Levantamento Rápido de Índices para Aedes Aegypti (LIRAa)

Capacitação sobre o Levantamento Rápido de Índices para Aedes Aegypti (LIRAa) Responsáveis: Gerência de Vigilância das Arboviroses Gerência de Vigilância e Controle das Doenças Tropicais Negligenciadas Diretoria de Vigilância das Doenças Vetoriais e Zoonoses (DVDVZ) Superintendência de Vigilância em Saúde (SVS) Secretaria de Estado da Saúde do Tocantins (SES-TO)

Costos totales asociados a úlceras por presión y caídas en usuarios de los servicios clínicos de cirugía y medicina, en un establecimiento de alta complejidad, primer semestre del 2017 y primer semestre 2018, Chile / Total costs associated with pressure ulcers and falls in users of clinical surgery and medical services, in a highly complex establishment, first half of 2017 and first semester 2018, Chile

INTRODUCCIÓN: las actividades asistenciales relacionadas con la atención de pacientes en servicios clínicos tienen diferentes grados de riesgos para las personas que los reciben, el error en la atención sanitaria se denomina evento adverso y/o centinelas los que, según su gravedad, pueden llegar a causar la muerte de los usuarios. OBJETIVO: determinar los costos totales de úlceras por presión y caídas ocurridos en los usuarios de los servicios clínicos de cirugía y medicina en un establecimiento de alta complejidad durante el primer semestre del 2017 y primer semestre del 2018, en Chile. MÉTODO: estudio descriptivo retrospectivo. La ocurrencia de eventos relacionados a úlceras por presión y caídas son notificados a través del sistema informático Phoenix y son recepcionados por el Departamento de Calidad y Seguridad del Paciente del establecimiento, los datos económicos fueron proporcionados por el departamento de Finanzas. Los datos fueron procesados por programa computacional Excel. RESULTADOS: los costos totales asociado a úlceras por presión y caídas:Servicio de Cirugía, primer semestre del 2017:-Ulceras por presión $44.086.872 (U$ 57.557 dólares)-Caídas $39.630.517 (U$51.739 dólares)-Costo total $ 83.717.389 (U$109.297 dólares)Servicio de Medicina, primer semestre del 2017:-Úlceras por presión $22.654.894 (U$29.803 dólares)-Caídas $32.023.185 (U$41.807 dólares)-Costo total $ 54.678.079 (U$71.385 dólares)Servicio de Cirugía, primer semestre del 2018:-Ulceras por presión $76.979.440 (U$100.500 dólares)-Caídas $18.522.927 (U$24.182 dólares)-Costo total $ 95.502.367 (U$124.683 dólares)Servicio de Medicina, primer semestre del 2018:-Ulceras por presión $14.981.255 (U$19.558 dólares)-Caídas $55.258.625 (U$72.142 dólares)-Costo total $ 70.239.880 (U$91.701 dólares) CONCLUSIÓN: se logró levantar información actual sobre los recursos financieros y clínicos que determinan el impacto económico que generan los eventos adversos en los pacientes atendidos en un centro asistencial público. Es por esto, que el presente estudio, permitió cuantificar y evidenciar el impacto económico de dos eventos ocurridos en los servicios clínicos de un hospital de alta complejidad de Chile.

