AI Predictive Adherence Counseling (South Africa)
Palindrome and Right to Care, South Africa (September 2021)
Intervention Description
Model that can predict whether a patient will miss their next scheduled appointment. Patient gets a tailored intervention based on the results.
Presenter: Tom Compton, Right to Care; Kieran Sharpey-Schafer, Palindrome
Intervention Details
Viral load Demographics Clinical data (age, gender, viral load history, visit pattern) | |
Compared to adherence scorecard Model performance: Loss to follow up: Accuracy – 66% Specificity- 94% Sensitivity -61% Graphs were presented on tracking LTFU at different stages of care | |
Machine learning and AI Patient risk score are used to assist workers in nudging towards intervention. | |
Machine Learning Algorithm Total Adherence Score | |
What are the impacts of telling someone they’re high risk? | |
Last updated
