Supporting patient centric care with a predictive, machine learning, profiling tool

For health programs and interventions to be successful and reach all populations that need it, they need to be inclusive and person-centric. This means programs need to understand target populations beyond their demographic and clinical features. This session discusses using a data science model developed by Palindrome and partners to segment target populations based on additional features such as personal, contextual, behavioral or psychographic to help program managers and implementers design more suitable and successful interventions and programs, much the same way as market segmentation is used in product marketing.

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