INTRODUCTION: healthcare activities related to the care of patients in clinical services, have different degrees of risks for the people who receive them, the error in health care is called an adverse event and / or sentinels which, depending on their severity, can arrive to cause the death of users. OBJECTIVE: to determine the total costs of pressure ulcers and falls that occurred in users of clinical services of surgery and medicine in a highly complex establishment during the first half of 2017 and the first half of 2018, in Chile. METHOD: retrospective descriptive study. The occurrence of events related to pressure ulcers and falls are notified through the Phoenix computer system and are received by the Department of Quality and Patient Safety of the establishment, the economic data were provided by the Department of Finance. The data were processed by Excel computer program. RESULTS: the total costs associated with pressure ulcers and falls:Surgery Service, first semester of 2017: -Pressure ulcers $ 44,086,872 (U$ 57,557)-Falls $ 39,630,517 (U$ 51,739) -Total cost$ 83,717,389 (U$ 109,297)Medicine Service, first semester of 2017: -Pressure ulcers $ 22,654,894 (U$29,803 dollars) -Falls $ 32,023,185 (U$41,807 dollars) -Total cost $ 54,678,079 (U$71,385 dollars)Surgery Service, first semester of 2018: -Pressure ulcers $ 76,979,440 (U$100,500 dollars) -Falls $ 18,522,927 (U$24,182 dollars) -Total cost $ 95,502,367 (U$124,683 dollars)Medicine Service, first semester of 2018: -Pressure ulcers $ 14,981,255 (U$19,558 dollars) -Falls $ 55,258,625 (U$72,142dollars) -Total cost $ 70,239,880 (U$91,701 dollars) CONCLUSIONS: it was possible to collect current information on financial and clinical resources that determine the economic impact generated by adverse events in patients treated in a public healthcare center. This is why the present study made it possible to quantify and demonstrate the economic impact of two events that occurred in the clinical services of a highly complex hospital in Chile.

Factores que Afectan la Duración de los Tratamientos de Ortodoncia en un Servicio Público de Salud / Factors that Affect the Duration of Orthodontic Treatment in Public Health Services

RESUMEN: La duración de los tratamientos de ortodoncia siempre ha sido una de las mayores preocupaciones, tanto en los pacientes como en los Ortodoncistas. El proposito de esta investigacion fue determinar la magnitud de las inasistencias a los controles por parte de los pacientes y como estas y otras variables, influyen en la duración de los tratamientos de Ortodoncia en el Centro de Salud Familiar (CESFAM) Dr. Victor Manuel Fernandez, Servicio de Salud de Concepcion, Chile. Se realizo un estudio descriptivo, de tipo transversal, retrospectivo, en el que se utilizaron las fichas clínicas de todos los pacientes que fueron dados de alta por los Ortodoncistas del CESFAM Dr. V. M. F. durante el año 2017. La tabulación se realizó en Microsoft Excel y el análisis estadístico se hizo en InfoStat 17. Se incluyeron 246 pacientes, con una edad de ingreso promedio de 13,6 años. La maloclusion predominante fue la Clase I de Angle (71 %). Estos pacientes tuvieron una duracion de tratamiento promedio de 33,9 meses. Se concluyó que a mayor cantidad de inasistencias, el tratamiento de ortodoncia tuvo una duración mayor.

ABSTRACT: The duration of orthodontic treatments has always been one of the biggest concerns, both in patients and for orthodontists. The purpose of this investigation was to determine the magnitude of the absences to the controls of the patients and how they influence the duration of the orthodontic treatments in the CESFAM Dr. Victor Manuel Fernandez, Concepcion, Chile. A descriptive, cross-sectional, retrospective study was carried out, in which the clinical records of all patients discharged by the Orthodontists of CESFAM Dr. V.M.F. during the year 2017 were analyzed. The tabulation was performed in Microsoft Excel and the statistical analysis was carried out in InfoStat 17. In total, 246 patients were included, with an average age of admission of 13.6 years. The predominant malocclusion was Class I of Angle (71 %). These patients had an average treatment duration of 33.9 months. It was further concluded that the length of orthodontic treatment, was also affected by the increased number of times patients failed to show for treatment.

Design of Knowledge Bases for Plant Gene Regulatory Networks.

Developing a knowledge base that contains all the information necessary for the researcher studying gene regulation in a particular organism can be accomplished in four stages. This begins with defining the data scope. We describe here the necessary information and resources, and outline the methods for obtaining data. The second stage consists of designing the schema, which involves defining the entire arrangement of the database in a systematic plan. The third stage is the implementation, defined by actualization of the database by using software according to a predefined schema. The final stage is development, where the database is made available to users in a web-accessible system. The result is a knowledgebase that integrates all the information pertaining to gene regulation, and which is easily expandable and transferable.

