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No Brasil, a judicialização da saúde, que é o uso de ações judiciais para garantir acesso a medicamentos e serviços de saúde, atende a interesses diversos e torna mais complexa a gestão das políticas públicas de saúde. A produção de estatísticas sobre essas ações é desafiadora, pois existem grandes divergências entre fontes de dados. Em Minas Gerais há um número significativo de ações, com grandes desafios na classificação e na padronização das informações. A pesquisa realizada mostrou que, com técnicas de mineração de dados e padronização da definição de processos de saúde, é possível avançar nessa direção. Ferramentas como o JUDJe objetivam facilitar a compreensão da judicialização da saúde, utilizando tecnologia de ponta e respeitando as regras de privacidade e segurança. Conclui-se pela necessidade de incorporar amplamente essas ferramentas e padronizar os assuntos, para beneficiar a gestão do setor de saúde em todo o Brasil.
The judicialization of health in Brazil, through legal actions to guarantee access to medicines and health services, complicates health policies and serves different interests. Accurately accounting for these actions is challenging, highlighting divergences between data sources. Analysis of data from Minas Gerais reveals significant numbers, but highlights challenges in classifying and standardizing information. Research showed that, with data mining techniques and standardization of the definition of health processes, it is possible to move in this direction. Tools like JUDJe promise to improve understanding of the judicialization of health, facing technological, privacy and security challenges. It is concluded that there is a need to widely incorporate these tools and standardize matters, to benefit the management of the health sector throughout Brazil.
La judicialización de la salud en Brasil, a través de acciones legales para garantizar el acceso a medicamentos y servicios de salud, complica las políticas de salud y atiende intereses diferentes. Contabilizar con precisión estas acciones es un desafío, lo que pone de relieve las divergencias entre las fuentes de datos. El análisis de datos de Minas Gerais revela cifras significativas, pero destaca los desafíos en la clasificación y estandarización de la información. Investigaciones muestran que, con técnicas de minería de datos y estandarización de la definición de procesos de salud, es posible avanzar en esa dirección. Herramientas como JUDJe prometen mejorar la comprensión de la judicialización de la salud, enfrentando desafíos tecnológicos, de privacidad y de seguridad. Se concluye que es necesario incorporar ampliamente estas herramientas y estandarizar las materias, para beneficiar la gestión del sector salud en todo Brasil.
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Direito SanitárioRESUMO
O texto parte da disputa em torno da regulação da inteligência artificial (IA) realmente existente, dividida entre dois polos, o da proteção da inovação e o da necessidade de mitigar riscos sociais e ambientais. Avança para apontar a colossal concentração de poder computacional e de dados nas mãos dos oligopólios digitais, as big techs. Levanta preocupações sobre o impacto dessa concentração na soberania digital e na capacidade do país em controlar suas infraestruturas e dados. Argumenta como a falta de transparência e explicabilidade nos sistemas de IA agrava os riscos de discriminação e exclusão social. Ainda, defende que a regulação da IA deve garantir direitos, salvaguardar a soberania e promover um ecossistema digital autônomo e inclusivo.
The text begins by addressing the debate surrounding the regulation of existing artificial intelligence (AI), divided between two poles: the protection of innovation and the need to mitigate social and environmental risks. It progresses to highlight the colossal concentration of computational power and data in the hands of digital oligopolies, the big tech companies. The text raises concerns about the impact of this concentration on digital sovereignty and the country's ability to control its infrastructures and data. It argues that the lack of transparency and explainability in AI systems exacerbates the risks of discrimination and social exclusion. The text advocates that AI regulation should ensure rights, safeguard sovereignty, and promote an autonomous and inclusive digital ecosystem.
El texto parte de la disputa en torno a la regulación de la inteligencia artificial (IA) existente, dividida entre dos polos: la protección de la innovación y la necesidad de mitigar riesgos sociales y ambientales. Avanza para señalar la colosal concentración de poder computacional y de datos en manos de los oligopolios digitales, las big tech. Plantea preocupaciones sobre el impacto de esta concentración en la soberanía digital y en la capacidad del país para controlar sus infraestructuras y datos. Argumenta que la falta de transparencia y explicabilidad en los sistemas de IA agrava los riesgos de discriminación y exclusión social. El texto defiende que la regulación de la IA debe garantizar derechos, salvaguardar la soberanía y promover un ecosistema digital autónomo e inclusivo.
