to those born at term. Our study aims to map and analyze the spatial, socioeconomic, and health coverage determinants related to preterm birth in Brazil in order to understand how spatial variations in demographics and access to primary care may affect preterm birth occurrences.  METHODS: Using publicly available national-level data from the Brazilian health system for 2008-2017, we conducted an ecological study to visualize the spatial distributions of preterm birth along with socioeconomic status, the structure of health services, and primary care work process, each consisting of multiple variables reduced via principal component analysis. Regression models were created to determine predictive effects of numeric and spatial variation of these scores on preterm birth rates. RESULTS: In Brazil, preterm birth rates increased from 2008-2017, with small and rural municipalities frequently exhibiting higher rates than urban areas. Scores in socioeconomic status and work process were significant predictors of preterm birth rates, without taking into account spatial adjustment, with more positive scores in socioeconomic status predicting higher preterm birth rates (coefficient 0.001145) and higher scores in work process predicting lower preterm birth rates (coefficient -0.002416). Geographically weighted regression showed socioeconomic status to be a more significant predictor in the North, with the work process indicators being most significant in the Northeast. CONCLUSIONS: Results support that primary care work process indicators are more significant in estimating preterm birth rates than physical structures available for care. These results emphasize the importance of ensuring the presence of the minimum human resources needed, especially in the most deprived areas of Brazil. The association between social determinants of health and preterm birth rates raises questions regarding the importance of policies dedicated to foster equity in the accessibility of healthcare services, and improve income as protective proxies for preterm birth.

The development of the Pan American Health Organization digital health specialist on alcohol use.

Introduction: On 19 November 2021 the Pan American Health Organization (PAHO) developed and deployed the first-ever digital health worker dedicated to alcohol-related topics, named Pahola. This paper describes this developmental process and the first results of its uptake and interactions with the public. Methods: PAHO secured a non-exclusive worldwide license with a technology company to use their Human OS ecosystem, which enables human-like interactions between digital people and users via an application. Google Digital flow ES was used to develop the conversations of Pahola on topics related to alcohol and health, screening of alcohol risk using the AUDIT and providing a quit/cut back plan to users, along with additional treatment services and resources in each country of the Americas. A communication campaign was also implemented from launching date until 31 December 2021. Results: Pahola attracted good attention from the media, and potentially reached 1.6 million people, leading to 236,000 sessions on its landing page, mostly through mobile devices. The average time people effectively spent talking to Pahola was five minutes. Major dropouts were observed in different steps of the conversation flow. Discussion: Pahola was quickly able to connect to a large worldwide population with reliable alcohol information. It could potentially increase the delivery of SBI and improve alcohol health literacy. However, its preliminary results pointed to much needed changes to its corpus and on its accessibility, which are being currently implemented.

[Factors associated with hospitalizations for primary care-sensitive conditions in Brazil: an ecological studyFactores asociados a las hospitalizaciones infantiles por afecciones que podrían tratarse en la atención primaria en Brasil: estudio ecológico]. / Fatores associados às internações infantis por condições sensíveis à atenção primária no Brasil: estudo ecológico.

Objective: To investigate whether structural aspects of primary care units (PCUs) and the work processes of primary care teams are associated with the rate of hospitalizations for primary care-sensitive conditions (HPCSC) in children younger than 5 years of age in Brazil. Method: For this longitudinal ecological study, secondary data were obtained from the Brazilian Hospital Information System and from three cycles of the National Program for Access and Quality Improvement in Primary Care (PMAQ-AB) (2012, 2014, 2017/2018). The analysis included 42 916 PCUs. A multilevel random intercept model with fixed slope was used. In the first level, the outcome (HPCSC rates) and explanatory variables (structure and process indicators) aggregated by PCU were analyzed. Social determinants (represented by a stratification criterion combining municipality population and health care management indicators) were entered in the second level. The t test with Bonferroni correction was used to compare indicator means between regions, and multilevel linear regression was used to estimate the correlation coefficients. Results: The HPCSC rate in children younger than 5 years was 62.78/100 thousand population per estimated PCU coverage area. A direct association with the outcome was observed for: participation in one or more PMAQ-AB cycles; team planning; special hours; dedicated pediatric care area; and availability of vaccines. Equipment, materials, supplies, and being a small or medium-size municipality were inversely associated with HPCSC. Conclusions: HPCSC rates in children below 5 years of age may potentially be reduced through improvements in PCU structure and process indicators and in municipal social determinants.