Data science, learning, and applications to biomedical and health sciences.

The last decade has seen an unprecedented increase in the volume and variety of electronic data related to research and development, health records, and patient self-tracking, collectively referred to as Big Data. Properly harnessed, Big Data can provide insights and drive discovery that will accelerate biomedical advances, improve patient outcomes, and reduce costs. However, the considerable potential of Big Data remains unrealized owing to obstacles including a limited ability to standardize and consolidate data and challenges in sharing data, among a variety of sources, providers, and facilities. Here, we discuss some of these challenges and potential solutions, as well as initiatives that are already underway to take advantage of Big Data.

Distributed data networks: a blueprint for Big Data sharing and healthcare analytics.

This paper defines the attributes of distributed data networks and outlines the data and analytic infrastructure needed to build and maintain a successful network. We use examples from one successful implementation of a large-scale, multisite, healthcare-related distributed data network, the U.S. Food and Drug Administration-sponsored Sentinel Initiative. Analytic infrastructure-development concepts are discussed from the perspective of promoting six pillars of analytic infrastructure: consistency, reusability, flexibility, scalability, transparency, and reproducibility. This paper also introduces one use case for machine learning algorithm development to fully utilize and advance the portfolio of population health analytics, particularly those using multisite administrative data sources.

A modular informatics platform for effective support of collaborative and multicenter studies in cardiology.

Collaborative and multicenter studies permit a large number of patients to be enrolled within a reasonable time and providing the opportunity to collect different data. Informatics platforms play an important role in management, storage, and exchange of data between the participants involved in the study. In this article, we describe a modular informatics platform designed and developed to support collaborative and multicenter studies in cardiology. In each developed module, data management is implemented following local defined protocols. The modular characteristic of the developed platform allows independent transfer of different kinds of data, such as biological samples, imaging raw data, and patients' digital information. Moreover, it offers safe central storage of the data collected during the study. The developed platform was successfully tested during a European collaborative and multicenter study, focused on evaluating multimodal non-invasive imaging to diagnose and characterize ischemic heart disease.

Estrés psicológico y problemática musculoesquelética. Revisión sistemática / Psychological stress and musculoskeletal problems. Systematic review

Objetivo. Analizar los diseños epidemiológicos más utilizados en el estudio de la relación entre estrés psicológico y problemática musculoesquelética. Metodología. Búsqueda bibliográfica con criterios de inclusión y exclusión específicos, en PubMed/Medline, EBSCOhost y revistas electrónicas de diversas disciplinas siguiendo las recomendaciones del estándar PRISMA. Se extrajeron 2782 artículos de los cuales fueron seleccionados 41 para la revisión. Resultados. Más del 80% de los estudios confirmaron la relación entre estrés psicológico y problemática musculoesquelética, determinando que los niveles de estrés mantenidos aumentan el riesgo de aparición de sintomatología, sobre todo en lumbares y cervicales. Del total de estudios, más del 50% fueron de diseño transversal y 77% sobre temática laboral. La población más vulnerable fue la femenina, especialmente funcionarios y trabajadores de oficina. Las “Demandas laborales” constituyeron el estresor psicosocial más descrito. Respecto a los instrumentos de medición más usados, destacan el “Stress Energy Questionnaire”, el “Job Content Questionnaire” y el “Standardized Nordic Musculoskeletal Questionnaire”. Conclusión: Los estudios sobre estrés psicológico y problemática musculoesquelética tienen diseños y resultados heterogéneos. Los hallazgos resaltaron múltiples estresores psicosociales y áreas corporales afectadas, siendo escasos los consensos en diagnósticos e instrumentos de medida. Aunque aparece una asociación entre estrés psicológico y problemas musculo esqueléticos, no se vislumbran relaciones causales claras. Dado el elevado coste de estos problemas, se considera necesario realizar más estudios con diseños y metodologías rigurosas (AU)

