Tamil Nadu First TB Deaths Prediction Model Integrated into Public Health System
Tamil Nadu First TB Deaths Prediction system is now part of the state’s battle against tuberculosis. In a significant move toward reducing TB-related deaths, Tamil Nadu has become the first state in India to adopt a predictive model that forecasts the risk of death among adults diagnosed with tuberculosis. This model has now been integrated into the state’s existing TB SeWA (Severe TB Web Application) platform.
The aim is to drastically cut down the time between diagnosis and hospital admission, especially for those most vulnerable to early complications. More than 70% of TB deaths occur within the first two months of starting treatment. With this new update, healthcare workers can now assess and act swiftly on patients flagged as high-risk.
Tamil Nadu First TB Deaths Prediction Model Integrated into Public Health System
Tamil Nadu First TB Deaths- The predictive tool is part of the Tamil Nadu-Kasanoi Erappila Thittam (TN-KET), a differentiated care model launched in 2022. Under this program, every adult diagnosed with TB is screened for severe conditions like undernutrition, respiratory distress, and weak physical condition. Five specific indicators—body mass index (BMI), pedal oedema, respiratory rate, oxygen saturation, and the ability to stand unaided—are recorded at the time of diagnosis.
These values are entered into the TB SeWA app, which earlier flagged patients as “severely ill.” Now, it goes a step further by calculating a predicted probability of death, allowing for more immediate and precise intervention. For example, a severely ill patient may have a death risk ranging from 10% to 50%, depending on how many risk factors are present. In contrast, patients not marked as severely ill show much lower risk—typically between 1% and 4%.
Tamil Nadu First TB Deaths Reduction Strategy Shows Promise
The model was developed by the Indian Council of Medical Research–National Institute of Epidemiology (ICMR-NIE), using clinical data from nearly 56,000 TB patients across Tamil Nadu between July 2022 and June 2023. The idea is to ensure timely hospital admission for those who need it most, avoiding fatal delays.
Currently, the average time for admission after a diagnosis is around one day under TN-KET. But nearly 25% of patients still face delays ranging from three to six days. With the new predicted risk model, frontline staff are now empowered to take faster and more decisive action. This also creates accountability and a measurable benchmark for how quickly the system responds to urgent cases.
All of Tamil Nadu’s 2,800 government-run health facilities ranging from primary health centres to medical colleges have access to this technology. They also continue to use a paper-based triage system in parallel for backup and verification.
Leading the Nation in Early TB Intervention
Tamil Nadu First TB Deaths is currently the only state in India systematically capturing and acting on these five clinical indicators. The state’s consistent efforts over the last three years have already shown promising results. A recent internal study found that most districts recorded reduced TB mortality rates after implementing TN-KET.
Additionally, this model is more time-effective than the national TB platform Ni-kshay. While Ni-kshay collects more data, those details become available only after three weeks too late to be useful for high-risk patients. The five triage variables used in Tamil Nadu are recorded within a day, allowing for faster response.
Conclusion
By being the first in India to implement a TB deaths prediction model, Tamil Nadu is setting an example for other states. This initiative not only improves patient outcomes but also brings a data-driven, proactive approach to public health. With faster diagnoses, clear risk alerts, and quicker hospitalisation, the state is making steady progress in eliminating tuberculosis deaths.
