Our Data Management team is responsible for maintaining the quality of the data returned to you through your various Hub applications, and operates within your databases, so that the data complies with the OpenHealth Company quality requirement.
1. The elements we need in order to reproduce your observation
The first step is to reproduce the observation that triggers this investigation, for this before triggering this process we ask you to provide us with the following elements along with a screenshot:
TRACEABILITY CARTRIDGE
Server / environment name : The database server or environment for an application
Mug: Name of the underlying database.
Application: The name of your application.
Data source : Data source for the observation.
Geographical territory: The geographical territory of the observation.
Module: The HUB module you are observing on.
Filter: The set of filters that you have applied within the sheet MY QUERY or MARKET DEFINITION (Markets / Segments / Companies / Brands)
Dimensions: The product granularity used (MARKET / SEGMENT / COMPANY / BRAND / PRODUCT AND CODE)
Indicator: The indicator used in your observation .
Period: The period over which you make your observation.
Operator: Operator that reproduces the observation.
2. The second step of the LEVEL 1 INVESTIGATION, checking the version of your database
This step consists of verifying all the traceability elements in your database:
The server your database is located on.
The traceability of the database.
The date of its creation.
The date of its last update.
The date of the most recent data.
The frequency of updating the data.
The version of the database.
The name of the market (s).
The number of products.
The reference of your contract.
Data sources wired to your base.
The list of all treatments (IPR / MAM / CCP / CMT) with full traceability (Date / Time / Treatment / Parameters / Operator)
The number of sectorizations calculated for TMA and / or CUSTOMER TYPE.
3. The third step of the LEVEL 1 INVESTIGATION, checking the consistency of the data between them (Consistency of data in Intrabase)
We then run a check that allows us to check the consistency of the data in your database:
For national PHARMACIES (PHARMA) data
The depth of history.
The number of products sold.
National sales data per month:
The turnover per month (EXCLUDING PRESCRIPTION)
The turnover per month (ON PRESCRIPTION)
The turnover per month (TOTAL: EXCLUDING PRESCRIPTION + PRESCRIPTION)
Volume sales per month (EXCLUDING PRESCRIPTION)
Sales volume per month (ON PRESCRIPTION)
Volume sales per month (TOTAL: EXCLUDING PRESCRIPTION + PRESCRIPTION)
National sales data per day:
The turnover per day (EXCLUDING PRESCRIPTION)
Turnover per day (ON PRESCRIPTION)
The turnover per day (TOTAL: EXCLUDING PRESCRIPTION + PRESCRIPTION)
Sales volume per day (EXCLUDING PRESCRIPTION)
Sales volume per day (ON PRESCRIPTION)
Volume sales per day (TOTAL: OUT OF PRESCRIPTION + ON PRESCRIPTION)
For PHARMACY (PHARMA) data by sector
Sales data per month by sector:
The turnover per month (EXCLUDING PRESCRIPTION)
The turnover per month (ON PRESCRIPTION)
The turnover per month (TOTAL: EXCLUDING PRESCRIPTION + PRESCRIPTION)
Volume sales per month (EXCLUDING PRESCRIPTION)
Sales volume per month (ON PRESCRIPTION)
Volume sales per month (TOTAL: EXCLUDING PRESCRIPTION + PRESCRIPTION)
The number of sectors
Sales data per day by sector:
The turnover per day (EXCLUDING PRESCRIPTION)
Turnover per day (ON PRESCRIPTION)
The turnover per day (TOTAL: EXCLUDING PRESCRIPTION + PRESCRIPTION)
Sales volume per day (EXCLUDING PRESCRIPTION)
Sales volume per day (ON PRESCRIPTION)
Volume sales per day (TOTAL: OUT OF PRESCRIPTION + ON PRESCRIPTION)
The number of sectors
For national PARAPHARMACIES (SMKT) data
The depth of history
The number of products sold
National sales data per month:
Turnover per month
Sales volume per month
National sales data per day:
Turnover per day
Sales volume per day
For PARAPHARMACIES (SMKT) data by sector
Sales data per month by sector:
Turnover per month
Sales volume per month
The number of sectors
The turnover per month for the sum of the sectors versus the turnover per month nationally
Volume sales per month for the sum of the sectors versus volume sales per month nationally
Sales data per day by sector:
Turnover per day
Sales volume per day
The number of sectors
The turnover per day for the sum of the sectors versus the turnover per day nationally
Volume sales per day for the sum of sectors versus volume sales per day nationally
Then we apply the same controls for the consolidated PHARMA + SMKT (Pharmacy and Parapharmacy) data and also for the data from other data sources (CORSE / MONACO / DROM- COM / Other country)
For PHARMACY data (PHARMA only) of stocks:
data:
data per month in volume
data by month in value
4. The fourth step of the LEVEL 1 INVESTIGATION, checking the consistency of the data with our reference databases (Consistency of data in Interbase)
Once the consistency of the intrabase data has been verified, we check the consistency of the data with our reference databases, in order to guarantee the quality of the data throughout the production chain.
So we check, on the list of products in your database:
The depth of history in the reference mug
Turnover per day
Turnover per month
Sales volume per day
Sales volume per month
The number of products sold per day
The number of products sold per month
data per month in volume
data by month in value
5. The fifth step of the LEVEL 1 INVESTIGATION, the search for tickets from pharmacies
We are able, during a LEVEL 1 INVESTIGATION, to trace our production chain up to tickets from pharmacies, in order to guarantee the total traceability of the data available to you through your Hub app.
In certain cases we can detect atypical behavior, on certain pharmacies, certain sales of products, or certain days of sales.
To find out what an atypical sale is: Article on atypical sales
6. The sixth step of the LEVEL 1 INVESTIGATION, the restitution
Finally, we provide you with full transparency, all the results with all the traceability of this investigation, in a summary email.
Our Success site contains many articles on all of our processes, don't hesitate to share them.
In the appendix here are the articles related to this subject:
The data sources of the Hub : the list of data sources
The geographical territories : the list of territories geographic locations available in the HUB
The measurements and time periods : the measurements available in the HUB
The Hub indicators : the list of indicators
For all information on our panel of pharmacies here is the article: understand what the OpenHealth-panel of pharmacies is
For questions concerning the updating of our data from parapharmacies (SMKT: Supermarket) : On what date are the GSA drugstore data updated (SMKT data) in the Hub?
Interval and confidence level of the data : what you need to know.
Data quality : Sales decomposition process at OpenHealth
You want to compare data from two different providers : How to conduct a comparative analysis?
To find out what an atypical sale : Article on atypical sales
How to integrate a new data source in the HUB ? : process d 'data integration in the HUB