Objetivo: Determinar la asociación de la estructura de las unidades básicas de salud (UBS) y del proceso de trabajo de los equipos de atención primaria con los determinantes sociales y las tasas de hospitalización por afecciones que podrían tratarse en la atención primaria en menores de 5 años en Brasil. Métodos: Estudio longitudinal ecológico, con datos secundarios del Sistema de Informaciones Hospitalarias y los tres ciclos del Programa Nacional de Mejora del Acceso y de la Calidad de la Atención Básica (PMAQ-AB) (2012, 2014, 2017-2018). Se analizaron 42.916 UBS. Se aplicó un modelo multinivel con pendiente fija e intercepción aleatoria. En el primer nivel, se analizaron el desenlace (tasas de hospitalización por afecciones que podrían tratarse en los servicios de atención primaria) y las variables explicativas (indicadores estructurales y procedimentales) consolidados por UBS. En el segundo nivel, se incluyeron determinantes sociales municipales (representados por un criterio de estratificación que combina el tamaño del municipio con indicadores que influyen en la gestión de salud). Se utilizó la prueba de la t con la corrección de Bonferroni para comparar las medias de los indicadores entre las regiones y la regresión lineal multinivel para estimar los coeficientes de correlación. Resultados: La tasa de hospitalización por afecciones que podrían tratarse en los servicios de atención primaria en menores de 5 años fue de 62,78/100 mil habitantes por área estimada de cobertura de UBS. Los siguientes factores presentaron una asociación directa con el desenlace: participación en uno o más ciclos del PMAQ-AB; planificación del equipo; horario especial; dependencias de atención infantil en la unidad; y disponibilidad de vacunas. La variable relativa a equipos, materiales e insumos y la clasificación como municipio pequeño o mediano se asociaron inversamente con las hospitalizaciones por afecciones que podrían tratarse en los servicios de atención primaria. Conclusiones: Las hospitalizaciones de menores de 5 años por afecciones que podrían tratarse en los servicios de atención primaria pueden reducirse mejorando los indicadores estructurales y procedimentales de las UBS y los determinantes sociales municipales.

Fatores associados às internações infantis por condições sensíveis à atenção primária no Brasil: estudo ecológico

[RESUMO]. Objetivo. Identificar a associação da estrutura das unidades básicas de saúde (UBS) e do processo de trabalho das equipes de atenção primária com determinantes sociais e taxas de internações por condições sensíveis à atenção primária (ICSAP) em menores de 5 anos no Brasil. Métodos. Estudo longitudinal ecológico, com dados secundários do Sistema de Informações Hospitalares e dos três ciclos do Programa Nacional de Melhoria do Acesso e da Qualidade da Atenção Básica (PMAQ-AB) (2012, 2014, 2017/2018). Foram analisadas 42 916 UBS. Foi realizada modelagem multinível com angulação fixa e intercepto aleatório. No primeiro nível, foram analisados o desfecho (taxas de ICSAP) e as variáveis explicativas (indicadores estruturais e processuais), agregados por UBS. No segundo nível, foram incluídos determinantes sociais municipais (representados por critério de estratificação que combina o porte do muni- cípio com indicadores que influenciam a gestão de saúde). Utilizou-se o teste t com correção de Bonferroni para comparar as médias dos indicadores entre as regiões, e a regressão linear multinível para estimar os coeficientes de correlação. Resultados. A taxa de ICSAP em menores de 5 anos foi de 62,78/100 mil habitantes por área estimada de cobertura de UBS. Apresentaram associação direta com o desfecho: participação em um ou mais ciclos do PMAQ-AB; planejamento da equipe; horário especial; dependências para atenção infantil na unidade; e dis- ponibilidade de vacinas. A variável equipamentos, materiais e insumos e a classificação como município de porte pequeno ou médio associaram-se inversamente às ICSAP. Conclusões. As ICSAP em menores de 5 anos podem ser potencialmente reduzidas pela melhoria dos indi- cadores estruturais e processuais das UBS e dos determinantes sociais municipais.

