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Evaluating the Use of an Artificial Intelligence (AI) Platform on Mobile Devices to Measure and Support Tuberculosis Medication Adherence

 

In this poster you will learn: 

  • The total number of new TB cases reported in the U.S. in 2015 was 9,563, with LA County ranked within the top five areas reporting the highest number of cases. In addition, there are an estimated 11 million cases of latent TB infection in the US, of which 5-10% could progress to TB disease if left untreated.
  • In-person directly observed therapy (DOT) is a global standard of care and a proven effective method to monitor patients during their course of TB treatment. DOT is resource intensive for TB programs and patients; universal DOT is challenging.
  • Millions of patients begin TB treatment but face challenges in complying with treatment: logistical requirements of in-person DOT and complex regimens cause many patients to adhere inconsistently or stop treatment prematurely.
  • Challenges to in-person DOT include logistical requirements of in-person DOT causing delays in completing the treatment regimen.
  • Recently, innovative approaches to adherence monitoring have been piloted such as video-based DOT (synchronous or asynchronous video transmission requiring full review of each video). The Los Angeles County Department of Public Health (DPH) collaborated with AiCure to pilot using AI in lieu of in-person DOT for TB disease and LTBI patients in one public health TB clinic.