From Raw Data to FAIR Data: The FAIRification Workflow for Brazilian Tuberculosis Research.
Stud Health Technol Inform
; 305: 331-334, 2023 Jun 29.
Article
en En
| MEDLINE
| ID: mdl-37387031
ABSTRACT
Among the main factors that negatively influence the decision-making process, it is possible to highlight the low quality, availability, and integration of population health data. This study aims to highlight the difficulty of research based on tuberculosis data available in Brazil. The FAIR methodology is a solution for standardizing data and sharing information about the disease. All the main actors involved, including those who generate data and administrators of information systems, should be encouraged to know their strengths and weaknesses. Continuously fostering strategies to promote data quality is, therefore, a strong stimulus for strengthening national health information systems and can potentially benefit from recommendations on how to overcome the inherent limitations of these information systems. Data quality management in Brazilian tuberculosis information systems is still not carried out organized and systematically. According to the FAIR principles, the evaluation demonstrates only 37.75% of compliance.
Palabras clave
Texto completo:
1
Colección:
01-internacional
Base de datos:
MEDLINE
Contexto en salud:
1_ASSA2030
/
3_ND
Problema de salud:
1_sistemas_informacao_saude
/
3_neglected_diseases
/
3_tuberculosis
Asunto principal:
Tuberculosis
/
Personal Administrativo
Tipo de estudio:
Diagnostic_studies
/
Prognostic_studies
Límite:
Humans
País/Región como asunto:
America do sul
/
Brasil
Idioma:
En
Revista:
Stud Health Technol Inform
Asunto de la revista:
INFORMATICA MEDICA
/
PESQUISA EM SERVICOS DE SAUDE
Año:
2023
Tipo del documento:
Article
País de afiliación:
Brasil