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Empowered by the rapid development of artificial intelligence technology and information security technology, basic medicine, translational medicine, and clinical medicine have entered a new era. In this process, the relevant data such as text, genetics, images, and videos have increased at an astonishing rate. Traditional specialized disease databases cannot adapt to the multimodality of data and the multicentralization of data sources in the present/future. Therefore, establishing a next-generation multimodal and multicenter collaborative specialized disease database that is suitable for secure data sharing and ethical in clinical research is essential. This paper expounds the concept and basic framework of developing a next-generation clinical research disease database with universal use, emphasizing the establishment of a multimodal data integration mechanism, a multicenter collaborative system supported by privacy-preserving computing, highly intelligent software and hardware entities, and an integrated operational management mode. It also introduces the application of this concept in the construction of a breast cancer three-dimensional life database, a project of China Breast Cancer Innovation Alliance.
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ABSTRACT BACKGROUND: Precisely determining the aspects related to an instrument's validity and reliability measures allows for greater assurance of the quality of the results. OBJECTIVES: To analyze the psychometric properties of The Providers Survey in the Brazilian context of mental health services. DESIGN AND SETTING: The instrument validation study was conducted in Montes Claros, Minas Gerais, Brazil. METHODS: The validation study was conducted using the Consensus-based Standards for the Selection of Health Measurement Instruments checklist to analyze its validity and reliability. RESULTS: A committee of expert judges performed content validation after which the Content Validity Index was calculated. Construct validation took place through Exploratory Factor Analysis using the Kaiser-Meyer-Olkin Test criterion and Bartlett's Sphericity Test. Reliability was verified using test-retest reliability. The significance level adopted for the statistical tests was 5% (P < 0.05). The final instrument comprised 54 questions. The Content Validity Index was 97%. Exploratory Factor Analysis identified a Kaiser-Meyer-Olkin index of 0.901 and Bartlett's Sphericity Test with P < 0.001. We obtained a Cronbach's alpha coefficient of 0.95 and an intraclass correlation coefficient of 0.849. CONCLUSIONS: The Providers Survey, translated and adapted into Portuguese, was named the Work Assessment Instrument for the Recovery of Mental Health. It presented adequate psychometric properties for evaluating work-related practices for the recovery of psychosocial care network users.
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Abstract Background: Alarms alert healthcare professionals of deviations from normal/physiologic status. However, alarm fatigue may occur when their high pitch and diversity overwhelm clinicians, possibly leading to alarms being disabled, paused, and/or ignored. We aimed to determine whether a staff educational program on customizing alarm settings of bedside monitors may decrease inconsistent alarms in the Post-Anesthesia Care Unit (PACU). Methods: This is a prospective, analytic, quantitative, pragmatic, open-label, single-arm study. The outcome was evaluated on PACU admission before (P1) and after (P2) the implementation of the educational program. The heart rate, blood pressure, and oxygen saturation alarms were selected for clinical consistency. Results: A total of 260 patients were included and 344 clinical alarms collected, with 270 (78.4%) before (P1), and 74 (21.6%) after (P2) the intervention. Among the 270 alarms in P1, 45.2% were inconsistent (i.e., false alarms), compared to 9.4% of the 74 in P2. Patients with consistent alarms occurred in 30% in the P1 and 27% in the P2 (p = 0.08). Patients with inconsistent alarms occurred in 25.4% in the P1 and in 3.8% in the P2. Ignored consistent alarms were reduced from 21.5% to 2.6% (p = 0.004) in the P2 group. The educational program was a protective factor for the inconsistent clinical alarm (OR = 0.11 [95% CI 0.04-0.3]; p < 0.001) after adjustments for age, gender, and ASA physical status. Conclusion: Customizing alarm settings on PACU admission proved to be a protective factor against inconsistent alarm notifications of multiparametric monitors.
