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.

The process:

1st step:

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.

2nd step:

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.

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