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SNF Report No. 08/10
Are Pharmaceuticals
Still Inexpensive in Norway?
A Comparison of Prescription Drug Prices
in Ten European Countries
by
Kurt Richard Brekke
Tor Helge Holmås
Odd Rune Straume
SNF project no. 2353:
Comparison of Pharmaceutical Prices in Europe
The project is funded by the Norwegian Pharmacy Association
THE INSTITUTE FOR RESEARCH IN ECONOMICS AND BUSINESS
ADMINISTRATION (SAMFUNNS- OG NÆRINGSLIVSFORSKNING AS)
BERGEN, MAY 2010
© Dette eksemplar er fremstilt etter avtale
med KOPINOR, Stenergate 1, 0050 Oslo.
Ytterligere eksemplarfremstilling uten avtale
og i strid med åndsverkloven er straffbart
og kan medføre erstatningsansvar.
ISBN 978-82-491-0705-6 Printed version
ISBN 978-82-491-0706-3 Electronic version
ISSN 0803-4036
Foreword
On behalf of the Norwegian Pharmacy Association (Apotekforeningen), the Institute for
Research in Economics and Business Administration (SNF) has conducted the project
”Comparison of pharmaceutical prices in Europe”. The purpose of the project has been to
examine whether the price level of prescription drugs in Norway are higher (or lower) than in
comparable European countries. A part of the project has also involved finding a sound
method for comparing prices of pharmaceuticals. The data used are delivered by IMS Health.
This report is a follow-up of two previous reports on the same topic. The first report (SNF
report 05/08) was conducted for the Ministry of Health, while the second report (SNF report
06/09) was conducted for the Norwegian Pharmacy Association who is also funding the
current report. The continuation of this project has enabled us to further develop our analysis
and understanding of pharmaceutical pricing across countries. In addition, we can now study
the development in prices and price difference across the ten European countries over time.
The project has been undertaken by Professor Kurt R. Brekke (project leader) at the
Norwegian School of Economics and Business Administration, Senior Researcher Tor Helge
Holmås at the Uni Rokkan Centre, University of Bergen, and Associate Professor Odd Rune
Straume at the University of Minho (Portugal). The authors are affiliated to the Institute of
Research of Economics and Business Administration and the Centre for Health Economics in
Bergen.
We wish to express our gratitude to director Oddbjørn Tysnes and senior advisor Jon
Andersen at the Norwegian Pharmacy Association for useful suggestions and comments,
although this does not in any way make them responsible for the report’s content and
conclusions.
Bergen, May 2010
Kurt R. Brekke
Table of contents
Foreword
Abstract
1. Introduction ................................................................................................................... 1
1.1. Objective ....................................................................................................................... 1
1.2. Data and analyses ........................................................................................................ 1
1.3. Results .......................................................................................................................... 2
1.4. Structure of the report .................................................................................................. 3
2. Regulations in the prescription drug market ............................................................. 4
2.1. An overview and discussion of different regulatory instruments ................................. 4
2.2. A regulatory classification of the ten countries ........................................................... .6
3. Data and sample ............................................................................................................ .9
3.1. Sample .......................................................................................................................... .9
3.2. Price data ..................................................................................................................... 10
3.3. Volume data .................................................................................................................. 13
3.4. Volume-weighted average substance prices ................................................................ 13
3.5. Percentage margins ...................................................................................................... 14
3.6. The patent and generic market segments ..................................................................... 14
4. Price indices ................................................................................................................... 16
4.1. General aspects of price indices .................................................................................. 16
4.2. Price indices for identical packs .................................................................................. 17
4.3. Price indices based on average substance prices ........................................................ 21
4.4. Price indices for global substances .............................................................................. 24
5. Changes in prices and price indices from 2007 to 2009 ............................................. 26
5.1. Development in price indices 2007-2009 ..................................................................... 26
5.2. Nominal changes in pharmaceutical prices 2007-2009 ............................................... 29
6. Regression analyses ....................................................................................................... 31
6.1. Pharmacy prices (AUP) ............................................................................................... 31
6.2. Pharmacy margins ....................................................................................................... 33
7. Concluding remarks ...................................................................................................... 35
Appendix
Reference list
SNF Report No. 08/10
1
1. Introduction
1.1. Objective
In this study we compare prices of pharmaceuticals in Norway and nine Western
European countries, i.e., Austria, Belgium, Denmark, Finland, Germany, Ireland, the
Netherlands, Sweden and United Kingdom. These countries constitute the basket of
countries that form the basis for setting maximum prices for prescription drugs in
Norway, and can therefore be considered to be relatively comparable countries. The
objective of the study is to see whether prescription drugs are less or more expensive
in Norway than in other Western European countries. We also study the change in
price levels and price indices over the three last years. Finally, since we have
information on prices at both wholesale (AIP) and retail (AUP) level we also compare
pharmacy margins across the ten coutries.
1.2. Data and analyses
In this study we have obtained data from IMS Health for the 300 top-selling
(prescription bound) active substances in Norway in the first half of 2009. The data
set contains detailed information on price, volume, patent status, originals/generics,
pack size, presentation, strength, etc. We have prices per pack and per (standard) dose
for each product sold within the top 300 substances. Prices are at both wholesale
(AIP) and retail (AUP) level. Using the sales data, we compute volume-weighted
average prices for each active substance. We also calculate the (percentage) pharmacy
margins for all countries using the wholesale and retail prices. This data set is also
combined with similar data from 2007 and 2008 based on two previous studies by
Brekke, Holmås and Straume (2008, 2009), so that we in addition can study any
trends in prices and price differences.