Objective: Analyze the epidemiological approach more used in the study of the relationship between psychological stress and musculoskeletal problems. Methodology: Bibliographic research with specific inclusion and exclusion criteria on PubMed / Medline, EBSCOhost and electronic journals from diverse disciplines following the recommendations of PRISMA standards. 2782 articles were extracted, of which 41 were selected for the revision. Results: More than 80% of the articles confirmed that maintained stress levels increase the risk of developing musculoskeletal symptoms, especially in the lower back and neck. Over 50% of the studies followed a transversal design, and 77% of them dealt with labour issues. The most vulnerable population were women working in civil service or white collars, and labour demands was the most described psychosocial stressor. Regarding measurement instruments, the most used were the Energy Stress Questionnaire, the Job Content Questionnaire, and the Standardized Nordic Musculoskeletal Questionnaire. Conclusion: Studies on psychological stress and musculoskeletal problems had heterogeneous results and designs. The findings highlight multiple psychosocial stressors and body areas affected and there was little consensus on diagnosis and measuring instruments. Although there was an association between psychological stress and musculoskeletal problems, their causal relationships are unclear. Given the higher cost of this problem, it is necessary to develop more studies with designs and rigorous methodologies (AU)

Brain Tumor Database, a free relational database for collection and analysis of brain tumor patient information.

In this study, we describe the development and utilization of a relational database designed to manage the clinical and radiological data of patients with brain tumors. The Brain Tumor Database was implemented using MySQL v.5.0, while the graphical user interface was created using PHP and HTML, thus making it easily accessible through a web browser. This web-based approach allows for multiple institutions to potentially access the database. The BT Database can record brain tumor patient information (e.g. clinical features, anatomical attributes, and radiological characteristics) and be used for clinical and research purposes. Analytic tools to automatically generate statistics and different plots are provided. The BT Database is a free and powerful user-friendly tool with a wide range of possible clinical and research applications in neurology and neurosurgery. The BT Database graphical user interface source code and manual are freely available at http://tumorsdatabase.altervista.org.

Active in-database processing to support ambient assisted living systems.

As an alternative to the existing software architectures that underpin the development of smart homes and ambient assisted living (AAL) systems, this work presents a database-centric architecture that takes advantage of active databases and in-database processing. Current platforms supporting AAL systems use database management systems (DBMSs) exclusively for data storage. Active databases employ database triggers to detect and react to events taking place inside or outside of the database. DBMSs can be extended with stored procedures and functions that enable in-database processing. This means that the data processing is integrated and performed within the DBMS. The feasibility and flexibility of the proposed approach were demonstrated with the implementation of three distinct AAL services. The active database was used to detect bed-exits and to discover common room transitions and deviations during the night. In-database machine learning methods were used to model early night behaviors. Consequently, active in-database processing avoids transferring sensitive data outside the database, and this improves performance, security and privacy. Furthermore, centralizing the computation into the DBMS facilitates code reuse, adaptation and maintenance. These are important system properties that take into account the evolving heterogeneity of users, their needs and the devices that are characteristic of smart homes and AAL systems. Therefore, DBMSs can provide capabilities to address requirements for scalability, security, privacy, dependability and personalization in applications of smart environments in healthcare.

[Automatic analysis pipeline of next-generation sequencing data].

The development of next-generation sequencing has generated high demand for data processing and analysis. Although there are a lot of software for analyzing next-generation sequencing data, most of them are designed for one specific function (e.g., alignment, variant calling or annotation). Therefore, it is necessary to combine them together for data analysis and to generate interpretable results for biologists. This study designed a pipeline to process Illumina sequencing data based on Perl programming language and SGE system. The pipeline takes original sequence data (fastq format) as input, calls the standard data processing software (e.g., BWA, Samtools, GATK, and Annovar), and finally outputs a list of annotated variants that researchers can further analyze. The pipeline simplifies the manual operation and improves the efficiency by automatization and parallel computation. Users can easily run the pipeline by editing the configuration file or clicking the graphical interface. Our work will facilitate the research projects using the sequencing technology.