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【Objective】 To conduct a case-control study on precocious puberty as an example to introduce the establishment and design of the electronic Data capture and management platform using Research Electronic data Capture (REDCap) system and support the development of clinical research. 【Methods】 Based on the clinical REDCap system, the case-control research project of precocious puberty was created, the case report forms were designed, the user rights were set, and the data quality control rules were formulated. 【Results】 We established the electronic data capture and management platform for our research, which had 15 case report forms, to collect the data of the participants, including sociodemographic information, time for rest and activities, diet, exposure to environmental internal-secretion interfering-substances, physical examination and biochemical indicators. We conducted project management by setting up features such as user permissions and workgroups, and added data quality verification rules to control data quality. The data could be exported in various file formats for analysis and sharing. 【Conclusion】 The application of REDCap to establish the data capture and management platform of precocious puberty case-control study has promoted the efficient implementation of clinical research, which can be further popularized and applied to clinical researches in other fields.
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The use of digital means has made the public health emergency management more efficient and convenient. However, in the practice of managing public health emergencies, there are dilemmas in the protection of personal health information, such as the imperfect legal system, the weakened right of informed consent and control, the lack of reasonable norms in the collection and use of information, and the disclosure of personal health information. To solve the dilemma of personal health information protection, it is necessary to improve the corresponding legal mechanism, strengthen the classification of health information, standardize the behavior of health information collection and use, enhance the technical support of personal health information protection, build a system combining law and technology, and protect the security of personal health information.
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@#The number of investigator initiated research (IIR) is increasing. But the recognition and management of IIR in China is still in its infancy, and there is a lack of specific and operable guidance for the implementation process. Based on our practical experiences, previous literature reports, and current policy regulations, the authors took prospective IIR as an example to summarize the implementation process of IIR into 14 steps, which are as the following: study initiation, ethical review, study registration, study filing, case report form design, database establishment, standard operating procedure making, investigator training, informed consent, data collection, data entry, data verification, data locking and data archiving.
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Objective To develop aeromedical training data management software for manned centrifuges to realize comprehensive management of multi-type and multi-dimensional training information during pilot manned centrifuge training.Methods A piece of aeromedical training data management software for manned centrifuges was designed with micro-service pattern,programmed with C# language and developed with model-view-controller mode,which realized data interaction and time synchronization with other systems through multi-threading technology.There were eight functional modules involved in the system developed for login management,training management,training program management,pilot information management,trainer information management,pilot training data management,statistical query and system management.Results The software developed implemented information automatic acquisition and unified management of physiological parameter data,audio and video data and operating load curve,which enhanced the efficiency of training and the informatization level of training data statistics and analysis.Conclusion The software developed improves the informatization level of pilot manned centrifuge aeromedical training data management and provides support for aeromedical training.[Chinese Medical Equipment Journal,2023,44(11):39-44]
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@#Problem: From April to September 2021, Fiji experienced a second wave of coronavirus disease (COVID-19) precipitated by the Delta variant of concern, prompting a need to strengthen existing data management of positive COVID-19 cases. Context: With COVID-19 cases peaking at 1405 a day and many hospital admissions, the need to develop a better way to visualize data became clear. Action: The Fiji Ministry of Health and Medical Services, the World Health Organization and the United Nations Office for the Coordination of Humanitarian Affairs collaborated to develop an online clinical dashboard to support better visualization of case management data. Outcome: The dashboard was used across Fiji at national, divisional and local levels for COVID-19 management. At the national level, it provided real-time reports describing the surge pattern, severity and management of COVID-19 cases across the country during daily incident management team meetings. At the divisional level, it gave the divisional directors access to timely information about hospital and community isolation of cases. At the hospital level, the dashboard allowed managers to monitor trends in isolated cases and use of oxygen resources. Discussion: The dashboard replaced previous paper-based reporting of statistics with delivery of trends and real-time data. The team that developed the tool were situated in different locations and did not meet physically, demonstrating the ease of implementing this online tool in a resource-constrained setting. The dashboard is easy to use and could be used in other Pacific island countries and areas.