[ABSTRACT]. Objective. To investigate whether structural aspects of primary care units (PCUs) and the work processes of primary care teams are associated with the rate of hospitalizations for primary care-sensitive conditions (HPCSC) in children younger than 5 years of age in Brazil. Method. For this longitudinal ecological study, secondary data were obtained from the Brazilian Hospital Infor- mation System and from three cycles of the National Program for Access and Quality Improvement in Primary Care (PMAQ-AB) (2012, 2014, 2017/2018). The analysis included 42 916 PCUs. A multilevel random intercept model with fixed slope was used. In the first level, the outcome (HPCSC rates) and explanatory variables (structure and process indicators) aggregated by PCU were analyzed. Social determinants (represented by a stratification criterion combining municipality population and health care management indicators) were ente- red in the second level. The t test with Bonferroni correction was used to compare indicator means between regions, and multilevel linear regression was used to estimate the correlation coefficients. Results. The HPCSC rate in children younger than 5 years was 62.78/100 thousand population per estimated PCU coverage area. A direct association with the outcome was observed for: participation in one or more PMAQ-AB cycles; team planning; special hours; dedicated pediatric care area; and availability of vaccines. Equipment, materials, supplies, and being a small or medium-size municipality were inversely associated with HPCSC. Conclusions. HPCSC rates in children below 5 years of age may potentially be reduced through improve- ments in PCU structure and process indicators and in municipal social determinants.

[RESUMEN]. Objetivo. Determinar la asociación de la estructura de las unidades básicas de salud (UBS) y del proceso de trabajo de los equipos de atención primaria con los determinantes sociales y las tasas de hospitalización por afecciones que podrían tratarse en la atención primaria en menores de 5 años en Brasil. Métodos. Estudio longitudinal ecológico, con datos secundarios del Sistema de Informaciones Hospitalarias y los tres ciclos del Programa Nacional de Mejora del Acceso y de la Calidad de la Atención Básica (PMAQ-AB) (2012, 2014, 2017-2018). Se analizaron 42.916 UBS. Se aplicó un modelo multinivel con pendiente fija e inter- cepción aleatoria. En el primer nivel, se analizaron el desenlace (tasas de hospitalización por afecciones que podrían tratarse en los servicios de atención primaria) y las variables explicativas (indicadores estructurales y procedimentales) consolidados por UBS. En el segundo nivel, se incluyeron determinantes sociales munici- pales (representados por un criterio de estratificación que combina el tamaño del municipio con indicadores que influyen en la gestión de salud). Se utilizó la prueba de la t con la corrección de Bonferroni para comparar las medias de los indicadores entre las regiones y la regresión lineal multinivel para estimar los coeficientes de correlación. Resultados. La tasa de hospitalización por afecciones que podrían tratarse en los servicios de atención pri- maria en menores de 5 años fue de 62,78/100 mil habitantes por área estimada de cobertura de UBS. Los siguientes factores presentaron una asociación directa con el desenlace: participación en uno o más ciclos del PMAQ-AB; planificación del equipo; horario especial; dependencias de atención infantil en la unidad; y disponibilidad de vacunas. La variable relativa a equipos, materiales e insumos y la clasificación como muni- cipio pequeño o mediano se asociaron inversamente con las hospitalizaciones por afecciones que podrían tratarse en los servicios de atención primaria. Conclusiones. Las hospitalizaciones de menores de 5 años por afecciones que podrían tratarse en los ser- vicios de atención primaria pueden reducirse mejorando los indicadores estructurales y procedimentales de las UBS y los determinantes sociales municipales.

Spatiotemporal analysis of hospital admissions for primary care-sensitive conditions in women and children in the first 1000 days of life.

OBJECTIVE: To analyze the spatiotemporal distribution of hospital admission rates for primary care-sensitive conditions (PCSC) in women and children in the first 1000 days of life in Brazil. METHODS: Ecological study, with spatiotemporal analyses, using secondary data from Brazilian municipalities. PCSC in women, related to prenatal care and childbirth, and in children under two years old, from 2008 to 2019 were used to characterize trends and formations of spatiotemporal clusters/outliers. Crude PCSC rates were calculated and adjusted by the local empirical Bayesian method, presented in choropleth maps. We also used Anselin Local Moran I type analyses to identify spatial clusters, and space-time cube with clustering by emerging hotspot, followed by time series clustering, for analysis of spatiotemporal trends (alpha = 5%). RESULTS: A total of 1,850,776 PCSC were registered in pregnant women, puerperae, and children under two years of age in Brazil, representing 1.7% of the total number of hospital admissions in the period. PCSC rates showed different behaviors when the groups of women and children were evaluated, with a predominant growing trend of 109% in admissions in the first group and a reduction of 34.4% in the second. The North, Northeast, and Midwest regions had larger high-risk clusters and more significant increasing trends in PCSC in the two subpopulations studied. CONCLUSIONS: Health actions and services in primary care may be reducing hospital admissions for children, but they are not being effective in reducing hospital admissions for women for causes related to prenatal care and childbirth, especially in the North, Northeast, and Midwest of Brazil. Investments in the qualification of care over the thousand days are urgent in the country.