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Inteligência Artificial , Administração das Tecnologias da Informação , Governo Eletrônico , Algoritmos , Sistemas Inteligentes , Processamento Eletrônico de Dados , Riscos Ambientais , Invenções , Análise de Dados , Tecnologia Digital , Vulnerabilidade SocialRESUMO
Introducción: La Distrofia Muscular de Duchenne (DMD) y la Atrofia Muscular Espinal (AME) son enfermedades neuromusculares genéticas poco comunes pero graves en la población pediátrica con alta carga de morbilidad y mortalidad. A pesar de avances en su comprensión y búsqueda de opciones terapéuticas dirigidas, persisten vacíos en la detección oportuna, caracterización, seguimiento de pacientes, búsqueda activa de portadores y en algunos países de Latinoamérica sin tamización neonatal. Objetivo: Caracterizar clínica, paraclínica, imagenológica y molecularmente pacientes con diagnóstico presuntivo y confirmado de distrofia muscular de Duchenne (DMD) y Atrofia Muscular Espinal (AME) atendidos en un centro pediátrico de referencia y excelencia del Suroccidente Colombiano. Materiales y Métodos: Estudio observacional de corte transversal en pacientes menores de 18 años con diagnósticos CIE-10 relacionados con DMD y AME. Los datos se exportaron a una matriz de Excel en Office 365 versión 2403, y luego a IBM SPSS versión 29 para realizar un análisis univariado, se emplearon medidas de tendencia central y dispersión para variables numéricas, considerando su distribución, y frecuencias absolutas y porcentajes para variables cualitativas. Resultados: Tras revisar 954 historias clínicas pertenecientes a un centro de atención pediátrica en el Suroccidente Colombiano entre los años 2015 - 2021, se identificaron 422 casos relacionados a Distrofia Muscular de Duchenne (DMD) y Atrofia Muscular Espinal (AME); excluyendo duplicados y registros no relacionados, de estos, se seleccionaron aleatoriamente 99 casos para un análisis exhaustivo utilizando OpenEpi versión 3.01, distribuidos en dos grupos: AME (n=23) y DMD (n=76). Los pacientes confirmados con Distrofia Muscular de Duchenne (DMD) mostraron un inicio de síntomas a los 54,5 ± 29,0 meses y un diagnóstico a los 98,8 ± 34,9 meses, siendo más común en varones con hipotonía y niveles elevados de creatin quinasa (CK), el 54,5% presentaba trastorno cognitivo y el 88.2% tenía antecedentes familiares, en la Atrofia Muscular Espinal (AME), el inicio de síntomas fue a los 28,9 ± 37,7 meses y el diagnóstico a los 37,9 ± 38,2 meses, siendo predominante en mujeres con arreflexia y fasciculaciones, no hubo registros de la función cognitiva en los pacientes confirmados, y el 21,7% tenía antecedentes familiares de AME, además de ligeras elevaciones de CK. En el grupo AME, 9 casos se confirmaron molecularmente y 3 se respaldaron con registros médicos; en contraste, en el grupo de DMD, 22 casos tuvieron confirmación molecular, pero 9 contaban con anotaciones en los registros médicos, aunque estos informes eran incompletos. Conclusiones: La sospecha y diagnóstico temprano de estas enfermedades neurodegenerativas progresivas que se caracterizan por altas tasas de morbilidad y mortalidad es fundamental para impactar en el abordaje holístico que deben recibir los pacientes. Dado al continuo avance en métodos diagnósticos y opciones terapéuticas innovadoras y dirigidas ( medicina de la hiperpersonalización ), se hace necesario crear registros y "big data" médicos- clínicos completos, que cuenten con todas las herramientas actuales disponibles (opciones diagnósticas multimodales) que faciliten el re-contacto de pacientes, seguimiento y poderles ofrecer una atención personalizada, de precisión, que mejore la calidad de vida de ellos, sus familias, contribuyendo en la generación de políticas públicas integradas y dirigidas. (provisto por Infomedic International)
Introduction: Duchenne Muscular Dystrophy (DMD) and Spinal Muscular Atrophy (SMA) are rare but severe genetic neuromuscular diseases in the pediatric population with high burden of morbidity and mortality. Despite advances in their understanding and search for targeted therapeutic options, there are still gaps in timely detection, characterization, patient follow-up, active search for carriers and in some Latin American countries no neonatal screening. Objective: To characterize clinically, paraclinically, imaging and molecularly patients with presumptive and confirmed diagnosis of Duchenne muscular dystrophy (DMD) and Spinal Muscular Atrophy (SMA) attended in a pediatric center of reference and excellence in Southwestern Colombia. Materials and Methods: Observational cross-sectional study in patients under 18 years of age with ICD-10 diagnoses related to DMD and SMA. Data were exported to an Excel matrix in Office 365 version 2403, and then to IBM SPSS version 29 to perform a univariate analysis, measures of central tendency and dispersion were used for numerical variables, considering their distribution, and absolute frequencies and percentages for qualitative variables. Results: After reviewing 954 medical records belonging to a pediatric care center in Southwestern Colombia between 2015 - 2021, 422 cases related to Duchenne Muscular Dystrophy (DMD) and Spinal Muscular Atrophy (SMA) were identified; excluding duplicates and unrelated records, from these, 99 cases were randomly selected for a comprehensive analysis using OpenEpi version 3.01, distributed in two groups: SMA (n=23) and DMD (n=76). Patients confirmed with Duchenne Muscular Dystrophy (DMD) showed symptom onset at 54.5 ± 29.0 months and diagnosis at 98.8 ± 34.9 months, being more common in males with hypotonia and elevated creatin kinase (CK) levels, 54.5% had cognitive impairment and 88. 2% had family history, in Spinal Muscular Atrophy (SMA), the onset of symptoms was at 28.9 ± 37.7 months and diagnosis at 37.9 ± 38.2 months, being predominant in females with areflexia and fasciculations, there were no records of cognitive function in confirmed patients, and 21.7% had family history of SMA, in addition to slight elevations of CK. In the SMA group, 9 cases were molecularly confirmed and 3 were supported by medical records; in contrast, in the DMD group, 22 cases had molecular confirmation, but 9 had annotations in medical records, although these reports were incomplete. Conclusions: Early suspicion and diagnosis of these progressive neurodegenerative diseases characterized by high morbidity and mortality rates is critical to impact the holistic approach patients should receive. Given the continuous advance in diagnostic methods and innovative and targeted therapeutic options (hyperpersonalization medicine), it is necessary to create complete medical-clinical registries and big data, which have all the current tools available (multimodal diagnostic options) to facilitate patient re-contact, follow-up and to be able to offer personalized, precision care that improves the quality of life of patients and their families, contributing to the generation of integrated and targeted public policies. (provided by Infomedic International)
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Resumo O objetivo foi analisar a qualidade dos dados antropométricos de crianças menores de cinco anos em dois sistemas de informação no estado de São Paulo. A amostra compreendeu 2.117.108 crianças do Sistema de Vigilância Alimentar e Nutricional (Sisvan) e 748.551 do Projeto Estadual do Leite (Vivaleite). Inicialmente, avaliamos a frequência de valores faltantes e fora do espectro do equipamento, e calculamos o índice de preferência de dígito para peso. Após calcular os índices de altura para idade (A-I), peso para idade (P-I) e índice de massa corporal para idade (IMC-I), identificamos os valores biologicamente implausíveis (VBI) e calculamos o desvio-padrão (DP). Para cada município, calculamos a média e o DP de A-I, P-I e IMC-I; e plotamos os valores de DP em função da média. A preferência de dígito no peso foi maior em crianças de 24 a 59 meses no Sisvan. A frequência de VBI para A-I (SISVAN 2,56%; Vivaleite 0,98%) foi maior do que para P-I (Sisvan 2,10%; Vivaleite 0,18%). Para o índice A-I as variações entre os municípios foram mais acentuadas no Vivaleite do que no Sisvan. A variável altura apresentou baixa confiabilidade nos dois sistemas. A variável peso apresentou qualidade satisfatória no Vivaleite e insatisfatória no Sisvan.