When comparing prices across countries, we construct price indices in which the
various products are assigned weights to reflect a representative pattern of
consumption in the benchmark country. In this study, we use primarily Norwegian
consumption weights, where products or active substances with high sales levels
(measured in volume terms) in Norway are assigned a higher weight than products or
active substances with low sales levels. In this way, it can be ascertained what a
typical Norwegian “shopping basket” would cost in the various reference countries,
which gives us a measure of any cost savings.
The calculation of price indices entails a trade off between two aspects: precision
versus representativity. For pharmaceuticals, this appraisal is particularly important
because many types of pharmaceuticals are involved (for various conditions), and the
same pharmaceuticals come in many variants (original/generic, pack size, strength,
presentation, etc.). Precision is maximised by comparing the prices of the same packs
between countries. The top-selling pack for a given active substance is then typically
chosen in the benchmark country (Norway), and the price of this is compared with the
price of corresponding packs in other countries.
SNF Report No. 08/10
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The problem with price comparisons based on identical packs is that a representative
sample is rarely obtained. Firstly, it is often the case that the top-selling pack of a
given active substance in Norway is not the top-selling (and thus most representative)
pack in the reference countries. In many cases, this pack is not found in other
countries, which could typically give a false impression of price differences between
countries. Secondly, the comparison of identical packs will typically exclude generics
and thus lead to over-representativity of original preparations, resulting in the
overestimation of prices in countries with high levels of generic competition. In
addition, by selecting only the top-selling pack within a substance, a large amount of
information is ignored.
When we examine the sample of pharmaceuticals, both the number of active
substances and average pack sizes vary considerably between countries. This indicates
problems with representativity if the price comparisons are based on a narrow product
definition, i.e. identical packs. Using volume-weighted average prices per active
substance for each country reduces this problem. Most price indices are therefore
calculated on the basis of volume-weighted substance prices, but we also report price
indices based on comparisons of identical packs so that we take account of both
precision and representativity.
Many price indices are calculated in the study. First, we calculate bilateral price
indices, in which we match products or substances that are common to Norway and a
given reference country (say Sweden). We then calculate global price indices in which
we only compare prices of products or substances available in all countries in the
sample. The price indices are calculated for all active substances, but we also report
separate subindices for the patent and generic market segment, and also separate price
indices for pharmaceuticals subject to reference pricing (trinnprisregulering).
Using the data from 2007 and 2008, we examine the development in the price indices.
There are generally three reasons for why the price indices may vary over time. First,
prices of pharmaceuticals might change. Second, exchange rates might vary. Third,
there might be changes in the consumption weights and the sample of products across
years. Price changes can be detected by looking at the price change for products that
are in the sample each year. This gives us the nominal changes in prices for each
country from year to year. The impact of exchange rates is analysed by using last
year’s exchange rates to recalculate this years price indices.
1.3. Results
The main result is that UK, Norway and Sweden are the three cheapest countries in
the reference group of ten Western European countries, wheras Ireland, Belgium and
(usually) Germany are the three most expensive countries. This ranking is very robust
to how we compute the price indices and also fairly consistent across submarkets as
the patent and generic market segments (see summary of rankings according to the
various price indices in Table 7.1, p. 36). UK is usually the cheapest country, but for
the pharmaceuticals that are subject to reference pricing (trinnpris) in Norway, then
Norway is clearly the less expensive country.
SNF Report No. 08/10
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When we look at the development over time in the price indices, we see that Norway
becomes even less expensive during time. In fact, since 2007 and 2008, all countries
become more expensive relative to Norway. Using last year’s exchange rates, we
show that a significant part of the favourable change in the price indices is due to
currency fluctuations. However, we still find that Norway become cheaper compared
with the reference countries even after correcting for exchange rate fluctuations
(though the differences are much smaller). We then proceed by analysing the changes
in (nominal) prices for the products present in 2007 and 2008 using each country’s
own currency. Here we find that prices tend to decline in all countries, but the price
reductions in Norway are among the strongest.
Finally, we use regression analyses to study price differences across the ten European
countries in our sample. These analyses confirm our findings from the price index
analyses, though the differences in price levels are smaller. We also use regression
analysis to study differences in percentage (not absolute) pharmacy margins. These
analyses show that Norway has the lowest (percentage) pharmacy margins if we look
at all substances. In the patent segment, UK seems to have lower margins.
The low prescription drug prices and pharmacy margins in Norway are likely to be
due to strict price and markup regulation in the patent market segment combined with
several competition stimulating incentives in the generic market segments such as
reference pricing (trinnpris) and generic substitution regulations.
1.4. Structure of the report
The report is organised as follows. In Chapter 2 we describe the pharmaceutical
market and various regulatory regimes adopted in this market. We also classify the 10
countries included in this study with reference to the various types of regulatory
regimes. In Chapter 3 we provide an overview of the data and present some
descriptive statistics of key variables. In Chapter 4 we present price indices for
Norway and the nine reference countries. In Chapter 5 we analyse the change in price
indices over time. In Chapter 6 we conduct regression analyses to test whether the
differences in prices are statistically significant. We also test for differences in
pharmacy margins across countries. Finally, Chapter 7 concludes the report with a
brief summary of our main findings and a overview of the rankings of countries
according to price levels.