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Health informatics,also known as healthcare informatics or biomedical informatics, is a multidisciplinary field that focuses on the scientific study and practice of managing health data. In this paper authors have conceptualized health information literacyand health informatics. Discourses include: the role of medical libraries and medical librarians, Electronic Health Systems including Health Information Systems, Electronic Medical Record (EMR). Also, Medical Data Management, its benefits and challenges were also highlighted. Health information literature is also reviewed. The authors concluded by reiterating the importance of health information literacy, health informatics and its technological applications and the need for librarians and medical practitioners in the healthcare environments to acquire the requisite knowledge, skills and technologies that could enhance health information services delivery on the part of the librarians and healthcare services delivery on the part of the health practitioners
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Informática MédicaRESUMO
ABSTRACT Objectives: to analyze the accuracy of the clinical indicators of ineffective airway clearance in adult intensive care unit patients. Methods: diagnostic accuracy study, performed in the intensive care unit of a university hospital in northeastern Brazil. The sample consisted of 104 patients hospitalized between June and October 2019. Results: the prevalence of ineffective airway clearance was 36.54%. The indicators with high specificity included absence of cough (0.8326), orthopnea (0.6817), adventitious breath sounds (0.8175), and diminished breath sounds (0.8326). The clinical indicators with high sensitivity and specificity were alteration in respiratory rate (0.9999) and alteration in respiratory pattern (0.9999). Conclusions: six clinical indicators provided an accurate identification of ineffective airway clearance. The clinical indicators alteration in respiratory rate and alteration in respiratory pattern were the most accurate for critical adult patients. The findings of this study contribute to accurate diagnostic inferences and to prevention of respiratory complications in these patients.
RESUMO Objetivos: analisar a acurácia dos indicadores clínicos de desobstrução ineficaz de vias aéreas em pacientes de unidade de terapia intensiva adulto. Métodos: estudo de acurácia diagnóstica em unidade de terapia intensiva de um hospital universitário do nordeste do Brasil. Amostra de 104 pacientes internados entre junho e outubro de 2019. Resultados: a prevalência de desobstrução ineficaz de vias aéreas foi de 36,54%. Os indicadores com alta especificidade foram ausência de tosse (0,8326), ortopneia (0,6817), sons respiratórios adventícios (0,8175) e sons respiratórios diminuídos (0,8326). Os indicadores clínicos com alta sensibilidade e especificidade foram alteração na frequência respiratória (0,9999) e alteração no padrão respiratório (0,9999). Conclusões: seis indicadores clínicos forneceram identificação precisa da desobstrução ineficaz de vias aéreas. Os indicadores clínicos alteração na frequência respiratória e alteração no padrão respiratório foram os mais precisos para pacientes críticos. Os achados contribuem para inferências diagnósticas precisas e para prevenção de complicações respiratórias nesses pacientes.
RESUMEN Objetivos: analizar la precisión de indicadores clínicos de limpieza ineficaz de las vías aéreas en pacientes de unidades de cuidados intensivos adulto. Métodos: estudio de precisión diagnóstica en unidad de cuidados intensivos de hospital universitario en noreste brasileño. Muestra de 104 pacientes hospitalizados entre junio y octubre de 2019. Resultados: prevalencia de limpieza ineficaz de las vías aéreas del 36,54%. Indicadores con alta especificidad; ausencia de tos (0,8326), ortopnea (0,6817), ruidos respiratorios adventicios (0,8175) y ruidos respiratorios disminuidos (0,8326). Indicadores clínicos con alta sensibilidad y especificidad; cambio en la frecuencia respiratoria (0,9999) y cambio en el patrón de respiración (0,9999). Conclusiones: seis indicadores clínicos proporcionaron identificación precisa de la limpieza ineficaz de las vías aéreas; cambio en la frecuencia respiratoria y cambio en el patrón de respiración fueron los más precisos para pacientes críticos. Nuestros hallazgos contribuyen a inferencias diagnósticas precisas y la prevención de complicaciones respiratorias en estos pacientes.