Towards large-scale data analysis: challenges in the design of portable systems and use of Cloud computing.

Portable systems and global communications open a broad spectrum for new health applications. In the framework of electrophysiological applications, several challenges are faced when developing portable systems embedded in Cloud computing services. In order to facilitate new developers in this area based on our experience, five areas of interest are presented in this paper where strategies can be applied for improving the performance of portable systems: transducer and conditioning, processing, wireless communications, battery and power management. Likewise, for Cloud services, scalability, portability, privacy and security guidelines have been highlighted.

Managing large SNP datasets with SNPpy.

Using relational databases to manage SNP datasets is a very useful technique that has significant advantages over alternative methods, including the ability to leverage the power of relational databases to perform data validation, and the use of the powerful SQL query language to export data. SNPpy is a Python program which uses the PostgreSQL database and the SQLAlchemy Python library to automate SNP data management. This chapter shows how to use SNPpy to store and manage large datasets.

The Pathogen-annotated Tracking Resource Network (PATRN) system: a web-based resource to aid food safety, regulatory science, and investigations of foodborne pathogens and disease.

Investigation of foodborne diseases requires the capture and analysis of time-sensitive information on microbial pathogens that is derived from multiple analytical methods and sources. The web-based Pathogen-annotated Tracking Resource Network (PATRN) system (www.patrn.net) was developed to address the data aggregation, analysis, and communication needs important to the global food safety community for the investigation of foodborne disease. PATRN incorporates a standard vocabulary for describing isolate metadata and provides a representational schema for a prototypic data exchange standard using a novel data loading wizard for aggregation of assay and attribution information. PATRN currently houses expert-curated, high-quality "foundational datasets" consisting of published experimental results from conventional assays and next generation analysis platforms for isolates of Escherichia coli, Listeria monocytogenes, and Salmonella, Shigella, Vibrio and Cronobacter species. A suite of computational tools for data mining, clustering, and graphical representation is available. Within PATRN, the public curated data repository is complemented by a secure private workspace for user-driven analyses, and for sharing data among collaborators. To demonstrate the data curation, loading wizard features, and analytical capabilities of PATRN, three use-case scenarios are presented. Use-case scenario one is a comparison of the distribution and prevalence of plasmid-encoded virulence factor genes among 249 Cronobacter strains with similar attributes to that of nine Cronobacter isolates from recent cases obtained between March and October, 2010-2011. To highlight PATRN's data management and trend finding tools, analysis of datasets, stored in PATRN as part of an ongoing surveillance project to identify the predominant molecular serogroups among Cronobacter sakazakii isolates observed in the USA is shown. Use-case scenario two demonstrates the secure workspace available for private users to upload and analyze sensitive data, and for collating cross-platform datasets to identify and validate congruent datapoints. SNP datasets from WGS assemblies and pan-genome microarrays are analyzed in a combinatorial fashion to determine relatedness of 33 Salmonella enterica strains to six strains collected as part of an outbreak investigation. Use-case scenario three utilizes published surveillance results that describe the incidence and sources of O157:H7 E. coli isolates associated with a produce pre-harvest surveillance study that occurred during 2002-2006. In summary, PATRN is a web-based integrated platform containing tools for the management, analysis and visualization of data about foodborne pathogens.

Creating an infrastructure for high-throughput high-resolution cryogenic electron microscopy.

New instrumentation for three-dimensional electron microscopy is facilitating an increase in the throughput of data collection and reconstruction. The increase in throughput creates bottlenecks in the workflow for storing and processing the image data. Here we describe the creation and quantify the throughput of a high-throughput infrastructure supporting collection of three-dimensional data collection.