SNF Report No. 08/10
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Chapter 2. Regulations in the prescription drug market
The market for prescription drugs is generally characterised by low price elasticity of
demand and considerable market power on the supply side. From a policy perspective,
this is a worrying combination, since an unregulated market is expected to yield high
prices and a correspondingly high level of expenditures for drug consumption. Indeed,
most countries are using several regulatory instruments in order to control prices and
total consumption of prescription drugs. In this chapter we will give a brief overview
of some of the most important regulatory instruments used and briefly discuss how
different regulatory choices are expected to affect prices and demand for
pharmaceuticals. We will then categorise the ten different countries under study with
respect to the regulatory instruments used.
2.1. An overview and discussion of different regulatory instruments
We can make a fundamental distinction between supply-side and demand-side
regulation. Supply-side regulation attempts to control drug prices directly and can
apply to different levels of the vertical supply chain: manufacturers, wholesalers and
retailers (pharmacies). On the other hand, demand-side regulation attempts to control
prices indirectly through the design of the reimbursement system. In other words, we
can distinguish between regulation of the price that the suppliers of drugs receive
(supply-side regulation) and regulation of the price that consumers actually pay
(demand-side regulation). The latter type of regulation consists mainly of different
forms of reference pricing, where regulators attempt to increase the degree of
competition in the market through the design of the reimbursement system.
Reference Pricing
Reference pricing implies that drugs are classified into different reference groups
based on therapeutic effect. For each reference group, the regulator chooses a
reference price, which is the maximum reimbursable price for all drugs in the
reference group. Any positive difference between the actual drug price and the
reference price is not reimbursable.
The effect of reference pricing is to increase the price elasticity of demand for prices
above the reference price, which will stimulate price competition and yield lower
prices. The lower the reference price is set, the stronger is the effect on price
competition.
Generic reference pricing
Under generic reference pricing (GRP) the reference groups are constructed so that
each group only contains drugs with identical active chemical ingredients. This
implies that GRP by definition only applies for the off-patent market. Thus, GRP is a
regulatory instrument that is primarily intended to stimulate generic competition, with
the expected price effects occurring in the off-patent market.
SNF Report No. 08/10
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Therapeutic reference pricing
Under therapeutic reference pricing (TRP) the reference groups are constructed
according to therapeutic (but not necessarily chemical) equivalence. This implies that
drugs currently under patent protection can be included, provided the existence of
sufficiently close therapeutic substitutes. Thus, TRP implies that (part of) the on-
patent market is more directly exposed to stronger competition. It is therefore
reasonable to assume that TRP also will stimulate generic competition, leading to
lower prices, to an even stronger degree than GRP.
Other instruments to stimulate competition
In addition to specific reference pricing schemes, the demand side can also be
regulated through the more general design of the reimbursement system. An important
factor here is whether the patient co-payment is set as a fixed fee or as a percentage of
the drug price (or a combination of both). By designing the reimbursement scheme
such that the consumer pays a share of the actual drug price, the price elasticity of
demand is increased. However, the pro-competitive effect of a percentage co-payment
scheme is often counteracted by the fact that many countries (including Norway)
impose a cap on total drug expenditures (per year and sometimes per script) for
consumers.
The absence of both reference pricing and percentage co-payment should in principle
lead to a very low price elasticity of drug demand, with a correspondingly low degree
of price competition. Among the countries under study, this situation applies to three
countries: Austria, Ireland and UK.
Another instrument for stimulating price competition is to allow for generic
substitution by pharmacies. This means that, if a brand-name drug is prescribed, the
pharmacy can, if possible, dispense a cheaper copy drug instead. This could
potentially be a powerful regulatory instrument if generic substitution is either
compulsory or stimulated through financial incentives for the dispensing pharmacies.
Price cap regulation
Reference pricing (GRP or TRP) does not solve the problem of cost control for the
group of on-patent drugs where no close therapeutic substitutes exist. Therefore,
reference pricing is usually combined with supply-side regulation. The most common
way to regulate the supply side of the drug market is through price cap regulation,
which defines a maximum price for each drug.
Many countries have introduced a price cap regulation scheme commonly referred to
as international reference pricing. This regulatory scheme implies that the price cap
for a new drug is determined as a weighted average of prices for the same (or an
equivalent) drug in a pre-defined group of countries. This group usually consists of
countries with comparable price and income levels.
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The most obvious effect of international reference pricing is that is contributes to an
international harmonization of drug prices. The more countries that apply this
instrument the stronger the effect.
International reference pricing is now the most common type of price cap regulation
for prescription drugs and is applied in a majority of the ten countries under study.1
The exceptions are Denmark, Germany and UK.
Mark-up regulation
In addition to price-cap regulation at the level of manufacturers or wholesalers, most
countries also regulate the mark-ups of pharmacies (and, in fewer cases, wholesalers)
in order to control the drug prices that consumers face.
