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1.
Vaccine ; 35(48 Pt A): 6575-6581, 2017 12 04.
Artículo en Inglés | MEDLINE | ID: mdl-28479177

RESUMEN

Immunization of pregnant women is a promising public health strategy to reduce morbidity and mortality among both the mothers and their infants. Establishing safety and efficacy of vaccines generally uses a hybrid design between a conventional interventional study and an observational study that requires enrolling thousands of study participants to detect an unknown number of uncommon events. Historically, enrollment of pregnant women in clinical research studies encountered many barriers based on risk aversion, lack of knowledge, and regulatory ambiguity. Conducting research enrolling pregnant women in low- and middle-income countries can have additional factors to address such as limited availability of baseline epidemiologic data on disease burden and maternal and neonatal outcomes during and after pregnancy; challenges in recruiting and retaining pregnant women in research studies, variability in applying and interpreting assessment methods, and variability in locally acceptable and available infrastructure. Some measures to address these challenges include adjustment of study design, tailoring recruitment, consent process, retention strategies, operational and logistical processes, and the use of definitions and data collection methods that will align with efforts globally.


Asunto(s)
Investigación Biomédica/normas , Seguridad del Paciente/normas , Mujeres Embarazadas , Proyectos de Investigación , Vacunación , Ensayos Clínicos como Asunto , Países en Desarrollo , Femenino , Humanos , Consentimiento Informado , Selección de Paciente , Embarazo , Nivel de Atención , Revelación de la Verdad , Vacunas/efectos adversos , Vacunas/uso terapéutico
3.
Vaccine ; 34(49): 5993-5997, 2016 12 01.
Artículo en Inglés | MEDLINE | ID: mdl-27751641

RESUMEN

Immunization in pregnancy provides a promising contribution to globally reducing neonatal and under-five childhood mortality and morbidity. Thorough assessment of benefits and risks for the primarily healthy pregnant women and their unborn babies is required. The GAIA project was formed in response to the call of the World Health Organization for a globally concerted approach to actively monitor the safety of vaccines and immunization in pregnancy programs. GAIA aims to improve the quality of outcome data from clinical vaccine trials in pregnant women with a specific focus on the needs and requirements for safety monitoring in LMIC. In the first year of the project, a large and functional network of experts was created. The first outputs include a guidance document for clinical trials of immunization in pregnancy, a basic data collection guide, ten case definitions of key obstetric and neonatal health outcomes, an ontology of key terms and a map of pertinent disease codes. The GAIA Network is designed as an open and growing forum for professionals sharing the GAIA vision and aim. Based on the initial achievements, tools and services are developed to support investigators and strengthen immunization in pregnancy programs with specific focus on LMIC.


Asunto(s)
Salud Global , Inmunización/efectos adversos , Embarazo , Vacunas/efectos adversos , Ensayos Clínicos como Asunto , Femenino , Humanos , Vacunas/administración & dosificación , Organización Mundial de la Salud
4.
Genome Med ; 8(1): 71, 2016 06 23.
Artículo en Inglés | MEDLINE | ID: mdl-27338147

RESUMEN

Medicine and healthcare are undergoing profound changes. Whole-genome sequencing and high-resolution imaging technologies are key drivers of this rapid and crucial transformation. Technological innovation combined with automation and miniaturization has triggered an explosion in data production that will soon reach exabyte proportions. How are we going to deal with this exponential increase in data production? The potential of "big data" for improving health is enormous but, at the same time, we face a wide range of challenges to overcome urgently. Europe is very proud of its cultural diversity; however, exploitation of the data made available through advances in genomic medicine, imaging, and a wide range of mobile health applications or connected devices is hampered by numerous historical, technical, legal, and political barriers. European health systems and databases are diverse and fragmented. There is a lack of harmonization of data formats, processing, analysis, and data transfer, which leads to incompatibilities and lost opportunities. Legal frameworks for data sharing are evolving. Clinicians, researchers, and citizens need improved methods, tools, and training to generate, analyze, and query data effectively. Addressing these barriers will contribute to creating the European Single Market for health, which will improve health and healthcare for all Europeans.


Asunto(s)
Investigación Biomédica/legislación & jurisprudencia , Bases de Datos Factuales/normas , Unión Europea/organización & administración , Investigación Biomédica/normas , Bases de Datos Factuales/legislación & jurisprudencia , Implementación de Plan de Salud , Humanos , Difusión de la Información/legislación & jurisprudencia
5.
Stud Health Technol Inform ; 223: 93-9, 2016.
Artículo en Inglés | MEDLINE | ID: mdl-27139390

RESUMEN

The vast amount of clinical data in electronic health records constitutes a great potential for secondary use. However, most of this content consists of unstructured or semi-structured texts, which is difficult to process. Several challenges are still pending: medical language idiosyncrasies in different natural languages, and the large variety of medical terminology systems. In this paper we present SEMCARE, a European initiative designed to minimize these problems by providing a multi-lingual platform (English, German, and Dutch) that allows users to express complex queries and obtain relevant search results from clinical texts. SEMCARE is based on a selection of adapted biomedical terminologies, together with Apache UIMA and Apache Solr as open source state-of-the-art natural language pipeline and indexing technologies. SEMCARE has been deployed and is currently being tested at three medical institutions in the UK, Austria, and the Netherlands, showing promising results in a cardiology use case.


Asunto(s)
Minería de Datos/métodos , Registros Electrónicos de Salud , Humanos , Almacenamiento y Recuperación de la Información/métodos , Lenguaje , Lingüística/métodos , Procesamiento de Lenguaje Natural , Semántica
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