Detecting and resolving inconsistencies between domain experts' different perspectives on (classification) tasks.

OBJECTIVES: The work reported here focuses on developing novel techniques which enable an expert to detect inconsistencies in 2 (or more) perspectives that the expert might have on the same (classification) task. The high level task which the experts (physicians) had set themselves was to classify, on a 5-point severity scale (A-E), the hourly reports produced by an intensive care unit's patient management system. METHOD: The INSIGHT system has been developed to support domain experts exploring, and removing inconsistencies in their conceptualization of a task. We report here a study of intensive care physicians reconciling 2 perspectives on their patients. The 2 perspectives provided to INSIGHT were an annotated set of patient records where the expert had selected the appropriate category to describe that snapshot of the patient, and a set of rules which are able to classify the various time points on the same 5-point scale. Inconsistencies between these 2 perspectives are displayed as a confusion matrix; moreover INSIGHT then allows the expert to revise both the annotated datasets (correcting data errors, or changing the assigned categories) and the actual rule-set. RESULTS: Each of the 3 experts achieved a very high degree of consensus (~97%) between his refined knowledge sources (i.e., annotated hourly patient records and the rule-set). We then had the experts produce a common rule-set and then refine their several sets of annotations against it; this again resulted in inter-expert agreements of ~97%. The resulting rule-set can then be used in applications with considerable confidence. CONCLUSION: This study has shown that under some circumstances, it is possible for domain experts to achieve a high degree of correlation between 2 perspectives of the same task. The experts agreed that the immediate feedback provided by INSIGHT was a significant contribution to this successful outcome.

Experience implementing a point-of-care electronic medical record system for primary care in Malawi.

Due to the fact that health care professionals in Malawi are often overstretched, the use and quality of health data can be compromised. The Malawi Health Management Information System (HMIS) has streamlined data collection and reporting and increased the use of data to improve care. Obstacles remain, including incomplete reporting and low staff morale. With the Baobab Health Trust and the Malawi Ministry of Health, Partners In Health piloted an innovative point-of-care data system for primary care that functions alongside OpenMRS, an open source medical record platform. The system has given access to a patient-level primary care dataset in real time. Initial results highlight some of the benefits of a point-of-care system such as improved data quality, emphasize the importance of sharing data with clinical practitioners, and shed light on how this approach could strengthen HMIS.

Wildlife tracking data management: a new vision.

To date, the processing of wildlife location data has relied on a diversity of software and file formats. Data management and the following spatial and statistical analyses were undertaken in multiple steps, involving many time-consuming importing/exporting phases. Recent technological advancements in tracking systems have made large, continuous, high-frequency datasets of wildlife behavioural data available, such as those derived from the global positioning system (GPS) and other animal-attached sensor devices. These data can be further complemented by a wide range of other information about the animals' environment. Management of these large and diverse datasets for modelling animal behaviour and ecology can prove challenging, slowing down analysis and increasing the probability of mistakes in data handling. We address these issues by critically evaluating the requirements for good management of GPS data for wildlife biology. We highlight that dedicated data management tools and expertise are needed. We explore current research in wildlife data management. We suggest a general direction of development, based on a modular software architecture with a spatial database at its core, where interoperability, data model design and integration with remote-sensing data sources play an important role in successful GPS data handling.

Data management system in a movement disorder center: technical report.

OBJECTIVE: We designed a specialized monitoring unit and data management system with systematic storage and easy access for a deep brain stimulation program of patients with movement disorders. METHODS: All patients were monitored and evaluated in a specialized 24-hour monitoring system whenever it was needed, postoperatively as well as preoperatively. We digitized all the data and developed a data management system that allowed for systematic storage and easy access to the data on demand by users in the offices and outpatient clinics. CONCLUSION: We describe our data management system and how it provides benefit to patients in order that others may use it as a template for designing their own data management system.