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Big data has been a game changer of machine learning. But, big data is a form of centralized version of data only available and accessible to the technology giants. A way to decentralize this data and make machine learning accessible to the smaller organizations is via the blockchain technology. This peer?to?peer network creates a common database accessible to those in the network. Furthermore, blockchain helps in securing the digital data and prevents data tampering due to human interactions. This technology keeps a constant track of the document in terms of creation, editing, etc., and makes this information accessible to all. It is a chain of data being distributed across many computers, with a database containing details about each transaction. This record helps in data security and prevents data modification. This technology also helps create big data from multiple sources of small data paving way for creating a well serving artificial intelligence model. Here in this manuscript, we discuss about the usage of blockchain, its current role in machine learning and challenges faced by it
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Abstract Introduction: This study examines early- and long-term outcomes of mitral valve repairs in a low-volume cardiac surgery centre in the Caribbean. Methods: Ninety-six consecutive patients underwent mitral valve repair from April 2009 to December 2018. Patients were divided into two groups: functional mitral regurgitation requiring simple mitral annuloplasty (FMR, n=63) or structural degenerative mitral regurgitation requiring more complex repair (DMR, n=33). Data collected prospectively were retrospectively analysed from the unit-maintained cardiac surgery database. Results: Thirty-day mortality in the whole series was 2.1%, with 3% in the FMR group and 0% in the DMR group. Early post-operative echocardiography in the FMR group demonstrated 51 patients (83.6%) without mitral regurgitation, 8 patients (13.1%) with trivial to mild regurgitation, and 2 patients (3.3%) with moderate regurgitation. However, at a mean follow-up of 98.2±50.8, only 21 patients (42.8%) were in NYHA class I, with 7 (14.2%) in class II, 16 (32.6%) in class III, and 5 (10.2%) in class IV. There were 9 cardiac-related deaths at final follow-up, with freedom from re-operation and survival of 98% and 75.6%, respectively. In the DMR group, early post-operative echocardiography demonstrated 29 patients (87.9%) without mitral regurgitation, 3 patients (9.1%) with trivial regurgitation and 1 patient (3.0%) with mild regurgitation. At a mean follow-up of 114.1±25.4 months, there was a good functional post-operative status in this group with 93.3% in NYHA class I, and 6.7% in class II. No patient required reintervention, 96.3% of patients had mild or no mitral regurgitation and survival was 90.9%. Conclusion: Despite challenges of maintaining skills in a low-volume centre, mitral valve repair can be performed safely with good early- and long-term results.
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RESUMEN Fundamento: existen muchas herramientas computacionales para administrar imágenes y conjuntos de datos; reducir la dimensión de estos favorece el manejo de la información. Objetivo: reducir la dimensión de un conjunto de datos para un mejor manejo de la información. Métodos: se utilizó el conjunto de datos de Breast Cancer Wisconsin (información de biopsias - células nucleares) y la plataforma Python Jupyter. Se implementaron técnicas de análisis de la componente principal (PCA) y Kernel PCA (kPCA) para reducir la dimensión a 2, 4, 6. Se hizo una validación cruzada para seleccionar los mejores hiperparámetros de los algoritmos de máquina de vectores de soporte y regresión logística. La clasificación se realizó con el training test original, training test (PCA y kPCA) y training test (datos transformados de PCA y kPCA). Se analizó la exactitud, precisión, exhaustividad, recuperación y el área bajo la curva. Resultados: la PCA con seis componentes explicó la tasa de variación casi en 90 %. Los mejores hiperparámetros hallados para máquina de soporte de vectores: kernel lineal y C = 100, para regresión logística fueron C = 100, Newton-cg solución (solver) e I2. Los mejores resultados de las métricas fueron para PCA 2 y 4(0,99; 0,99; 1; 0,99; 0,99). Para el training set con datos originales fueron 0,96; 0,95; 0,99; 0,97; 0,95. Para regresión logística los mejores resultados fueron para kPCA con seis componentes. Los resultados estadísticos fueron iguales a 1. Para el training set con datos originales, esos valores fueron 0,96; 0,95; 0,99; 0,97; 0.95. Conclusiones: los resultados de las métricas mejoraron utilizando PCA y kPCA.
