AI breakthrough for HIV patients in Sub-Saharan Africa

AI breakthrough for HIV patients in Sub-Saharan Africa

Health technology innovators Vantage Health Technologies and the Institute of Human Virology Nigeria (IHVN), have made a breakthrough by using artificial intelligence to help HIV patients in Sub-Saharan Africa be on sustained treatment.

Keeping the world’s estimated 38 million HIV positive people on effective and sustained treatment is one of the most critical parts of controlling the global HIV epidemic.

It is estimated that 25 million – or 67% – of all people living with HIV, live in Sub-Saharan Africa, and 8.1 million of these people are virally unsuppressed.

Through Vantage’s artificial intelligence (AI)-enabled Patient Retention Solution, the IHVN team – funded through a grant from the United States’ Centres for Disease Control and Prevention – has been able to predict and positively influence the behaviour of high-risk HIV/AIDS patients.

The Patient Retention Solution is an AI-driven model that uses data from patient history to predict if patients will miss their next clinic appointment with the assumption that missing the appointment means the patient will drop off treatment as they are not present to collect their medication.

The solution uses a machine learning model to identify patients at high-risk of missing their next appointment and produces patient lists that are given to clinical staff to conduct various interventions to prevent patients from missing their next appointment.

SMS messages, phone calls and home visits for those without phone numbers are then arranged to provide personal attention to each patient ahead of their scheduled clinic appointments.

The Patient Retention Solution algorithm was trained on 330 000 IHVN patients, and this pilot project was focused on the approximately 5 000 identified at-risk patients.

Of these, 91% of patients on the predictive list who received an intervention (SMS, phone call or home visit) were up to date in the month of intervention, meaning that they were retained in care. This compares to 55% retention in a comparison group who did not receive the intervention.

Annika Lindorsson Krugel, Solutions Manager of Vantage Health Technologies, said “Collaboration between public health partners, combined with the use of state-of-the-art AI technology, is proving to be a highly effective strategy for improving retention for HIV/AIDS out-patients.”

“The burden of disease and treatment challenges in sub-Saharan Africa has made it especially crucial to use technology and partnerships to improve the care process.”

Mercy Omozuafoh, Programme Manager for Care and Support with the IHVN said, “The project has demonstrated the effectiveness of proactive tracking of Patients Living with HIV (PLHIV) and has made us understand the importance of interventions we are implementing. It has broadened our minds and we are able to scale up the solution to include more facilities.”

The Patient Retention machine learning model was independently validated by Dartmouth Institute for Health Policy and Clinical Practice. A case study by the Dartmouth Institute, which looked at eight months of data from the three Nigerian locations, found that the main barriers to treatment adherence included stigma, side-effects, logistical challenges, economic barriers and forgetfulness.

The study found that caregiver support, peer support and understanding one’s status helped patients overcome these barriers.

The Vantage Patient Retention Solution has been implemented in HIV treatment and care programmes across Nigeria and South Africa and is yielding similar successes. “The solution is an innovative example of what can be achieved when artificial intelligence truly powers human action,” concludes Krugel.