Abstract This paper involves the analysis of the quality of anthropometric data on children under five years of age in two information systems in the State of São Paulo. The sample included 2,117,108 children from the Food and Nutrition Surveillance System (SISVAN), and 748,551 from the State Milk Project (VIVALEITE). Initially, we evaluated the frequency of missing values and others outside the equipment spectrum and calculated the digit-to-weight preference index. After calculating height-for-age (HAZ), weight-for-age (WAZ), and body mass index-for-age (BAZ), we flagged the biologically implausible values (BIV) and calculated the standard deviation (SD). For each municipality, we calculated the mean and the SD of HAZ, WAZ, and BAZ; and plotted the SD values as a function of the mean. The digit-to-weight preference index was greater among children aged between 24 and 59 months in SISVAN. The frequency of BIV for HAZ (SISVAN 2.56%; VIVALEITE 0.98%) was higher than for WAZ (SISVAN 2.10%; VIVALEITE 0.18%). For HAZ, variations among municipalities were more pronounced in VIVALEITE than in SISVAN. The height variable presents low reliability in both systems. The weight variable reveals satisfactory quality in VIVALEITE and unsatisfactory quality in SISVAN.
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Introducción : La Organización Mundial de la Salud (OMS) efectuó recomendaciones en relación con la recopilación y notificación de datos agregados semanales de COVID-19. Objetivo : Investigar el grado de cumplimiento de las recomendaciones elaboradas por la OMS para la notificación de casos y muertes de COVID-19 en la Argentina durante el año 2020 a 2022, y comparar la notificación de muertes con el número de defunciones por COVID-19 consolidadas en el registro de estadísticas vitales del país. Materiales y métodos : Estudio cuantitativo descriptivo, basado en revisión documental y en fuentes de datos secundarias. Se utilizó los reportes diarios de información epidemiológica y la base de datos Dataset, COVID-19 casos registrados en la República Argentina. Adicionalmente, para estimar la omisión en los registros epidemiológicos de fallecimientos por COVID-19 en los años 2020 y 2021, se cotejaron los resultados de las bases de datos Dataset COVID-19 con la base de las Estadísticas vitales de mortalidad por causa de defunción, proporcionadas por la Dirección de Estadísticas e Información en Salud (DEIS). Se analizaron las variables recomendadas por la OMS para la notificación de casos y muertes por COVID-19. En cuanto a las consideraciones éticas relacionadas con el uso de la información utilizada en este trabajo, las bases de datos cumplen con lo estipulado por la Ley Nacional N° 17.622 de Resguardo del Secreto Estadístico, garantizando que la información mantiene el carácter confidencial y reservado del informante. Resultados: Del análisis de los reportes diarios, durante 2020 se observó que, de los 13 indicadores recomendados, 9 presentan datos algunos meses y los 4 restantes no se relevaron; en 2021 solo 7 indicadores presentaron datos algunos meses, y en 2022 solo 3 indicadores se continuaron informando. Respecto al análisis de la base de datos Dataset COVID-19, la mayoría fueron captadas. Respecto a la comparación de los valores de las defunciones registradas por el sistema de vigilancia epidemiológica y por la DEIS para los años 2020 y 2021, las muertes registradas fueron superiores en el registro de la DEIS (9,6% y 14,2%). Conclusiones : El Estado argentino cumplió con gran parte de las recomendaciones que establece la OMS para la notificación de los casos de COVID-19. Estudios posteriores deberían analizar otros componentes de la calidad de los datos, así como la oportunidad de los registros de defunciones, característica necesaria para la toma de decisiones en salud pública.
Introduction : The World Health Organization (WHO) establishes recommendations regarding the collection and reporting of weekly aggregated data on COVID-19. Objective : To investigate the degree of compliance with the recommendations made by the WHO for the reporting of COVID-19 cases and deaths in Argentina during the years 2020 to 2022, and to compare death notifications with the number of COVID-19 deaths recorded in the country's vital statistics registry. Materials and methods : Descriptive quantitative study, based on a documentary review and secondary data sources. Daily reports of epidemiological information and the Dataset database containing registered COVID-19 cases in the Argentine Republic were used. Additionally, to estimate the omission in the epidemiological records of COVID-19 deaths in the years 2020 and 2021, the results of the Dataset COVID-19 databases were compared with the vital statistics death registry on cause of death, provided by the Directorate of Statistics and Health Information (DEIS, by its acronym in Spanish). The variables recommended by the WHO for the reporting of COVID-19 cases and deaths were analyzed. As for the ethical considerations related to the use of the information in this study, the databases comply with the provisions of National Law 17,622 on the Protection of Statistical Secrecy, ensuring that the information remains confidential and reserved for the informant. Results : From the analysis of daily reports, it was observed that in 2020, out of the 13 recommended indicators, 9 had data for some months, and the remaining 4 were not reported. In 2021 only 7 indicators had data for some months, and in 2022 only 3 indicators continued to be reported. Regarding the analysis of the Dataset COVID-19 database, most data were captured. In comparing the values of deaths recorded by the epidemiological surveillance system and by the DEIS for the years 2020 and 2021, the deaths recorded were higher in the DEIS registry (9.6% and 14.2%). Conclusions : The Argentine state largely complied with the recommendations established by the WHO for the reporting of COVID-19 cases. Subsequent studies should analyze other components of data quality, as well as the timeliness of death records, a necessary characteristic for public health decision-making.
