The challenge & Our AI Solution
Patients dropping off TB treatment or being lost to follow-up face severe health risks, including loss of life. Healthcare workers need better tools to identify and support these vulnerable individuals.
PATO uses patient data to predict, at the start of treatment, who is at high risk of poor outcomes (like defaulting or mortality). This allows healthcare providers to focus their efforts on those who need the most support.
A sophisticated risk stratification model flags high-risk individuals for prioritized follow-up.
Real-World Impact
Over 147,000 TB patients enrolled across 15 states and UTs (Haryana, Chandigarh, Meghalaya, Manipur, Assam, Uttarakhand, Nagaland, Tripura, DDNH, Punjab, Kashmir, Madhya Pradhesh, Mumbai, Goa, Mizoram). PATO identified nearly 35,000 high-risk individuals, leading to over 22,000 targeted interventions. Patients who received follow-up showed a 20% reduction in adverse outcomes. PATO is being integrated into national TB platforms (Differentiated TB Care Module & Ni-kshay), set to impact ~2.5 million patients annually.
3,546,440
Patients enrolled
1,351,688
high-risk patients identified
36
28 States + 8 UTs
Partners in Health
