Entry data - DOE:
Openhealth Company's objective is to aggregate different data sources and present them on the platformThe Hub.
For the extrapolation of a patient follow-up, we use 2 different panels, the first panel P1 without patient ID and the second P2 with patient ID.
From the P1 panel, we extrapolate daily sales data from the entire French territory, for each of the 450,000 items sold in the 20,764 pharmacies (* as of 01/29/2020)
( see article on the OpenHealth panel )
- > We therefore have data extrapolated nationally from P1, with a number of boxes called M per day nationally for a given product.
In the P2 panel, in the gross sales data, the pharmacy tickets, we have patient data including age and gender.
- > We therefore have non-extrapolated data from P2, with a number of boxes that we call m for a set of pharmacies, for patients that the we name i, by age (0,1,2,3, ... n) and by gender (M / F) for this same product.
To extrapolate patient follow-up on a national level we use the coefficient α = M ( number of boxes per day nationally for a given product ) / m ( number of boxes per day for a set of pharmacies, for patients , and this by age and gender for this same product )
We then apply this coefficient α to the sales data of the P2 panel, in order to obtain national patient data by age and gender.
Then, from our method of re-allocation of national sales data to sector-level we are able to present this patient information according to a previously chosen geographic breakdown: for example the administrative regions and Health territories.
Output data - DOS:
As an output we have patient data, for a given product, by month, by age and by gender.