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Objetivo: Estimar as perdas de produtividade causadas pela doença pulmonar obstrutiva crônica (DPOC) na população brasileira. Métodos: O estudo utilizou dados obtidos do Datasus, IBGE, indicadores previdenciários, óbitos e aposentadorias precoces por DPOC no Brasil de 2017 a 2022. Para estimar o impacto da DPOC, foram utilizados: anos de vida saudável perdidos (DALYs) e anos de vida ajustados por produtividade (PALYs), assim como as métricas de perda de produtividade salarial (PPS) e perda de produtividade nacionalizada (PPN), que avalia a perda em função do PIB. Resultados: Mais de 196 milhões de dias de trabalho foram perdidos devido à DPOC. As principais fontes são: óbitos precoces (95.264.088), afastamentos permanentes (67.314.232) e aposentadoria precoce (30.304.490). Diárias hospitalares (3.221.591) têm uma contribuição minoritária. O valor total de DALYs observado no período do estudo foi de 2.819.332,63 anos de vida saudável perdidos causados pela DPOC; um total de 14.997.166 PALYs foi perdido por conta da DPOC ou um valor anual equivalente de R$ 230,7 bilhões. Considerando a PPS, estimamos que a DPOC acarretou perdas de produtividade associadas à reposição da mão de obra de R$ 1,38 bilhão anual e, em relação à PPN, de R$ 8,28 bilhões por ano. Conclusões: Afastamentos de pacientes com DPOC podem acarretar maiores dispêndios com pagamentos de benefícios previdenciários. Este estudo atualiza e amplia correlações entre dados socioepidemiológicos, custos de saúde e previdenciários da DPOC no Brasil. Considerando todas as perdas, a DPOC pode causar perdas de R$ 240 bilhões por ano.
Objective: To estimate productivity losses due to workdays lost caused by chronic obstructive pulmonary disease (COPD) in the Brazilian population. Methods: The study used data from DATASUS, IBGE, social security indicators, deaths, and early retirements due to COPD in Brazil from 2017 to 2022. To estimate the impact of COPD, the following were used: Disability-Adjusted Life Years (DALYs) and Productivity-Adjusted Life Years (PALYs), as well as metrics for wage productivity loss (PPS) and nationalized productivity loss (PPN), which evaluates the loss in relation to GDP. Results: More than 196 million workdays were lost due to COPD. The main sources are premature deaths (95,264,088), permanent absences (67,314,232), and early retirement (30,304,490). Hospitalization days (3,221,591) had a minor contribution. The total DALYs observed during the study period was 2,819,332.63 years of healthy life lost due to COPD; a total of 14,997,166 PALYs were lost due to COPD, equivalent to an annual value of R$ 230.7 billion. Considering PPS, we estimate that COPD resulted in productivity losses associated with workforce replacement of R$ 1.38 billion annually; and in relation to PPN, R$ 8.28 billion per year. Conclusions: Absences in COPD patients can lead to higher expenditures on social security benefit payments. This is the first study to correlate socioepidemiological data, health, and social security costs of COPD in Brazil. Considering all losses, COPD can cause losses of R$ 240 billion per year.
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In 2023, cholera affected approximately 1 million people and caused more than 5000 deaths globally, predominantly in low-income and conflict settings. In recent years, the number of new cholera outbreaks has grown rapidly. Further, ongoing cholera outbreaks have been exacerbated by conflict, climate change, and poor infrastructure, resulting in prolonged crises. As a result, the demand for treatment and intervention is quickly outpacing existing resource availability. Prior to improved water and sanitation systems, cholera, a disease primarily transmitted via contaminated water sources, also routinely ravaged high-income countries. Crumbling infrastructure and climate change are now putting new locations at risk - even in high-income countries. Thus, understanding the transmission and prevention of cholera is critical. Combating cholera requires multiple interventions, the two most common being behavioral education and water treatment. Two-dose oral cholera vaccination (OCV) is often used as a complement to these interventions. Due to limited supply, countries have recently switched to single-dose vaccines (OCV1). One challenge lies in understanding where to allocate OCV1 in a timely manner, especially in settings lacking well-resourced public health surveillance systems. As cholera occurs and propagates in such locations, timely, accurate, and openly accessible outbreak data are typically inaccessible for disease modeling and subsequent decision-making. In this study, we demonstrated the value of open-access data to rapidly estimate cholera transmission and vaccine effectiveness. Specifically, we obtained non-machine readable (NMR) epidemic curves for recent cholera outbreaks in two countries, Haiti and Cameroon, from figures published in situation and disease outbreak news reports. We used computational digitization techniques to derive weekly counts of cholera cases, resulting in nominal differences when compared against the reported cumulative case counts (i.e., a relative error rate of 5.67% in Haiti and 0.54% in Cameroon). Given these digitized time series, we leveraged EpiEstim-an open-source modeling platform-to derive rapid estimates of time-varying disease transmission via the effective reproduction number ( R t ). To compare OCV1 effectiveness in the two considered countries, we additionally used VaxEstim, a recent extension of EpiEstim that facilitates the estimation of vaccine effectiveness via the relation among three inputs: the basic reproduction number ( R 0 ), R t , and vaccine coverage. Here, with Haiti and Cameroon as case studies, we demonstrated the first implementation of VaxEstim in low-resource settings. Importantly, we are the first to use VaxEstim with digitized data rather than traditional epidemic surveillance data. In the initial phase of the outbreak, weekly rolling average estimates of R t were elevated in both countries: 2.60 in Haiti [95% credible interval: 2.42-2.79] and 1.90 in Cameroon [1.14-2.95]. These values are largely consistent with previous estimates of R 0 in Haiti, where average values have ranged from 1.06 to 3.72, and in Cameroon, where average values have ranged from 1.10 to 3.50. In both Haiti and Cameroon, this initial period of high transmission preceded a longer period during which R t oscillated around the critical threshold of 1. Our results derived from VaxEstim suggest that Haiti had higher OCV1 effectiveness than Cameroon (75.32% effective [54.00-86.39%] vs. 54.88% [18.94-84.90%]). These estimates of OCV1 effectiveness are generally aligned with those derived from field studies conducted in other countries. Thus, our case study reinforces the validity of VaxEstim as an alternative to costly, time-consuming field studies of OCV1 effectiveness. Indeed, prior work in South Sudan, Bangladesh, and the Democratic Republic of the Congo reported OCV1 effectiveness ranging from approximately 40% to 80%. This work underscores the value of combining NMR sources of outbreak case data with computational techniques and the utility of VaxEstim for rapid, inexpensive estimation of vaccine effectiveness in data-poor outbreak settings.
