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Calculation of Purchasing Power Parities for Pharmaceutical Products via EURIPID database

BACKGROUND: Purchasing power parities (PPPs) are indicators of price level differences for all goods and services across countries. Their calculation follows the ÉKS method (https://ec.europa.eu/eurostat/cache/metadata/en/prc_ppp_esms.htm). Prices of pharmaceuticals are collected by national statist...

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Autores principales: Habl, C, Zuba, M
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9593786/
http://dx.doi.org/10.1093/eurpub/ckac129.343
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author Habl, C
Zuba, M
author_facet Habl, C
Zuba, M
author_sort Habl, C
collection PubMed
description BACKGROUND: Purchasing power parities (PPPs) are indicators of price level differences for all goods and services across countries. Their calculation follows the ÉKS method (https://ec.europa.eu/eurostat/cache/metadata/en/prc_ppp_esms.htm). Prices of pharmaceuticals are collected by national statistical offices using different methods, from asking prices in pharmacies to retrieving scanner data. The sample is limited to 150 top-selling medicines, which are not available in all countries. Consequently, the PLIs (price level indices) and PPPs derived are sometimes based on only 50 pharmaceuticals. In a cooperation between Eurostat and EURIPID the PPP calculation was alternatively done with the EURIPID database for 28 countries. METHODS: The study compared the PLIs/PPPs derived from the E20-2 “Furniture and health” survey (aka CGS) with those from EURIPID for 2018-2020. The main challenge was to identify comparable products from the 224,448 products in EURIPID. For this we grouped those that shared the same 1) ATC, 2) active substance(s) & strength(s), 3) pack size group and 4) dosage form group (e.g., oromucosal) resulting in 157,186 distinctive products compared to 1,928 included in CGS. We used the Gross Retail price (GRP) as defined in the Eurostat PPP manual. RESULTS: The ranking of PPPs was similar in both approaches, with Switzerland and Iceland in the lead and Poland and Hungary in the end. Only for some countries, e.g. the Netherlands deviations were identified. The Pearson correlation between the 2020 PLI for the Euripid subsample using the asterisk method with all products marked as representative and the CGS results was 0,946. CONCLUSIONS: Results from EURIPID show the same trend as the CGS. It is possible to replace the national data collection by a central source. This would reduce the data collection burden on the statistical offices and allows a closer monitoring of the evolution of pharmaceutical prices (bi-annual PPP publication instead of current 3-year interval) KEY MESSAGES: • To monitor affordability of medicines for all citizens it is important to compare prices on a regular basis with a simple tool as e.g. some products prices differed by 1000-times across countries. • The EURIPID database (www.euripid.eu) allows detailed analysis of pharmaceutical prices in Europe and is available for free to non-commerical researchers.
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spelling pubmed-95937862022-11-22 Calculation of Purchasing Power Parities for Pharmaceutical Products via EURIPID database Habl, C Zuba, M Eur J Public Health Parallel Programme BACKGROUND: Purchasing power parities (PPPs) are indicators of price level differences for all goods and services across countries. Their calculation follows the ÉKS method (https://ec.europa.eu/eurostat/cache/metadata/en/prc_ppp_esms.htm). Prices of pharmaceuticals are collected by national statistical offices using different methods, from asking prices in pharmacies to retrieving scanner data. The sample is limited to 150 top-selling medicines, which are not available in all countries. Consequently, the PLIs (price level indices) and PPPs derived are sometimes based on only 50 pharmaceuticals. In a cooperation between Eurostat and EURIPID the PPP calculation was alternatively done with the EURIPID database for 28 countries. METHODS: The study compared the PLIs/PPPs derived from the E20-2 “Furniture and health” survey (aka CGS) with those from EURIPID for 2018-2020. The main challenge was to identify comparable products from the 224,448 products in EURIPID. For this we grouped those that shared the same 1) ATC, 2) active substance(s) & strength(s), 3) pack size group and 4) dosage form group (e.g., oromucosal) resulting in 157,186 distinctive products compared to 1,928 included in CGS. We used the Gross Retail price (GRP) as defined in the Eurostat PPP manual. RESULTS: The ranking of PPPs was similar in both approaches, with Switzerland and Iceland in the lead and Poland and Hungary in the end. Only for some countries, e.g. the Netherlands deviations were identified. The Pearson correlation between the 2020 PLI for the Euripid subsample using the asterisk method with all products marked as representative and the CGS results was 0,946. CONCLUSIONS: Results from EURIPID show the same trend as the CGS. It is possible to replace the national data collection by a central source. This would reduce the data collection burden on the statistical offices and allows a closer monitoring of the evolution of pharmaceutical prices (bi-annual PPP publication instead of current 3-year interval) KEY MESSAGES: • To monitor affordability of medicines for all citizens it is important to compare prices on a regular basis with a simple tool as e.g. some products prices differed by 1000-times across countries. • The EURIPID database (www.euripid.eu) allows detailed analysis of pharmaceutical prices in Europe and is available for free to non-commerical researchers. Oxford University Press 2022-10-25 /pmc/articles/PMC9593786/ http://dx.doi.org/10.1093/eurpub/ckac129.343 Text en © The Author(s) 2022. Published by Oxford University Press on behalf of the European Public Health Association. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Parallel Programme
Habl, C
Zuba, M
Calculation of Purchasing Power Parities for Pharmaceutical Products via EURIPID database
title Calculation of Purchasing Power Parities for Pharmaceutical Products via EURIPID database
title_full Calculation of Purchasing Power Parities for Pharmaceutical Products via EURIPID database
title_fullStr Calculation of Purchasing Power Parities for Pharmaceutical Products via EURIPID database
title_full_unstemmed Calculation of Purchasing Power Parities for Pharmaceutical Products via EURIPID database
title_short Calculation of Purchasing Power Parities for Pharmaceutical Products via EURIPID database
title_sort calculation of purchasing power parities for pharmaceutical products via euripid database
topic Parallel Programme
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9593786/
http://dx.doi.org/10.1093/eurpub/ckac129.343
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