ABSTRACT Background: there are many computational tools for managing images and data sets; reducing the size of these favors the management of information. Objective: reduce the data set size for better information management. Methods: the Breast Cancer Wisconsin data set (biopsy information - nuclear cells) and the Python Jupyter platform were used. Principal Component Analysis (PCA) and Kernel PCA (kPCA) techniques were implemented to reduce the dimension to 2, 4, 6. Cross-validation was made to select the best hyperparameters of the regression and support vector machine algorithms Logistics. The classification was carried out with the original training test, training test (PCA and kPCA) and training test (data transformed from PCA and kPCA). Accuracy, precision, completeness, recovery, and area under the curve were analyzed. Results: the PCA with six components explained the variation rate by almost 90%. The best hyperparameters found for the vector support machine: linear kernel and C = 100, for logistic regression were C = 100, Newton-cg solution (solver) and I2. The best results of the metrics were for PCA 2 and 4 (0.99, 0.99, 1, 0.99, 0.99). For the training set with original data they were 0.96; 0.95; 0.99; 0.97; 0.95. For logistic regression the best results were for kPCA with 6 components. The statistical results were equal to 1. For the training set with original data, these values were 0.96; 0.95; 0.99; 0.97; 0.95. Conclusions: the results of the metrics improved using PCA and kPCA.
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ABSTRACT BACKGROUND: Multiple opinion-based communications have highlighted the actions of the Brazilian government during the pandemic. Nevertheless, none have appraised public data to identify factors associated with worsening of the healthcare system. OBJECTIVE: To analyze and collate data from public health and treasury information systems in order to understand the escalating process of weakening of Brazilian healthcare and welfare since the beginning of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic. DESIGN AND SETTING: Secondary data study conducted using multiple public databases administered by the Brazilian federal government. METHODS: We processed information from multiple national databases and appraised health and economic-related data. RESULTS: Based on our analyses, there were substantial reductions in inpatient hospital admissions and in the numbers of patients seeking primary care services, along with a decrease in immunization coverage. Moreover, we observed a considerable decline in government transfers to hospital services (reduction of 82.0%) and a diminution of public outlays in several healthcare-related subfunctions ("hospital and outpatient care", "primary care", "prophylactic and therapeutic support" and "epidemiological surveillance"). We observed an increase in the overall mortality rate over the period analyzed, especially regarding all group-based diseases. Notably, there were remarkable differences among geographic, racial, gender and other parameters, thus revealing the impact of vulnerabilities on COVID-19 outcomes. CONCLUSION: This assessment of documentation of public expenditure and the shrinkage of investment in sensitive areas of the healthcare system in Brazil emphasized areas that still require collective attention in order to guarantee national welfare.
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COVID-19 , Brasil/epidemiologia , Gastos em Saúde , SARS-CoV-2 , HospitalizaçãoRESUMO
Objective:By analyzing the biomedical papers retracted due to the reason that " original data not provided" , to discuss the necessity of preventing scientific data misconduct and the feasible solutions for its management.Methods:Data of the international papers that were published from Jan 2011 to Dec 2021 and retracted due to " original data not provided" were retrieved from Retraction Watch Database. The data of time distribution, institution, journal sources, reasons for retraction, and disciplinary distribution were statistically analyzed and visually processed by using software packages of Excel, Python 3.7, Gephi 0.92.Results:A total number of 529 papers published in the biomedical field were retracted due to " original data not provided" , and the time of publication and retraction occurred mainly in 2019 (27.41%) and 2021 (41.97%). In addition to the reason " original data not provided" used as search term, the reasons for withdrawal were mainly data and image problems caused by scientific data misconduct, and reasons related to the discovery and investigation process of the paper, and these reasons had a strong co-linear relationship. Besides, the 4 disciplinary of biology-cellular, biology-cancer, genetics, medicine-oncology also had a strong co-linear relationship.Conclusions:It is necessary to incorporating scientific research data management into the scientific research code of conduct, strengthen the training on the code of conduct for original scientific research records keeping, establish the scientific research data review mechanism, and promote the prevention and governance of scientific research data misconduct in the biomedical field.
