Case Studies
Improving Targeting Precision and Field Force Direction through AIML-based Patient Finding
Background A global rare disease company was looking to improve targeting precision and support field team effectiveness Traditional targeting was non-viable due to the small size of the patient populations, complex disease recognition and diagnosis, and restrictive therapy eligibility criteria Attempts by a prior analytics partner to use rule-based alerts failed, and even after two years, no new patients had been identified Given the small number of patients in each indication, every new start is high value, both for the…