Patient-Centric Insights from Real-World Treatment Journey Visualization
Background
- Market leading brand in a highly competitive modern anti-diabetic class
- Heavy focus on HCP-centered analytics & insights … lack of visibility into how brand fits into the real patient journey
- Longitudinal (big) data lying virtually untapped on the cloud. Utilized, when needed, by analytics team to address business questions (tip of the iceberg)
- KBQs: How to fully leverage big data to rapidly derive patient-centric insights for brand team?
Objective
Build tool to visualize real-world treatment journey for diabetes patients by class, along with KPIs to enable patient-centered insights and hypothesis generation- Visualize patient journey across lines of therapy
- Provide KPIs at the market, brand, competitor and patient-level
- Inform brand planning
- Rapidly update tool and KPIs with incremental data
Approach
- Defined key business questions (KBQs) around the market, brand, competitor switching, patient journey and outcome
- Identified KPIs – firmed up definitions in collaboration with client
- Defined detailed business rules for diabetes patient journey progression
- Build Visualization Tool and beta tested with select group of users
- Deployed tool to the broader user community, and maintained it over time
- Guided design of patient analytics (deep dives)
Insights & Results
- Real-world patient journey is quite different (e.g. Many T2D patients getting started on DPP4, GLP1, SGLT2 vs. Metformin)
- Client’s brand leads competitor in 2L but is a close second in 3L
- Naïve patients contributing to lower days on therapy
- Reframed targeting – Shift from Metformin-heavy writers to those treating patients with the highest likelihood to switch by LoT
- Informed and shaped brand plan, and triggered focused AI/ML patient finder projects