Finding patients in claims databases, such as APLD (Anonymized Patient-Level Data) and Truven Marketscan can be accomplished by identifying patients that show characteristics that are similar to other patients with the same diagnosis codes. Using a vast trove of Claims data, our patient finder models categorize and rank Patient IDs that match historical patterns of onset of disease states. These are typically classification tasks with probability scores used for ranking potential candidates
It is a common practice within pharmaceutical companies to apply promotion response modeling to find the optimal sequence of mix multi-channel marketing (direct marketing, advertising, etc.) and other activities such as detail (P1, P2) and call frequency. Traditionally, such activities have been performed using negative exponential - a response curve that increases fast but soon levels out, indicating that increased amount of promotion spending will have lesser and lesser impact on revenues. The application of ML models to supplement the existing research is an effective approach to improve and further refine the process.
