The three lists tell you who and where. Enrichment tells you in what order. We overlay disease burden and demand signals onto the practice and operator map for a defined territory or therapy area, and return a ranked call list. It is the highest-value work Medius does with the data, and it is quoted per engagement.
On the left, every practice in a territory, one identical dot each. On the right, the same practices, sized by GP count and shaded by modelled condition burden in their area, with the priority set ringed. One is a footprint. The other is a plan.
Illustrative. Dot size is GP count, shade is modelled burden. Geography and figures are abstracted; no client or deployment is shown.
Clients are not named. These are method summaries, not case studies.
Peripheral arterial disease hotspot model. A diagnostic device supplier needed to prioritise a rollout. We modelled peripheral arterial disease burden by small area, tied it to the practices in the territory, and returned a ranked deployment list so the device went where the clinical need was highest first.
Respiratory burden workup. For a supplier planning territory and call cycles, we modelled respiratory burden across a state and matched it to practice size and location, so field effort followed demand rather than the map.
| Step | What happens |
|---|---|
| 1. Brief | Therapy area, territory and the demand signal that matters. |
| 2. Model build | Burden modelled by area from the best available prevalence, prescribing or procedure data. |
| 3. Overlay | The model is matched to the practices in the dataset for the territory. |
| 4. Ranked file | A prioritised target and call list, with the reasoning. |
Scoped on therapy area, territory and the modelling required.