One interesting issue with respect to mark-up regulation is that different mark-up
schemes could affect the final consumer prices through the pharmacies’ dispensing
incentives. More specifically, if pharmacy mark-ups are set as a percentage add-on to
wholesale prices, pharmacies would have a financial incentive to increase their
(absolute) mark-ups by dispensing more expensive drugs. This incentive could be
eliminated by setting the mark-up as a flat fee. Even if the mark-up is set as a
percentage, the incentive for pharmacies to dispense more expensive drugs could be
counteracted by choosing a regressive mark-up scheme, where the percentage mark-
up is lower for more expensive drugs. As we will see below, all these alternatives are
currently in use by one or more of the ten countries under study.
2.2 A regulatory classification of the ten countries
Here we classify the ten countries according to the different instruments used in
demand-side regulation (Table 2.1) and supply-side regulation (Table 2.2). Notice that
this distinction is not always clear-cut. For example, although we have categorized
generic substitution as demand-side regulation, this could arguably also be classified
as a supply-side instrument. The information is mainly extracted from the PPRI
Project (”Pharmaceutical Pricing and Reimbursement Information”).2
When making this classification, it is important to bear in mind that many real-world
regulatory schemes combine elements from the more stylized regulatory models
presented above. This means that the assignment of different countries to different
regulatory schemes is not always clear-cut. In Table 2.1, ambiguous classifications are
marked with an asterisk and apply to Belgium, Ireland, Norway and Sweden.
Let us briefly comment on the ambiguous classifications. First, the reference pricing
system used in Belgium can be described as an unusually far-reaching form of GRP.
The reason is that the scheme was extended in 2007 to include, in principle, off-patent
brand-name drugs without generic competitors in the market. Regarding Ireland, the
1 In some cases, international reference pricing is combined with other criterias, such as therapeutic
benefit, when setting the price cap.
2 Available at http://ppri.oebig.at
SNF Report No. 08/10
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generic substitution scheme is unusually weak, in the sense that generic substitution is
merely allowed, but not encouraged through direct instructions or financial incentives.
We have also classified Norway as a country with generic reference pricing, although
this is not the official name given to the current scheme. However, the system
nevertheless has the fundamental ingredients of a reference pricing system (with an
exogenously determined reference price). The same argument applies to Sweden,
which does not officially use generic reference pricing. However, since it is
compulsory for pharmacies to perform generic substitution, unless the patient chooses
to pay the price difference between the brand-name drug and the cheapest available
generic drug, the system is a de facto generic reference pricing scheme. Finally, it is
also worth mentioning that even if Germany uses percentage co-payments, this
applies only to certain price intervals.
Table 2.1 Demand-side regulation
Country Generic
reference
pricing
Therapeutic
reference
pricing
Generic
substitution Percentage
copayment
Austria No No No No
Belgium Yes* No No Yes
Denmark Yes No Yes Yes
Finland Yes No Yes Yes
Germany No Yes Yes Yes
Ireland No No Yes* No
Netherlands No Yes Yes No
Norway Yes* No Yes Yes
Sweden Yes* No Yes Yes
UK No No No No
Regarding recently implemented reforms in these countries, it is worth noticing that
Finland introduced generic reference pricing from 1 April 2009. It is reasonable to
expect that this should lead to lower prices, particularly in the off-patent segment.
As previously mentioned, Austria, Ireland and UK are the “outliers” in this group in
the sense that hardly any regulatory instruments are used to stimulate generic
competition. These countries do not have generic reference pricing, percentage co-
payments or regulatory schemes that provide incentives for generic substitution. On
the other hand, Germany and the Netherlands are the only countries that apply
therapeutic reference pricing, which stimulates competition not only in the off-patent
market, but also among on-patent drugs.
SNF Report No. 08/10
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Table 2.2 Supply side regulation
Country International
Reference
pricing
Mark-up regulation
Wholesalers Pharmacies
Austria Yes Regressive (%) Regressive (%)
Belgium Yes Linear (%) Linear (%)
Denmark No No direct regulation Linear (% + flat fee)
Finland Yes No direct regulation Regressive (% + flat fee)
Germany No Regressive (% + fixed fee) Linear (% + flat fee)
Ireland Yes Linear (%) Linear (%)
Netherlands Yes No direct regulation Fixed fee mark-up
Norway Yes No direct regulation Linear (% + flat fee)
Sweden No No direct regulation Regressive (% + flat fee)
UK No No direct regulation No direct regulation
Regarding the use of supply side regulation, we see that the combined choice of
instruments varies quite a lot among the different countries under consideration. The
most consistent pattern is that in all but one country, mark-up regulation at pharmacy
level is applied (the only exception is UK, where pharmacy remuneration is based on
fee-for-services). Several countries also use regressive mark-up schemes (or just a flat
fee in the case of the Netherlands) in order to counteract pharmacy incentives to
dispense more expensive drugs.
SNF Report No. 08/10
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Chapter 3. Data og sample
Data for the price comparisons have been provided by Intercontinental Medical
Systems (IMS).3 We have obtained data from IMS for Norway and the following nine
reference countries: Austria, Belgium, Denmark, Finland, Germany, Ireland, the
Netherlands, Sweden and the United Kingdom. The reference countries comprise the
nine countries included in Norway’s basket for setting maximum prices for
prescription pharmaceuticals. In this part of the report we provide an overview of data
and the sample of active substances, with particular emphasis on how the prices are
calculated.