Desigualdades macrorregionais na atenção primária ao Diabetes Mellitus: comparação dos três ciclos do PMAQ-AB / Diabetes Mellitus macro-regional inequalities in PHC: comparing the three PMAQ-AB cycles

RESUMO O objetivo do estudo foi identificar desigualdades macrorregionais relacionadas à estrutura e ao processo de trabalho para o atendimento do Diabetes Mellitus (DM) na Atenção Primária à Saúde (APS) ao longo dos três ciclos do Programa Nacional de Melhoria do Acesso e da Qualidade da Atenção Básica (PMAQ-AB) no Brasil. Trata-se de um estudo ecológico, longitudinal, de abrangência nacional, com dados secundários dos três ciclos do PMAQ-AB. Os dados foram comparados entre as macrorregiões brasileiras utilizando o teste t com a correção de Bonferroni. As regiões Norte e Nordeste apresentaram os menores percentuais de adequação nos itens de estrutura: dependências da unidade (<74%), acessibilidade ao cadeirante (<63%), horário especial de funcionamento (<16%), equipe ampliada (<12%) e insumos (<89%) em todos os ciclos do PMAQ-AB, quando comparadas às demais regiões. Já os itens relacionados ao processo de trabalho apresentaram pouca variação entre as regiões, e os que apresentaram percentuais médios ≤ 75% de adequação foram: agenda especializada (41%, 33%, 41%), apoio matricial (58%, 72%, 70%), oferta e resolubilidade de ações (62%, 64%, 75%) e educação permanente (35%, 42%, 58%). Ainda existe a necessidade de investimentos na estrutura e em melhorias no processo de trabalho das equipes, principalmente nas macrorregiões Norte e Nordeste.

ABSTRACT This study aimed to identify macro-regional structure and work process inequalities for Diabetes Mellitus (DM) treatment in Primary Health Care (PHC) throughout the three cycles of the National Program for Access and Quality Improvement of Primary Care (PMAQ-AB) in Brazil. This ecological, longitudinal, nationwide study employed secondary data from the three PMAQ-AB cycles. The data were compared between the Brazilian macro-regions using the t-test with Bonferroni correction. The North and Northeast had the lowest percentages of adequacy in the structure items: unit premises (<74%), wheelchair user accessibility (<63%), special opening hours (<16%), expanded teams (<12%), and supplies (<89%) in all PMAQ-AB cycles when compared to other regions. The items related to the work process barely varied between regions, and those with mean adequacy percentages ≤ 75% were specialized agenda (41%, 33%, 41%), matrix support (58%, 72%, 70 %), offer and resolution of actions (62%, 64%, 75%) and continuing education (35%, 42%, 58%). Investments are still required in the structure and improvement in the teams' work process, especially in the North and Northeast macro-regions.

Are Primary Health Care Features Associated with Reduced Late Neonatal Mortality in Brazil? An Ecological Study.

OBJECTIVE: To analyze the effect and efficiency of the characteristics of PHC facilities' structures and the work process of PHC teams on late neonatal mortality (LNM). METHODS: This ecological time-series study adopted 3.764 Brazilian municipalities as analysis units. The independent variables were sorted into three hierarchical levels and four blocks. The distal level consisted of economic and demographic variables; the intermediate level comprised health coverage and demand for services; and the proximal level included structure and work process. The dependent variable was LNM. A linear mixed-effects regression analysis with a hierarchical approach was performed, estimating the crude (ß) and adjusted (alpha = 5%) regression coefficients. Data involution analysis and municipalities were the decision-making unit according to their strata. RESULTS: LNM was directly associated with the number of live births and unemployment rate. LNM was inversely associated with the year, per capita income, the community health worker's strategy coverage, vaginal delivery, household visits, and available vaccines. In the 2002-2014 period, the number of municipalities efficient in reducing LNM dropped from 38 to 27. In 2014, a more significant investment occurred in the number of vaginal deliveries in almost all strata to make inefficient municipalities efficient. CONCLUSION FOR PRACTICE: The deaths of children aged 7-28 days are affected by the characteristics of the PHC structure and work process.