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Knowing the prevalence of potentially avoidable hospitalizations (PAHs) and the factors associated with them is essential if preventive action is to be taken. Studies on PAHs mainly concern adults, and very few have been carried out in South America. To the best of our knowledge, there has been no study on PAHs in French Guiana, particularly among older adults. This case-control study aimed to estimate the prevalence of PAHs in the Guianese population aged over 65 and to analyze their associated factors. We used the 2017-2019 data from the French National Health Service database (Système National des Données de Santé). The patients were age- and sex-matched 1 : 3 with controls without any PAH in 2019. Factors associated with PAHs were investigated through two conditional logistic regression models [one including the Charlson comorbidity index (CCI) and one including each comorbidity of the CCI], with calculation of the adjusted odds ratio (aOR) and 95% confidence interval (CI). The PAH incidence was 17.4 per 1000 inhabitants. PAHs represented 6.6% of all hospitalizations (45.6% related to congestive heart failure or hypertension). A higher CCI was associated with PAHs [aOR 2.2 (95% CI: 1.6, 3.0) and aOR 4.8 (95% CI: 2.4, 9.9) for 1-2 and ≥3 comorbidities, respectively, versus 0], as was immigrant health insurance status [aOR 2.3 (95% CI: 1.3, 4.2)]. Connective tissue disease, chronic pulmonary disease, congestive heart failure, diabetes, and peripheral vascular disease were comorbidities associated with an increased risk of PAHs. While the prevention of PAHs among immigrants is probably beyond the reach of the Guianese authorities, primary care and a public health policy geared toward prevention should be put in place for the French Guianese population suffering from cardiovascular disease in order to reduce PAHs.
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Hospitalização , Humanos , Guiana Francesa/epidemiologia , Idoso , Masculino , Feminino , Hospitalização/estatística & dados numéricos , Estudos de Casos e Controles , Idoso de 80 Anos ou mais , Comorbidade , Fatores de Risco , Bases de Dados FactuaisRESUMO
PURPOSE: The complexity of cancer care requires planning and analysis to achieve the highest level of quality. We aim to measure the quality of care provided to patients with non-small cell lung cancer (NSCLC) using the data contained in the hospital's information systems, in order to establish a system of continuous quality improvement. METHODS/PATIENTS: Retrospective observational cohort study conducted in a university hospital in Spain, consecutively including all patients with NSCLC treated between 2016 and 2020. A total of 34 quality indicators were selected based on a literature review and clinical practice guideline recommendations, covering care processes, timeliness, and outcomes. Applying data science methods, an analysis algorithm, based on clinical guideline recommendations, was set up to integrate activity and administrative data extracted from the Electronic Patient Record along with clinical data from a lung cancer registry. RESULTS: Through data generated in routine practice, it has been feasible to reconstruct the therapeutic trajectory and automatically calculate quality indicators using an algorithm based on clinical practice guidelines. Process indicators revealed high adherence to guideline recommendations, and outcome indicators showed favorable survival rates compared to previous data. CONCLUSIONS: Our study proposes a methodology to take advantage of the data contained in hospital information sources, allowing feedback and repeated measurement over time, developing a tool to understand quality metrics in accordance with evidence-based recommendations, ultimately seeking a system of continuous improvement of the quality of health care.
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This article presents an ingestion procedure towards an interoperable repository called ALPACS (Anonymized Local Picture Archiving and Communication System). ALPACS provides services to clinical and hospital users, who can access the repository data through an Artificial Intelligence (AI) application called PROXIMITY. This article shows the automated procedure for data ingestion from the medical imaging provider to the ALPACS repository. The data ingestion procedure was successfully applied by the data provider (Hospital Clínico de la Universidad de Chile, HCUCH) using a pseudo-anonymization algorithm at the source, thereby ensuring that the privacy of patients' sensitive data is respected. Data transfer was carried out using international communication standards for health systems, which allows for replication of the procedure by other institutions that provide medical images. OBJECTIVES: This article aims to create a repository of 33,000 medical CT images and 33,000 diagnostic reports with international standards (HL7 HAPI FHIR, DICOM, SNOMED). This goal requires devising a data ingestion procedure that can be replicated by other provider institutions, guaranteeing data privacy by implementing a pseudo-anonymization algorithm at the source, and generating labels from annotations via NLP. METHODOLOGY: Our approach involves hybrid on-premise/cloud deployment of PACS and FHIR services, including transfer services for anonymized data to populate the repository through a structured ingestion procedure. We used NLP over the diagnostic reports to generate annotations, which were then used to train ML algorithms for content-based similar exam recovery. OUTCOMES: We successfully implemented ALPACS and PROXIMITY 2.0, ingesting almost 19,000 thorax CT exams to date along with their corresponding reports.