3.1. Sample
We have got price and volume data for all prescription bound products sold in the 300
top-selling (measured in terms of sale value) active substances in Norway over the
period 1 January to 30 June 2009.4 The sample comprises exclusively pharmaceuticals
sold via pharmacies. Pharmaceuticals purchased and sold in hospitals are not
included.5
The data set contains detailed information on prices and volumes per month for the
period in question. In addition, the data contain information on a number of other
aspects such as active substance name, therapeutic classification, product name,
producer, original or generics, patent status, pack formulation (capsule, tablet,
strength, etc.), and pack size.6
Information on patent status was missing for 21 active substances. These are mainly
older pharmaceuticals (vaccines and a few combination pharmaceuticals). Since we
do not know whether these products are patent protected or not, we exclude these
from our sample, which leaves us with 279 active substances for Norway.
As expected, not all of the 279 active substances on the Norwegian market are sold in
the comparison countries. Table 3.1 below shows how many of the top-selling
Norwegian active substances are sold in the other countries. We can see that for the
entire sample, the number of active substances varies from 300 in Norway to 266 in
Belgium. If we limit the sample to active substances with patent status, the number of
active substances varies from 279 in Norway to 246 in Belgium. If we consider active
substances sold in all countries – which we refer to as globally active substances – the
number is 219 for the entire sample and 198 if we exclude pharmaceuticals without
3 IMS is a company that has specialised in collecting data on pharmaceutical sales throughout the
world.
4 These were the 300 top-selling products over the period September 2008 to September 2009. The
turnover figures are based on prescription pharmaceuticals sold via pharmacies.
5 The sample includes certain pharmaceuticals that can be called hospital pharmaceuticals in the sense
that they are prescribed and often consumed in connection with hospital treatment, e.g. etanercept
(Enbrel). However, these are only included in our data if the patient obtains these preparations via a
hospital pharmacy or a private pharmacy.
6 In the case of pharmaceuticals not in tablet form, there may be some deficiencies, particularly with
regard to strength.
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information on patent status. This is a relatively high level of representativity,
indicating that the comparison group is good.
Table 3.1 Number of active substances in Norway and the reference countries, 2009
All
substances Substances
without patent
status
Substances on
reference pricing
(trinnpris)
Substances in the
sample
Norway 300 21 45 279
Sweden 290 17 44 273
Denmark 285 17 45 268
Finland 279 16 45 263
UK 271 15 44 256
Germany 277 18 43 259
Netherlands 280 16 44 264
Belgium 266 20 44 246
Austria 271 18 45 253
Ireland 272 15 45 257
Global active
substances 219 - 41 198
3.2. Price data
Pharmaceutical prices arise in three forms: producer prices, wholesale prices and
pharmacy prices. We follow the established terminology and refer to producer prices
as the wholesale purchase price (GIP), wholesale prices as the pharmacy purchase
price (AIP) and pharmacy prices as the pharmacy sale price (AUP). In the study we
primarily focus on AUP since this is the price that the public authorities (insurers) and
patients face. However, we also compute price indices at wholesale level (AIP). The
difference between AUP and AIP is the gross margin obtained by the pharmacies. We
also take a closer look at this.
IMS collects price data in different ways in the individual countries. In principle, it
collects information on actual pricing at a point in the distribution chain. It then uses
detailed information from each country on discounts, profit regulations and
reimbursement prices to calculate the other prices. It also calculates wholesale and
pharmacy margins where necessary. The table below provides an overview of how the
price data from IMS have arisen for each country.
All prices are free of value added tax (VAT). Price differences therefore do not reflect
differences in VAT between countries. Most countries in the sample have lower value
added tax than Norway, apart from Denmark, which also has a VAT rate of 25%.
Sweden, for example, has no VAT on prescription pharmaceuticals, followed by
Belgium and the Netherlands with only 6% VAT. From economic theory, we know
that high taxes can contribute to producers cutting their prices to avoid losing sales.
However, as long as demand for pharmaceuticals is relatively price inelastic, it is
likely that patients bear much of the burden associated with high levels of VAT.
The prices from IMS are in the individual country’s currency. We have converted all
prices to the Norwegian currency, so all prices are expressed in Norske kroner (NOK).
For each month, we use the average exchange rate for the previous six months: For
January 2009, we thus use the average exchange rate for the period from August up to
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and including December 2008; for February 2009, we use the average exchange rate
for the period from September 2008 up to and including January 2009, etc.
Table 3.2. IMS price data: Observed price, source, calculation of AUP and AIP.
Country Observed
price Source Calculation of AUP and AIP
Austria
GIP Official list prices
from producers
AIP and AUP are calculated by applying regulated
markups for wholesalers and pharmacies.
Belgium AUP Association
Pharmaceutique
Belge
6 % VAT is deducted from AUP.
AIP is calculated by using reimbursement prices and
regulated pharmacy markups.
Denmark AIP Wholesaler
invoices
AUP is calculated by applying regulated pharmacy
markups.
Finland AIP Finnish
pharmaceutical
association
AUP is calculated by applying regulated pharmacy
markups and specific charges.
Germany
GIP German Health
Institute (Lauer-
taxe database)
AIP and AUP are deducted by applying regulated
markups. Repayments (clawback) to the sickness
insurance funds are then deducted.
