[Interpretation for the group standards in data management for large population-based cohorts].
Zhonghua Liu Xing Bing Xue Za Zhi
; 40(1): 17-19, 2019 Jan 10.
Article
em Zh
| MEDLINE
| ID: mdl-30669725
ABSTRACT
Precision medicine became the key strategy in development priority of science and technology in China. The large population-based cohorts become valuable resources in preventing and treating major diseases in the population, which can contribute scientific evidence for personalized treatment and precise prevention. The fundamental question of the achievements above, therefore, is how to construct a large population-based cohort in a standardized way. The Chinese Preventive Medicine Association co-ordinated experienced researchers from Peking University and other well-known institutes to write up two group standards Technical specification of data processing for large population-based cohort study (T/CPMA 001-2018) and Technical specification of data security for large population-based cohort study (T/CPMA 002-2018), on data management. The standards are drafted with principles of emphasizing their scientific, normative, feasible, and generalizable nature. In these two standards, the key principles are proposed, and technical specifications are recommended in data standardization, cleansing, quality control, data integration, data privacy protection, and database security and stability management in large cohort studies. The standards aim to guide the large population-based cohorts that have been or intended to be established in China, including national cohorts, regional population cohorts, and special population cohorts, hence, to improve domestic scientific research level and the international influence, and to support decision-making and practice of disease prevention and control.
Palavras-chave
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Padrões de Referência
/
Vigilância da População
/
Atenção à Saúde
Tipo de estudo:
Etiology_studies
/
Guideline
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Incidence_studies
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Observational_studies
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Prognostic_studies
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Risk_factors_studies
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Screening_studies
Limite:
Humans
País/Região como assunto:
Asia
Idioma:
Zh
Ano de publicação:
2019
Tipo de documento:
Article