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Algoritmos , Sistemas de Informação em Radiologia , Humanos , Inteligência Artificial , Tomografia Computadorizada por Raios X/métodos , Diagnóstico por Imagem , Bases de Dados FactuaisRESUMO
The double burden of diseases and scarce resources in developing countries highlight the need to change the conceptualization of health problems and translational research. Contrary to the traditional paradigm focused on genetics, the exposome paradigm proposed in 2005 that complements the genome is an innovative theory. It involves a holistic approach to understanding the complexity of the interactions between the human being's environment throughout their life and health. This paper outlines a scalable framework for exposome research, integrating diverse data sources for comprehensive public health surveillance and policy support. The Chilean exposome-based system for ecosystems (CHiESS) project proposes a conceptual model based on the ecological and One Health approaches, and the development of a technological dynamic platform for exposome research, which leverages available administrative data routinely collected by national agencies, in clinical records, and by biobanks. CHiESS considers a multilevel exposure for exposome operationalization, including the ecosystem, community, population, and individual levels. CHiESS will include four consecutive stages for development into an informatic platform: (1) environmental data integration and harmonization system, (2) clinical and omics data integration, (3) advanced analytical algorithm development, and (4) visualization interface development and targeted population-based cohort recruitment. The CHiESS platform aims to integrate and harmonize available secondary administrative data and provide a complete geospatial mapping of the external exposome. Additionally, it aims to analyze complex interactions between environmental stressors of the ecosystem and molecular processes of the human being and their effect on human health. Moreover, by identifying exposome-based hotspots, CHiESS allows the targeted and efficient recruitment of population-based cohorts for translational research and impact evaluation. Utilizing advanced technologies such as Artificial Intelligence (AI), Internet of Things (IoT), and blockchain, this framework enhances data security, real-time monitoring, and predictive analytics. The CHiESS model is adaptable for international use, promoting global health collaboration and supporting sustainable development goals.
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Ecossistema , Expossoma , Humanos , Chile , Saúde Pública , Exposição AmbientalRESUMO
BACKGROUND: Population surveys are crucial for public policy planning and provide valuable representative data. In the health sector studies to identify and assess the prevalence of Arterial Hypertension (AH), a chronic non-communicable disease (NCD), along with its associated risk factors have been conducted. OBJECTIVES: This study aims to assess the effectiveness of a population health survey in estimating the prevalence of arterial hypertension (AH) in the Sorocaba municipality between August 2021 and June 2023. METHODS: The analyzed performance indicator is the precision (design effect - deff) of AH prevalence in adults (≥ 18 years) and their exposure to primary risk factors. The total sample included 1,080 individuals from the urban area, deemed sufficient to estimate a deff of 1.5. This cluster-based study utilized census sectors as clusters, with data collected through household interviews, standardized questionnaires, and measurements of blood pressure and biometric parameters. The deff calculation formula used was weighted variance / raw variance. The Research Ethics Committee approved this study, with registration CAAE 30538520-1-0000-5373. RESULTS: The deff values ranged from 0.44 for chronic obstructive pulmonary disease to 1.63 for asthma, with a deff of 1.00 for AH prevalence. CONCLUSION: The study demonstrated good precision in its results, with high receptivity and cooperation from participants. The cost-effectiveness of the research deemed appropriate. The technique of selecting households within clusters (census sectors) based on detailed mapping and demographic data from the Instituto Brasileiro de Geografia e Estatística (IBGE) proved to be practical and efficient, suitable for replication in other municipalities and for studying other NCDs.
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Inquéritos Epidemiológicos , Hipertensão , Humanos , Hipertensão/epidemiologia , Hipertensão/diagnóstico , Prevalência , Adulto , Masculino , Pessoa de Meia-Idade , Feminino , Idoso , Adolescente , Adulto Jovem , Fatores de Risco , Brasil/epidemiologiaRESUMO
BACKGROUND: The use of technologies has had a significant impact on patient safety and the quality of care and has increased globally. In the literature, it has been reported that people die annually due to adverse events (AEs), and various methods exist for investigating and measuring AEs. However, some methods have a limited scope, data extraction, and the need for data standardization. In Brazil, there are few studies on the application of trigger tools, and this study is the first to create automated triggers in ambulatory care. OBJECTIVE: This study aims to develop a machine learning (ML)-based automated trigger for outpatient health care settings in Brazil. METHODS: A mixed methods research will be conducted within a design thinking framework and the principles will be applied in creating the automated triggers, following the stages of (1) empathize and define the problem, involving observations and inquiries to comprehend both the user and the challenge at hand; (2) ideation, where various solutions to the problem are generated; (3) prototyping, involving the construction of a minimal representation of the best solutions; (4) testing, where user feedback is obtained to refine the solution; and (5) implementation, where the refined solution is tested, changes are assessed, and scaling is considered. Furthermore, ML methods will be adopted to develop automated triggers, tailored to the local context in collaboration with an expert in the field. RESULTS: This protocol describes a research study in its preliminary stages, prior to any data gathering and analysis. The study was approved by the members of the organizations within the institution in January 2024 and by the ethics board of the University of São Paulo and the institution where the study will take place. in May 2024. As of June 2024, stage 1 commenced with data gathering for qualitative research. A separate paper focused on explaining the method of ML will be considered after the outcomes of stages 1 and 2 in this study. CONCLUSIONS: After the development of automated triggers in the outpatient setting, it will be possible to prevent and identify potential risks of AEs more promptly, providing valuable information. This technological innovation not only promotes advances in clinical practice but also contributes to the dissemination of techniques and knowledge related to patient safety. Additionally, health care professionals can adopt evidence-based preventive measures, reducing costs associated with AEs and hospital readmissions, enhancing productivity in outpatient care, and contributing to the safety, quality, and effectiveness of care provided. Additionally, in the future, if the outcome is successful, there is the potential to apply it in all units, as planned by the institutional organization. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/55466.
