Description of Session
Maintaining HIV patients on treatment is vital to bringing the disease into epidemic control and achieving “90-90-90”- the global objective of 90% of HIV+ individuals aware of their status, 90% of diagnosed patients on sustained treatment and 90% of treated patients achieving viral suppression. In South Africa only 74% of patients who are aware of their status are currently on treatment (Thembisa 4, SA AIDS Conference). Those that drop out, in addition to having poor health outcomes, increase the risk of viral transmission. Addressing patient retention is therefore critical to achieving HIV epidemic control. The challenge is magnified in an environment of underprivileged patients in resource-constrained public health systems. Many promising interventions to increase patient ongoing engagement in HIV treatment are hampered by health care worker capacity constraints. Meanwhile, scalable digital technologies that have been deployed elsewhere to promote adherence through direct patient engagement remain out of reach, exacerbated by low connectivity and underdeveloped data privacy policies. BroadReach is tackling the critical challenge through application of leading edge technology in the form of predictive modelling. Predictive modelling bridges the gap between the need and the available resources by empowering health care workers with insight into which patients are most at risk of dropout as early as possible in their treatment journey. Health workers can prioritize the “last mile” connection to the most vulnerable patients through focused interventions available in their environment, improving outcomes for both the individual and his or her community. BroadReach’s panel presentation demonstrates how predictive analytics modelling is used to establish risk and then, how pragmatically this information can be used in a live setting to catalyze targeted interventions that increase treatment retention among HIV patients, accelerating health system performance towards epidemic control.
