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[Use of database linkage and scripting rules to upgrade variables in the Sinan-TB database]
Marli Souza Rocha1, Gisele Pinto de Oliveira1, Luis Carlos Torres Guillen1
1Instituto de Estudos em Saúde Coletiva, Universidade Federal do Rio de Janeiro, Rio de Janeiro, Brasil.
Cadernos De Saude Publica
|December 5, 2019
Summary
Upgrading Brazil's tuberculosis (TB) disease surveillance data by linking databases improved accuracy. This enhanced data quality supports better decision-making for TB control programs.
Area of Science:
- Public Health
- Infectious Disease Epidemiology
- Health Informatics
Background:
- Brazil's Information System on Diseases of Notification (Sinan) is crucial for tuberculosis (TB) control.
- Accurate and reliable data are essential for effective TB incidence assessment and control measures.
- Existing data quality in Sinan-TB required enhancement for improved public health decision-making.
Purpose of the Study:
- To upgrade key variables within the Sinan-TB database, including entry variables, closure status, HIV testing, AIDS-related illness, and diabetes.
- To improve the overall reliability and accuracy of TB surveillance data in Brazil.
- To enhance the utility of Sinan-TB for informing tuberculosis control strategies.
Main Methods:
- Data linkage was performed between the Sinan-TB database, the Mortality Information System (SIM), and the AIDS database for Rio de Janeiro.
- Criteria for upgrading variables were established based on TB technical materials and Sinan database standards.
- A Structured Query Language (SQL) script was developed and implemented to perform the data upgrades.
Main Results:
- Treatment dropout rates increased by 115% due to refined closure criteria (decreased transfers, improved record closure).
- Records indicating diseases associated with diabetes increased by 2.4% after integrating SIM data.
- HIV testing and AIDS-related illness records showed increases of 5.3% and 8.7%, respectively, following integration with the AIDS database.
Conclusions:
- Integrating Sinan-TB with other information systems significantly improved data quality.
- Enhanced data accuracy provides a more reliable foundation for decision-making in TB control programs.
- The study demonstrates the value of data linkage for strengthening national disease surveillance systems.
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