Ireland AIP Official list prices
from wholesalers AUP is calculated by applying regulated pharmacy
markups and information on reimbursement prices.
The Netherlands AIP Pharmacy invoices AUP is calculated by deducting estimated AIP discounts
and then applying regulated pharmacy markups.
Norway AIP Wholesale invoices AUP is calculated by applying regulated pharmacy
markups.
Sweden
AIP Apoteket AUP is calculated by applying regulated pharmacy
markups.
United
Kingdom AIP National Health
Service AUP is calculated by deducting estimated AIP discounts
and then applying regulated pharmacy markups
(dispensing fees).
Price data come in two variants: price per pack and price per dose. The price per pack
will be used when we compare identical packs across countries. We select the best-
selling pack in Norway for a given active substance and compare the price of the same
pack in the reference countries, where these exist. The advantage of this approach is
that precision is ensured in the sense that exactly the same product is compared across
countries.
However, the disadvantages are many, and essentially relate to a lack of
representativity. Firstly, picking only the best-selling pack for each substance, implies
that we throw away information about all other packs for this substance. For Norway
there are almost 2500 products, implying an average number of products for each
substance of about 8. Thus, comparing prices per pack implies that we on average
eliminate 7 products per substance. If we look at the overall number of products, we
eliminate information of 2200 products by this procedure, and this is just for Norway.
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Secondly, the top-selling (and thus most representative) pack in Norway may not be
among the top-selling ones in the reference countries. In the worst case, this pack is
not sold at all in these countries. Table 3.3 below shows the average pack size for the
countries in the sample.
Table 3.3 Average number of doses per pack.
All active substances Substances with patent
status
Austria 28.8 28.9
Ireland 43.2 43.4
UK 44.0 44.6
Belgium 44.2 44.3
Norway 50.6 49.9
Germany 51.6 51.6
Finland 52.1 51.6
Denmark 55.2 55.4
Netherlands 55.3 56.0
Sweden 69.8 69.0
We see that average pack size varies between the countries in the sample. Austria has
the smallest packages, with an average of 28.8 doses per pack. Sweden, on the other
hand, has the largest packages, with an average of 69.8 doses per pack, which is more
than double the size of Austria. The pack size in Norway is fairly average of the
countries in the sample.
Finally, comparing prices of identical packs will mean that generics often drop out. In
the case of active substances that have come off patent, there are often a number of
generic products on the market, and these often have a smaller market share than the
original product. A selection based on top-selling packs within an active substance
could then lead to low representativity of generic products in the segment for non-
patent-protected products, and not give a true picture of the price because the original
preparation is typically higher priced than generics.
Price per dose is indicated by price per IMS standard unit7. A standard unit is a proxy
for a dose, and is defined by IMS as a tablet, a capsule, 10 ml liquid, etc. It is difficult
to find a perfect measure of a dose, but so long as a dose is relatively constant across
the countries in the sample, this will be relatively unproblematic. The advantage of
price per dose is that these are defined for all packs and formulations. This makes it
possible to calculate an average price for each active substance. Such an approach
means that we make use of all price information. This also ensures a good
representation of generics. As we will explain later, we weight the prices for an active
substance by volume, so that we attach greater importance to the price of products that
sell more than to the price of products that sell less. The weightings are calculated on
the basis of each country’s sales, so that we obtain the most representative price for
each country. In this way, we achieve a high level of representativity. This approach is
in line with Danzon and Chao (2000), who also provide a discussion of these two
approaches.
7 There are other dose measures used such as price per defined daily dose (DDD), price per gram of
active substance, etc. These are not available to us via IMS’s data set.
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3.3. Volume data
The data set contains two types of volume data: number of packs and number of
doses, where the number of doses is represented by IMS standard units as described
above. The volume data are per product (article number) and per month for each of
the countries we include in the sample for the whole period.
Volume data are used primarily to weight prices. The number of packs sold is not
especially suitable for calculating weights as packs, both within active substances and
not least across active substances, have differing numbers of doses (tablets, capsules,
etc.). Active substances that typically have many doses in a pack will then be given
too low a weight, and vice versa. We therefore use the number of doses as a basis for
calculating weights.
We have two types of volume weights: (i) Weights across active substance and packs
and (ii) weights within active substances. The weights within an active substance are
used to calculated average prices, as will be described in section 3.4. The weights
across active substances and packs are used to calculate indices, where they will
reflect consumption patterns so that prices of active substances with high sales (high
number of doses) are assigned a higher weighting than prices of active substances
with low sales. As Norway is the starting point for the study, the price indices will be
calculated with Norwegian consumption weights. This is presented in more detail
when we calculate prices and indices in the next two chapters.