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Assistência Ambulatorial , Aprendizado de Máquina , Humanos , Brasil , Segurança do PacienteRESUMO
BACKGROUND: Vestibular Activities and Participation Measure (VAP) subscales assess the effect of vestibular disorders on activity and participation. This study aimed to perform the cross-cultural adaptation and assess the validity, internal consistency, reliability, and measurement error of the Brazilian version of VAP subscales. METHODS: The cross-cultural adaptation followed the translation, synthesis, back-translation, review by a committee of experts, and pretesting phases. Structural validity was assessed using exploratory factor analysis (EFA) and confirmatory factor analysis (CFA), while Spearman's correlation between VAP subscales and the Dizziness Handicap Inventory (DHI) was used to assess construct validity. Cronbach's alpha measured internal consistency. Intraclass correlation coefficient (ICC) assessed intra- and inter-rater reliability, and measurement error was calculated by using the standard error of measurement (SEM) and minimal detectable change (MDC). RESULTS: Additional information was included in the Brazilian version of the Vestibular Activities and Participation measure (VAP-BR) after approval by one of the developers of the instrument to improve the understanding among individuals. One factor was found in the EFA for each subscale with 50% explained variance. Regarding CFA, the subscales 1 (S1) and 2 (S2) presented, respectively, adequate model fit indices (ie, comparative fit index of 0.99 and 0.97, and standardized root mean square residual of 0.04 for both subscales), but a very low factor load in item 6 of S1 (0.08). Chronbach's alpha was 0.80 (S1) and 0.82 (S2). For intra-rater assessment, the S1 and S2 presented an ICC of 0.87 and 0.90, SEM of 0.01 and 1.16, and MDC of 0.39 and 0.46, respectively. When assessed by 2 different raters, SEM values were 1.03 and 1.53, and MDC values were 2.85 and 4.23 for S1 and S2, respectively; both subscales showed an ICC of 0.92. Correlations between DHI and VAP subscales presented coefficients above 0.57. CONCLUSION: The Brazilian version of VAP subscales presents good measurement properties and may assist health professionals in identifying activity limitations and participation restrictions in individuals with vestibular disorders.
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Comparação Transcultural , Traduções , Doenças Vestibulares , Humanos , Brasil , Reprodutibilidade dos Testes , Doenças Vestibulares/diagnóstico , Doenças Vestibulares/fisiopatologia , Feminino , Masculino , Pessoa de Meia-Idade , Adulto , Inquéritos e Questionários/normas , Psicometria , Avaliação da Deficiência , Análise Fatorial , IdosoRESUMO
We introduce a new modelling for long-term survival models, assuming that the number of competing causes follows a mixture of Poisson and the Birnbaum-Saunders distribution. In this context, we present some statistical properties of our model and demonstrate that the promotion time model emerges as a limiting case. We delve into detailed discussions of specific models within this class. Notably, we examine the expected number of competing causes, which depends on covariates. This allows for direct modeling of the cure rate as a function of covariates. We present an Expectation-Maximization (EM) algorithm for parameter estimation, to discuss the estimation via maximum likelihood (ML) and provide insights into parameter inference for this model. Additionally, we outline sufficient conditions for ensuring the consistency and asymptotic normal distribution of ML estimators. To evaluate the performance of our estimation method, we conduct a Monte Carlo simulation to provide asymptotic properties and a power study of LR test by contrasting our methodology against the promotion time model. To demonstrate the practical applicability of our model, we apply it to a real medical dataset from a population-based study of incidence of breast cancer in São Paulo, Brazil. Our results illustrate that the proposed model can outperform traditional approaches in terms of model fitting, highlighting its potential utility in real-world scenarios.
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Biometria , Neoplasias da Mama , Modelos Estatísticos , Neoplasias da Mama/epidemiologia , Neoplasias da Mama/terapia , Humanos , Biometria/métodos , Feminino , Método de Monte Carlo , Funções Verossimilhança , Análise de Sobrevida , AlgoritmosRESUMO
BACKGROUND: Evidence describing the types and annual costs of biological treatments for psoriasis in Latin America is scarce. This study aimed to estimate the frequency of use and costs of biologic therapy for psoriasis in Colombia in 2019. METHODS: This secondary data analysis uses the International Classification of Diseases terms associated with psoriasis, excluding those related to psoriatic arthritis, based on data from the registry of the Colombian Ministry of Health. We estimated the prevalence of psoriasis per 100,000 inhabitants; then, we retrieved the frequency of use of biologic therapy in patients with psoriasis and estimated the cost per year of each and overall therapies in 2019 in US dollars (USD). RESULTS: There were 100,823 patients with psoriasis in Colombia in 2019, which amounts to a prevalence of 0.2% in the general population. Of those patients, 4.9% received biologic therapy, most frequently males (60%). The most commonly used biological therapies for psoriasis in Colombia in 2019 were ustekinumab (35.2%), with an annual cost per patient of $12,880 USD; adalimumab (26%), with a yearly cost per patient of $7130 USD; and secukinumab (19.8%), with an annual cost per patient of $6825 USD. CONCLUSION: This is the first study to describe the use and cost of biological therapy for psoriasis in Colombia. It provides valuable cost-awareness information for the Colombian health system.
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Adalimumab , Terapia Biológica , Psoríase , Humanos , Psoríase/economia , Psoríase/tratamento farmacológico , Psoríase/terapia , Psoríase/epidemiologia , Colômbia/epidemiologia , Masculino , Feminino , Adalimumab/uso terapêutico , Adalimumab/economia , Adulto , Pessoa de Meia-Idade , Terapia Biológica/economia , Terapia Biológica/estatística & dados numéricos , Anticorpos Monoclonais Humanizados/economia , Anticorpos Monoclonais Humanizados/uso terapêutico , Ustekinumab/uso terapêutico , Ustekinumab/economia , Prevalência , Adulto Jovem , Fármacos Dermatológicos/economia , Fármacos Dermatológicos/uso terapêutico , Idoso , Sistema de Registros/estatística & dados numéricos , Custos de Medicamentos/estatística & dados numéricos , Custos de Cuidados de Saúde/estatística & dados numéricos , AdolescenteRESUMO
BACKGROUND: Recent evidence has linked air pollution with frailty, yet little is known about the role of NO2 in this association. Our aim was to assess the association between frailty and NO2 air concentrations in Mexican older adults. METHODS: We used georeferenced data from the population-based Nutrition and Health Survey in Mexico (NHNS) 2021, representative of national and subnational regions, to measure a frailty index based on 31 health deficits in adults aged 50 and older. Air pollution due to NO2 concentrations was estimated from satellite images validated with data from surface-level stations. Maps were produced using Jensen's Natural break method. The association of frailty and NO2 concentrations was measured using the frailty index (multivariate fractional response logit regression) and a frailty binary variable (frailty index [FI]â ≥0.36, multivariate logit regression). RESULTS: There was a positive and significant association of the frailty index with the NO2 concentrations, adjusting for age, sex, urban and rural area, years of education, socioeconomic status, living arrangement, particulate matter smaller than 2.5 microns, and indoor pollution. For each standard deviation increase in NO2 concentrations measured 10 years before the survey, the odds of being frail were 15% higher, and the frailty index was 14.5% higher. The fraction of frailty attributable to NO2 exposure ranged from 1.8% to 23.5% according to different scenarios. CONCLUSIONS: Frailty was positively associated with exposure to NO2 concentrations. Mapping frailty and its associated factors like NO2 air concentrations can contribute to the design of targeted pro-healthy aging policies.
