PRESCRIBERS |
|
|
Main prescribers: General practitioners |
80.68% |
|
INSURED CONSUMERS |
|
|
% of insured consumers |
4.43% |
|
Median age |
49 years |
|
Max/min ratio of the median age (by district) |
1.06 |
|
Percentage of women |
59.81% |
|
Ratio Preferential scheme/General scheme |
1.20 |
|
Coefficient of variation (2022) |
23.84 |
|
Max/min ratio of % of insured consumers (by district) |
2.49 |
|
CONSUMPTION |
|
|
Annual consumption (DDD) |
61,183,521 |
|
Consumption of DDD (per 100,000 insured persons) |
531,619.19 |
|
% DDD issued outside the insurance (approximate) |
28.18% |
|
Average annual consumption per insured consumer (DDD) |
119.90 |
|
% of insured consumers with > 3 times the average consumption |
7,79% |
|
Coefficient of variation 2013-2015 |
13.12 |
|
Coefficient of variation 2020-2022 |
16.92 |
Trend 2013-2022 |
-0.89% |
|
Trend 2013-2019 |
-0.69% |
|
Trend 2019-2022 |
-1.30% |
DIRECT EXPENDITURE (DDD) |
|
|
Annual expenditure charged to the insurance |
5,346,257€ |
|
Average annual expenditure per insured person |
0.46 € |
|
Average patient share per insured consumer |
48.94% |
|
Max/min ratio of expenditure per insured person (by disctrict) |
2.24 |
|
% “Low-cost” medication |
99.33% |
|
Trend 2013-2022 |
-3.82% |
|
Trend 2019-2022 |
-3.57% |
|
On this table, when a statistical test has been performed, the data showing a significant difference is displayed on an yellow background, otherwise on a grey background.
CODES (ATC-5) |
LABELS |
R06AE |
PIPERAZINE DERIVATIVES |
The codes mentioned above can be used in rates and expenses, or only in expenses. We invite you to consult the full report for more information.
Click below to see the graph illustrating the evolution of the breakdown by volume of ATC codes used for the rates.
![Antihistamines for systemic use (2022) Antihistamines for systemic use (2022)](/images/INAMI/Graphiques/Antihistaminiques_2022/resized/Antihistaminiques_2022-Nomen_140x100.png)
ATC codes
Age, sex and CV
Rates by sex
Reimbursement rate
Trends by region
Trends break
Dot Plot
Funnel plot
DDD per patient by province
Quantity per patient
Distribution map
Low-cost DDD
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