UNSPLASH
Tamil Nadu has become the first state in the country to implement a model which predicts the probability of deaths among adults with Tuberculosis and has integrated it with the existing state-wide application TB SeWA, which triages them at diagnosis.
The predictive model, developed by ICMR's National Institute of Epidemiology (NIE) that was launched last week, aims to reduce the average time from diagnosis to hospital admission for severely ill TB patients, thereby bringing down the mortality rate further, said Dr Asha Frederick, State TB Officer of Tamil Nadu.
The new feature has been added to Tamil Nadu's existing TB SeWA (Severe TB Web Application), which has been in use since 2022 under the state's differentiated care model initiative Tamil Nadu - Kasanoi Erappila Thittam (TN-KET), she told PTI.
Under TN-KET, healthcare workers screen a triage every newly diagnosed adult with TB for very severe undernutrition, respiratory distress or poor physical condition using five variables — body mass index (BMI), pedal oedema (swelling of feet and ankles), respiratory rate, oxygen saturation, and the ability to stand without support.
Then, health staff feeds these variables into TB SeWA, which then tells whether a particular patient is severely ill or not. Under TN-KET, all severely ill (very severely undernourished or having respiratory distress or poor physical status) have to be prioritised for admission, Dr Frederick said.
Until now, TB SeWA flagged patients as 'severely ill' based on these variables, helping health staff prioritise them for inpatient care, Dr Manoj Murhekar, Director of NIE said.
"The new feature goes a step further — calculating and displaying predicted probability of death for adults with TB," Dr Murhekar said.
This objective risk percentage aims to overcome any subjective inference regarding severity and guide frontline staff to act immediately and firmly for the hospital admission of severely ill adults with TB at the time of diagnosis, he said.