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Poluição do Ar , Fragilidade , Dióxido de Nitrogênio , Humanos , Masculino , Feminino , Idoso , Fragilidade/epidemiologia , México/epidemiologia , Pessoa de Meia-Idade , Dióxido de Nitrogênio/análise , Poluição do Ar/efeitos adversos , Poluição do Ar/análise , Poluentes Atmosféricos/análise , Poluentes Atmosféricos/efeitos adversos , Idoso de 80 Anos ou mais , Exposição Ambiental/efeitos adversos , Idoso Fragilizado/estatística & dados numéricos , Análise Espacial , Material Particulado/análise , Material Particulado/efeitos adversosRESUMO
Most described species have not been explicitly included in phylogenetic trees-a problem named the Darwinian shortfall-owing to a lack of molecular and/or morphological data, thus hampering the explicit incorporation of evolution into large-scale biodiversity analyses. We investigate potential drivers of the Darwinian shortfall in tetrapods, a group in which at least one-third of described species still lack phylogenetic data, thus necessitating the imputation of their evolutionary relationships in fully sampled phylogenies. We show that the number of preserved specimens in scientific collections is the main driver of phylogenetic knowledge accumulation, highlighting the major role of biological collections in unveiling novel biodiversity data and the importance of continued sampling efforts to reduce knowledge gaps. Additionally, large-bodied and wide-ranged species, as well as terrestrial and aquatic amphibians and reptiles, are phylogenetically better known. Future efforts should prioritize phylogenetic research on organisms that are narrow-ranged, small-bodied and underrepresented in scientific collections, such as fossorial species. Addressing the Darwinian shortfall will be imperative for advancing our understanding of evolutionary drivers shaping biodiversity patterns and implementing comprehensive conservation strategies.
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Biodiversidade , Evolução Biológica , Filogenia , Vertebrados , Animais , Vertebrados/genética , Vertebrados/classificação , Anfíbios/genética , Anfíbios/classificação , Répteis/classificação , Répteis/genéticaRESUMO
The economic trend and the health care landscape are rapidly evolving across Asia. Effective real-world data (RWD) for regulatory and clinical decision-making is a crucial milestone associated with this evolution. This necessitates a critical evaluation of RWD generation within distinct nations for the use of various RWD warehouses in the generation of real-world evidence (RWE). In this article, we outline the RWD generation trends for 2 contrasting nation archetypes: "Solo Scholars"-nations with relatively self-sufficient RWD research systems-and "Global Collaborators"-countries largely reliant on international infrastructures for RWD generation. The key trends and patterns in RWD generation, country-specific insights into the predominant databases used in each country to produce RWE, and insights into the broader landscape of RWD database use across these countries are discussed. Conclusively, the data point out the heterogeneous nature of RWD generation practices across 10 different Asian nations and advocate for strategic enhancements in data harmonization. The evidence highlights the imperative for improved database integration and the establishment of standardized protocols and infrastructure for leveraging electronic medical records (EMR) in streamlining RWD acquisition. The clinical data analysis and reporting system of Hong Kong is an excellent example of a successful EMR system that showcases the capacity of integrated robust EMR platforms to consolidate and produce diverse RWE. This, in turn, can potentially reduce the necessity for reliance on numerous condition-specific local and global registries or limited and largely unavailable medical insurance or claims databases in most Asian nations. Linking health technology assessment processes with open data initiatives such as the Observational Medical Outcomes Partnership Common Data Model and the Observational Health Data Sciences and Informatics could enable the leveraging of global data resources to inform local decision-making. Advancing such initiatives is crucial for reinforcing health care frameworks in resource-limited settings and advancing toward cohesive, evidence-driven health care policy and improved patient outcomes in the region.
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Viral infection disrupts the normal regulation of the host gene's expression. In order to normalise the expression of dysregulated host genes upon virus infection, analysis of stable reference housekeeping genes using quantitative real-time-PCR (qRT-PCR) is necessary. In the present study, healthy and African swine fever virus (ASFV) infected porcine tissues were assessed for the expression stability of five widely used housekeeping genes (HPRT1, B2M, 18 S rRNA, PGK1 and H3F3A) as reference genes using standard algorithm. Total RNA from each tissue sample (lymph node, spleen, kidney, heart and liver) from healthy and ASFV-infected pigs was extracted and subsequently cDNA was synthesized, and subjected to qRT-PCR. Stability analysis of reference genes expression was performed using the Comparative delta CT, geNorm, BestKeeper and NormFinder algorithm available at RefFinder for the different groups. Direct Cycle threshold (CT) values of samples were used as an input for the web-based tool RefFinder. HPRT1 in spleen, 18 S rRNA in liver and kidney and H3F3A in heart and lymph nodes were found to be stable in the individual healthy tissue group (group A). The majority of the ASFV-infected organs (liver, kidney, heart, lymph node) exhibited H3F3A as stable reference gene with the exception of the ASFV-infected spleen, where HPRT1 was found to be the stable gene (group B). HPRT1 was found to be stable in all combinations of all CT values of both healthy and ASFV-infected porcine tissues (group C). Of five different reference genes investigated for their stability in qPCR analysis, the present study revealed that the 18 S rRNA, H3F3A and HPRT1 genes were optimal reference genes in healthy and ASFV-infected different porcine tissue samples. The study revealed the stable reference genes found in healthy as well as ASF-infected pigs and these reference genes identified through this study will form the baseline data which will be very useful in future investigations on gene expression in ASFV-infected pigs.