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Cost data caliber governance is key to fine cost management. To tackle the troubles in cost data management at multiple campuses of one hospital, the authors built a multi-campus cost data caliber governance mode. By means of enhanced top-level design, the mode carried out data governance by such measures as the establishment of data dictionary mapping library, standardizing department names and caliber, classification of charging items of medical services, precisely matching between fixed assets and charging items, interconnecting the management system of charging library and the procurement library of consumables, as well as precisely matching surgical disease types and charging items. These measures accomplished the consistency and comparability of cost data across campuses, building an automated, streamlined, standardized and integrated data governance mode for reference of hospitals with multiple campuses in need of cost management.
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With the enormous resources having been invested in oncology drugs development in China in recent years, the Center for Drug Evaluation (CDE) of National Medical Products Administration has been issuing a number of technical guidelines to further standardize the requirements on implementation and registration of domestic oncology clinical trials. As data is the cornerstone of clinical trials, data integrity and quality will directly decide the outcome of clinical studies. Given the specific characteristics of oncology therapeutic clinical trials, and combined with the clinical data standards established by the Clinical Data Interchange Standards Consortium (CDISC) and the issued industrial guidelines, this article introduces the general considerations of clinical data management for oncology clinical trials, with the aim of emphasizing normative data collection and timely data monitoring to ensure the data quality and reliability of results of the study. This article discusses the impact of complex study design on CRF, design CRF according to CDASH, develop DVP scientifically, rolling submissions and data cut-off.
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Este estudo aborda o tema de sistemas de informação utilizados na gestão de recursos humanos em saúde na Secretaria de Estado de Saúde do Rio de Janeiro (SES/RJ), órgão da Administração Direta do Poder Executivo do Estado. A SES/RJ é responsável por definir políticas de saúde no Estado, a qual utiliza vários sistemas de informação para gestão de sua força de trabalho, com evidências de fragmentação dos dados, dificuldade na gestão das informações e prejuízo na definição de estratégias. Nesse sentido, este trabalho tem como objetivo descrever os sistemas de informação de recursos humanos em uso na SES/RJ, no contexto dos modelos de gestão adotados em suas unidades de saúde, e contribuir para melhorar a gestão de recursos humanos e das informações geradas no âmbito da instituição, fornecendo subsídios para o processo de tomada de decisão. Para tanto, fez-se, primeiramente, uma revisão bibliográfica sobre o tema desde o ano de 1995, período da Reforma do Estado, e uma pesquisa documental em portais e legislações, tanto da SES/RJ como de outros órgãos estaduais, assim como das esferas federal e municipal. Em seguida, o trabalho discute as possibilidades e os subsídios que possam favorecer a interoperabilidade desses sistemas e, assim, facilitar a gestão da força de trabalho na instituição.
This study investigates the use of information systems in the administration of human resources in health at the Rio de Janeiro State Department of Health (SES/RJ), which is part of the Direct Administration of the State Government. SES/RJ oversees establishing state health policies and managing its staff using a variety of information systems, with evidence of data fragmentation, information management challenges, and strategy development impairment. In this sense, this study aims to describe the human resources information systems in use at SES/RJ in relation to the management models used in its health units, as well as to contribute to improving human resources management and the information generated within the institution by providing decision-making inputs. To that end, we conducted a bibliographic review of the topic dating back to 1995, during the State Reform period, as well as document search in the portals and legislation of SES/RJ and other state agencies, as well as federal and municipal domains. The study then moves on to the possibilities and advantages that may encourage system interoperability and, as a result, make labor management in the institution easier.