3.4. Volume-weighted average substance prices
For each active substance, we have a number of different pack types and we also have
data for six months. This means that, for each active substance, we have a number of
price observations (per dose) where some active substances have relatively few
observations and others have relatively many. Furthermore, it is the case that some
pack types have relatively high sales, while others are sold to a lesser extent. The aim
of the volume-weighted average prices is precisely to take account of this, i.e. we
want to weight the prices per dose of the top-selling pack types more than the lower-
selling packs. To take care of this, we have, for each active substance and for each
country, weighted the price per dose with the proportion of sales this pack accounts
for out of total turnover for the active substance in this country. We then sum the
volume-weighted prices within each active substance, and thereby get a price per dose
per active substance. A simple example may make things clear: Assume that for
active substance A (for example in Norway) we have three different packs with the
following prices and turnover:
Pack 1A: the price is NOK 10 per dose and turnover is 5 doses
Pack 2A: the price is NOK 20 per dose and turnover is 10 doses
Pack 3A: the price is NOK 30 per dose and turnover is 15 doses
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The volume-weighted average price per dose then becomes:
33.23
30
15
30
30
10
20
30
5
10 NOKNOKNOKNOK
The arithmetic (unweighted) mean in the example above is NOK 20. The volume-
weighted average price in the example then becomes higher because the most
expensive packs are the top-selling ones. If this has been the opposite – i.e. if turnover
of the more expensive packs had been relatively low – the volume-weighted average
price would conversely have been lower than the arithmetic mean.
Many studies compare prices of identical packs instead of calculating the average
price within an active substance. The top-selling pack in the base country is then
selected, and the price of this pack is then compared with corresponding packs in the
reference countries. In our example, pack 3A is the top-selling one with a price of
NOK 30. The problem with this approach is, as mentioned earlier, that this pack may
not exist or may have lower sales in the reference countries. In addition, we throw
away a lot of information by excluding other pack sizes in the price comparison.
Volume-weighted average prices take account of both these aspects, and yield a much
higher level of representativity.
3.5. Percentage margins
As we have information on pharmacies’ sale price (AUP) and pharmacies’ purchase price
(AIP), it is possible to say something about how the margins vary between countries. To
calculate the margins, we use the most common method (the Lerner index) for calculating
relative margins/price supplements in a market:
100
i
ii
AUP
AIPAUP
M
The margin is thus measured as a percentage of the pharmacies’ sale price (AUP). For
each country, we use volume-weighted average AUP and AIP per active substance
and calculate margins on the basis of these prices as described above.
3.6. The patent and generic market segment
The sample contains pharmaceuticals that are on patent and pharmaceuticals whose
patents have expired and copy preparations (generics) have been launched, or could
potentially be launched, as an alternative to the original preparation. It may be useful
to break down the sample according to whether or not the pharmaceutical is protected,
partly because the competitive situation is different and partly because many
countries, including Norway, use different regulations of these two segments. In
addition, it is the case that a certain yield (and thus a higher price) will be ensured
during the patent period to promote innovation in pharmaceuticals, while the lowest
possible price is a natural policy target once the patent has expired. One way of
dividing the sample could be to use the patent status variable in the data set. It
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emerges, however, that pharmaceuticals within the same active substance are
registered both as being on patent (protected) and off patent (not protected). In
addition, this variable is difficult to use across countries. We have therefore chosen
not to use this variable. However, the data set contains information on whether a
pharmaceutical is an original preparation or generic.8 We therefore observe whether
generics are sold within an active substance. In the light of this information, we
construct the following two sub-indices:
1. Active substances without actual generic competition in Norway.
2. Active substances with actual generic competition in Norway.
The first index represents the patent segment, while the second index represents the
generics segment. All active substances for which we report the sale of generics in
Norway in January 2009 are classified as having generic competition. In the case of
active substances that do not have generic competition in the first period (January
2009), but have generic competition in one of the next 5 months, we classify the
active substance as being without generic competition up to the month when we first
report actual generic competition.
Table 3.4 Active substances with generic competition in Norway and globally
All active
substances Without generic
competition in
Norway
With generic
competition
in Norway
Without generic
competition
globally
With generic
competition
globally
Norway 279 159 120 116 163
Sweden 273 154 119 114 159
Denmark 268 152 116 104 153
Finland 263 148 115 109 154
UK 256 140 116 97 159
Germany 259 148 111 108 151
Netherlands 264 147 117 105 159
Belgium 246 134 112 98 148
Austria 253 136 117 99 154
Ireland 257 144 113 104 153
A potential problem with using actual generic competition in Norway as a basis for
classification in the patent and generics segment is that the size of the patent segment
may be overestimated, as substances might have gone off patent without generic
competition taking place in Norway. This classification may therefore give rise to
incorrect estimation of price differences. In Brekke, Holmås and Straume (2008) we
therefore also used a different approach to separate the patent and the generic market
segments. In particular, we defined the patent segment by active substances that did
not have generic competition in any country. The generic segment would then be the
residual number of active substances that had generic competition in at least one
country. However, as the results turned out to be quite similar regardless of which
approach we used, we choose not to include these indices in this report.
8 This information does not exist for certain pharmaceuticals. This group is equivalent to those that do
not have patent status, as discussed in the introduction. These (21) active substances are excluded from
the data set, so that we are left with (279) active substances with information on whether an original
preparation or generic is involved.
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Chapter 4. Price indices
In this chapter we present the results for the various price indices we have calculated
for Norway and the nine reference countries. Price indices are often sensitive to how
these are calculated. We have therefore conducted a number of different
approximations for calculating the indices. First, we compare prices of identical packs
between countries. Second, we compute volume-weighted average prices per dose per
substance and use these to compare prices and construct price indices. Third, we
calculate bilateral and global price indices at wholesale (AIP) and retail (AUP) level.
