Calculation of Purchasing Power Parities for Pharmaceutical Products via EURIPID database
Abstract 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...
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Online Access: | http://dx.doi.org/10.1093/eurpub/ckac129.343 https://academic.oup.com/eurpub/article-pdf/32/Supplement_3/ckac129.343/48593664/ckac129.343.pdf |
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croxfordunivpr:10.1093/eurpub/ckac129.343 2023-05-15T16:52:36+02:00 Calculation of Purchasing Power Parities for Pharmaceutical Products via EURIPID database Habl, C Zuba, M 2022 http://dx.doi.org/10.1093/eurpub/ckac129.343 https://academic.oup.com/eurpub/article-pdf/32/Supplement_3/ckac129.343/48593664/ckac129.343.pdf en eng Oxford University Press (OUP) https://creativecommons.org/licenses/by/4.0/ CC-BY European Journal of Public Health volume 32, issue Supplement_3 ISSN 1101-1262 1464-360X Public Health, Environmental and Occupational Health journal-article 2022 croxfordunivpr https://doi.org/10.1093/eurpub/ckac129.343 2023-01-13T10:48:29Z Abstract 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 ... Article in Journal/Newspaper Iceland Oxford University Press (via Crossref) European Journal of Public Health 32 Supplement_3 |
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Oxford University Press (via Crossref) |
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English |
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Public Health, Environmental and Occupational Health |
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Public Health, Environmental and Occupational Health Habl, C Zuba, M Calculation of Purchasing Power Parities for Pharmaceutical Products via EURIPID database |
topic_facet |
Public Health, Environmental and Occupational Health |
description |
Abstract 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 ... |
format |
Article in Journal/Newspaper |
author |
Habl, C Zuba, M |
author_facet |
Habl, C Zuba, M |
author_sort |
Habl, C |
title |
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_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_sort |
calculation of purchasing power parities for pharmaceutical products via euripid database |
publisher |
Oxford University Press (OUP) |
publishDate |
2022 |
url |
http://dx.doi.org/10.1093/eurpub/ckac129.343 https://academic.oup.com/eurpub/article-pdf/32/Supplement_3/ckac129.343/48593664/ckac129.343.pdf |
genre |
Iceland |
genre_facet |
Iceland |
op_source |
European Journal of Public Health volume 32, issue Supplement_3 ISSN 1101-1262 1464-360X |
op_rights |
https://creativecommons.org/licenses/by/4.0/ |
op_rightsnorm |
CC-BY |
op_doi |
https://doi.org/10.1093/eurpub/ckac129.343 |
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European Journal of Public Health |
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32 |
container_issue |
Supplement_3 |
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1766042972520972288 |