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Gestão de Recursos Humanos , Sistemas de Informação , Saúde Pública , Registros Eletrônicos de Saúde , Mão de Obra em Saúde , BrasilRESUMO
INTRODUCCIÓN: La Fibrosis Pulmonar Idiopática (FPI) es una de las enfermedades respiratorias crónicas del adulto de mayor impacto y letalidad, diversos estudios epidemiológicos muestran tendencias progresivas al aumento de las tasas de mortalidad por FPI. En Chile no existen reportes sobre las tendencias de las tasas de mortalidad por FPI. El objetivo del presente estudio es determinar las tendencias de la mortalidad por FPI en Chile entre los años 2002 y 2015. MÉTODO: Estudio descriptivo de diseño ecológico, a partir de la información de bases de datos secundarias de libre disposición de las estadísticas vitales del Departamento de Estadísticas e Información de Salud (DEIS) y del Instituto Nacional de Estadísticas (INE) de Ministerio de Salud de Chile entre los años 2002 y 2015 se obtuvieron las tasas crudas de mortalidad por fibrosis pulmonar idiopática en población de 45 años y más en ambos sexos y las tasas ajustadas por sexo y edad por regiones, se calculó también la frecuencia mensual de las muertes por FPI y se compararon las tasas medias de mortalidad por regiones. RESULTADOS: Se observó un incremento progresivo de la tasa nacional cruda de mortalidad por FPI entre los años 2002 a 2015, la que fue de 18,5 fallecidos por 100.000 habitantes en el año 2002 hasta 24,6 fallecidos por 100.000 habitantes en el año 2015 con una pendiente de ascenso por año de +0,27 por 100.000 habitantes (p = 0,013). En las mujeres las tasas fueron más altas que en los hombres, pero las pendientes de ascenso no presentaron diferencias entre sexos. En la gran mayoría de las regiones las tasas ajustadas presentaron tendencias significativas al ascenso y las tasas medias más altas se presentaron en las regiones del norte de Chile. Se observó un comportamiento estacional de las muertes siendo las frecuencias más altas en los meses de invierno. CONCLUSIONES: Las tasas de mortalidad por FPI en Chile presentan una tendencia progresiva al aumento, con marcadas diferencias regionales lo que lleva a considerar, entre otros factores, influencia ambiental y contaminación del aire y de suelos que se debieran investigar para poder realizar intervenciones de salud pública que permitan reducir la mortalidad de esta enfermedad en nuestro país.
BACKGROUND: Idiopathic Pulmonary Fibrosis (IPF) is one of the chronic respiratory diseases in adults with the greatest impact and high case fatality rate. Various epidemiological studies show progressive trends towards increasing IPF mortality rates. In Chile there are no national reports on country and regional trends in IPF mortality rates. The objective of this study is to determine trends in mortality due to IPF in Chile from year 2002 to 2015. METHOD: Epidemiological study of ecological design based on information from public databases of vital statistics of the Department of Health Statistics and Information (DEIS) and the National Institute of Statistics (INE) of the Ministry of Health of Chile. Crude mortality rates due to IPF in the population aged 45 years and over in both sexes were obtained from years 2002 to 2015. Besides the adjusted mortality rates for sex and age by region, the monthly frequency of IPF deaths during the same period and the average mortality rates by Chilean regions were calculated. RESULTS: A progressive increasing trend in the crude national IPF mortality rate was observed between years 2002 to 2015, which went from 18.5 deaths per 100,000 inhabitants in 2002 to 24.6 deaths per 100,000 inhabitants in 2015 with a slope of ascent per year of +0.27 per 100,000 inhabitants (p = 0.013); female rates were higher than men rates, but without differences in the slopes between sexes; in the vast majority of the regions the rates showed significant upward trends with the higher ones in the northern regions of Chile. A seasonal behavior of the death's frequency was observed being the highest in the winter term. CONCLUSIONS: Mortality rates due to IPF in Chile show a progressive upward trend, with marked regional differences which leads to consider, among other factors, environmental influence and air and soil contamination that should be investigated to carry out public health interventions that allow reducing the mortality of this disease in our country.
