Intelligent TB Prevention: How AI is making the difference in the Philippines
The USAID’s TB Innovations and Health Systems Strengthening Project managed by FHI 360, together with the Department of Health and ACCESS TB Project, pilot-tested a one-stop-hub Tuberculosis Intensified Case Finding (ICF) in the out-patient department of 3 government tertiary hospitals in the Philippines from August 2019 to March 2020.
Chest X-Ray augmented with AI was used to screen patients and their companions for TB, followed by on-the-spot sputum collection if the chest X-ray showed possible Tuberculosis(TB) and/or patients showed symptoms of TB. To confirm diagnosis, their sputum specimens were tested using Xpert MTB/Rif and/or TB Loop-mediated isothermal amplification (TB LAMP).
A total of 12,917 clients were screened, 27.8% were identified as presumptive TB and 89.3% of clients submitted specimens. There was an overall confirmed TB yield of 5.6% among presumptive TB and an average of 79% treatment rate in 3 hospitals. Without the AI-augmented Chest X-rays, 37.6% of bacteriologically confirmed TB cases could have been missed, if only signs and symptoms alone are used to screen clients for TB.
In other words, in FHI 360’s screening study on around 13k suspects, 3 out of 8 confirmed TB cases were found to be asymptomatic and were only detected because they had deployed AI-based Chest X-ray screening.
The strategy proved to be effective in finding new TB cases among seemingly asymptomatic clients in a shorter turn-around time. Hence, immediate treatment can be given to avoid the occurrence of severe disease and prevention of TB transmission in the community.
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