PubMed · 2002 · 22 citations · 7 references
Public HealthHealth InformaticsInfectious Disease ControlCase FindingDisease SurveillanceTuberculosis ControlTuberculosis Case FindingTuberculosis DiagnosisTuberculosis EpidemiologyTuberculosis PreventionTuberculosis Program ManagementTuberculosis SurveillancePaper-based RegistrationSputum Smear ConversionTreatment Outcome MeasurementTreatment Outcome MonitoringTuberculosis Case DetectionTuberculosis Notification SystemsTuberculosis Surveillance SystemsUser Acceptance
SETTING: Tuberculosis (TB) rates in southern Africa have increased dramatically in recent years. Provision of accurate data for surveillance, program management, and supervision is increasingly essential. OBJECTIVE: To develop software that would provide more efficient collection, compilation, and analysis of TB data on an ongoing basis. DESIGN: The 'Electronic TB Register' is a user-friendly, Epi-Info based software program based on the WHO/IUATLD format of recording and reporting. Individual records from the TB registry are entered in a program that provides interactive support. The software provides several patient management and supervision functions, such as lists of defaulters. Finally, it generates standard quarterly and annual reports on case-finding, sputum conversion, and cohort analysis, and provides graphs of trends and maps of TB indicators. RESULTS: The 'Electronic TB Register' software has been successfully implemented in five pilot projects in southern Africa. User acceptance has been high and quality of data has improved, although timeliness remains unchanged. Factors critical for success include a functioning, paper-based system, involvement of staff from the TB program, health information systems, and health facilities, ongoing training, and backup support. CONCLUSIONS: The 'Electronic TB Register' is a potentially powerful tool for surveillance, management, and supervision for countries with well-functioning paper-based recording and reporting systems.
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Real-time tracking of self-reported symptoms to predict potential COVID-19
Cristina Menni, Ana M. Valdes, Maxim B. Freidin et al. · Nature Medicine · 2020 · 1.5K citations · Full text
Xiangao Jiang, Megan Coffee, Anasse Bari et al. · Computers, materials & continua/Computers, materials & continua (Print) · 2020 · 456 citations · Full text