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Masculino , Feminino , Pessoa de Meia-Idade , Idoso , Idoso de 80 Anos ou mais , Fibrose Pulmonar Idiopática/mortalidade , Estações do Ano , Chile/epidemiologia , Epidemiologia Descritiva , Estatísticas Vitais , Mortalidade/tendências , Distribuição por Sexo , Estudos EcológicosRESUMO
The FAIR principles have become a data management instrument for the academic and scientific community, since they provide a set of guiding principles to bring findability, accessibility, interoperability and reusability to data and metadata stewardship. Since their official publication in 2016 by Scientific Data Nature, these principles have received worldwide recognition and have been quickly endorsed and adopted as a cornerstone of data stewardship and research policy. However, when put into practice, they occasionally result in organisational, legal and technological challenges that can lead to doubts and uncertainty as to whether the effort of implementing them is worthwhile. Soon after their publication, the European Commission and other funding agencies started to require that project proposals include a Data Management Plan (DMP) based on the FAIR principles. This paper reports on the adherence of DMPs to the FAIR principles, critically evaluating ten European DMP templates. We observed that the current FAIRness of most of these DMPs is only partly satisfactory, in that they address data best practices, findability, accessibility and sometimes preservation, but pay much less attention to metadata and interoperability.
Os princípios FAIR tornaram-se um instrumento de gestão de dados para a comunidade acadêmica e científica, uma vez que fornecem um conjunto de princípios orientadores que facilitam a localização, acessibilidade, interoperabilidade e reutilização de dados e metadados. Desde sua publicação oficial em 2016 pela Scientific Data - Nature, esses princípios receberam reconhecimento mundial e foram rapidamente endossados e adotados como pilares da gestão de dados e das políticas de pesquisa. No entanto, quando postos em prática, apresentam ocasionalmente desafios organizacionais, jurídicos e tecnológicos que podem levar a dúvidas e incertezas quanto ao esforço em implementá-los. Logo após sua publicação, a Comissão Europeia e outras agências de financiamento começaram a exigir nas suas propostas de projetos um Plano de Gestão de Dados (PGD) com base nos princípios da FAIR. Este artigo relata a aderência dos PGDs aos princípios FAIR, avaliando criticamente dez modelos europeus de PGD. Observamos que o nível de FAIRness da maioria dos PGDs analisados ainda é parcialmente satisfatório, uma vez que abordam as melhores práticas de dados, localização, acessibilidade e, às vezes, preservação, mas dão pouca atenção aos metadados e a interoperabilidade.
Los principios FAIR se han convertido en una herramienta de gestión de datos para la comunidad académica y científica, ya que proporcionan un conjunto de principios rectores que facilitan la localización, accesibilidad, interoperabilidad y reutilización de la gestión de datos y metadatos. Desde su publicación oficial en 2016 por Scientific Data - Nature, estos principios han recibido reconocimiento mundial y fueron rápidamente respaldados y adoptados como pilares de la política de investigación y gestión de datos. Sin embargo, cuando se ponen en práctica, ocasionalmente presentan desafíos organizativos, legales y tecnológicos que pueden generar dudas e incertidumbres sobre el esfuerzo para implementarlos. Poco después de su publicación, la Comisión Europea y otras agencias de financiación comenzaron a exigir en sus propuestas de proyectos un Plan de Gestión de Datos (PGD) basado en los principios de FAIR. Este artículo informa sobre la adherencia de los PGD a los principios FAIR, evaluando críticamente diez modelos europeos de PGD. Observamos que el nivel de FAIRness de la mayoría de los PGD analizados sigue siendo parcialmente insatisfactorio, ya que abordan las mejores prácticas de datos, ubicación, accesibilidad y, a veces, preservación, pero prestan poca atención a los metadatos y la interoperabilidad.