Finally, we calculate separate indicies for the patent and generic market segments, as
well as for the substances subject to reference pricing (trinnpris). Before we present
the analyses, we provide a brief theoretical presentation of price indices generally.
4.1. General aspects of price indices
A price index is a weighted average of prices for different products, generally
calculated over time, such as the consumer price index. If we have two time periods,
period 0 and t, and two products, product 1 and 2, we can express a price index as
follows:
,100
2
0
21
0
1
2211
wpwp wpwp
Itt
P
where w1 and w2 are weights applied to the respective prices and tt pppp 2
0
21
0
1 and ,,. In
calculating price indices, it is customary to use sold quantities as weights to take
account of the relative importance of the various product prices. We can obtain two
different indices depending on the choice of weights. If we choose sold quantities in
the last period (period t) as weights, we obtain the so-called Paasche price index:
,100
2
0
21
0
1
2211
tt
tttt
Pqpqp qpqp
P
where tt qq 21 and are quantities of product 1 and 2 sold in period t. If we choose
quantities sold over the base period (period 0) as weightings, we obtain the so-called
Laspeyres price index:
,100
0
2
0
2
0
1
0
1
0
22
0
11
qpqp qpqp
Ltt
P
where 0
1
q and 0
2
q are quantities of product 1 and 2 sold in period 0. Both these price
indices will express changes in average prices over time. If prices are less (more) than
100, this means that there has been a reduction (increase) in average prices over the
period.
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In this study, we calculate differences in average prices across countries (not over
time) to see whether the prices of pharmaceuticals in Norway are higher or lower than
in other countries. Let us assume two countries, Norway and Abroad, where products
1 and 2 are sold (but with potentially different quantities). The general price index can
then be expressed as
,100
2211
2211
wpwp wpwp
INN
UU
P
where U
p1 and U
p2 are the prices of product 1 and 2 abroad, and N
p1 are N
p2 the
prices of products 1 and 2 in Norway, and w1 and w2 are the weights to be applied to
these different prices. It is customary to use weights to express the relative importance
of the products including when price indices are to be calculated across countries. If
we use quantities sold abroad as weights, we calculate a Paasche price index. It is
nevertheless natural in this context to use quantities sold in Norway as weights, giving
us a Laspeyres price index, which can be expressed as follows:
,100
2211
2211
NNNN
NUNU
Pqpqp qpqp
L
where N
q1 and N
q2 are quantities sold of products 1 and 2 in Norway. If the price
index is more (less) than 100, this means that average prices abroad are higher (lower)
than in Norway. However, it does not mean that all prices are higher abroad than in
Norway. We can imagine that product 1 has a higher price abroad than in Norway
(NU pp 11 ), while it is the converse for product 2 ( NU pp 22 ). The effect on the price
index will thus be determined by the weighting, which in our case is determined the
Norwegian consumption weights. If product 1 has a low sales volume relative to
product 2 in Norway ( NN qq 21 ), this may give rise to a price index of less than 100,
i.e. on average the price level in Norway is lower than abroad.
For most price indices, we will use Norwegian quantity weightings. In this way, we
measure what a Norwegian “shopping basket” costs abroad. If Norway is more
expensive than the reference countries, the differences in the price index may be
interpreted as the cost savings that could be achieved by importing the foreign price
level. In Brekke, Holmås and Straume (2008) we also conducted sensitivity analyses
where we used Swedish and Danish quantity weightings to see whether the price
indices change. Such a comparison means that we import both foreign prices and
foreign shopping baskets into Norway. The latter is a more unrealistic measure of
possible cost savings. However, the results were fairly robust to these sensitivity
checks.
4.2. Price indices for identical packs
Let us first compare prices between countries for identical packs, i.e. packs with same
size (e.g. 100 tablets) and strength (e.g. 500 mg Paracetamol). For each of the 279
active substances, we select the top-selling (measured in number of doses) pack in
Norway. For certain (28) active substances, the data set does not contain information
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on strength. To ensure that we do not compare the price of packs with different
strengths, these are excluded. We are left with a sample of the 251 top-selling packs in
Norway. These packs are then linked to corresponding packs in the reference
countries. We do not require the packs to be available in all countries (global) to be
included in the calculation. The matching is carried out bilaterally for each country, so
that the number of packs included varies between the reference countries from 190 in
Sweden to 63 in Ireland. We then calculate paired price indices for each country based
on the selected packs. The prices are weighted with Norwegian consumption weights,
where the weights are simply the number of doses sold of a given pack divided by the
total number of doses sold. The Norwegian consumption weights are calculated for
each reference country depending on which packs are included in the sample.
All the price indices we calculate based on prices of identical packs are reported in
Table 4.1 below. We will now only focus on the main results. Figure 4.1 reports the
price indices for all packs in the sample at wholesale (AIP) and pharmacy (AUP)
level. We have ranked the countries from cheapest to most expensive based on
pharmacy prices (AUP), which we consistently will do in this chapter.
Figure 4.1 Bilaterale price indices, identical packs, AUP and AIP.
If we look at final pharmacy prices, we see that only UK is less expensive (about 18.2
per cent) than Norway. The third cheapest country is Sweden where prices of
prescription drugs are slight (8.1 per cent) more expensive than Norway. The most
expensive countries are Ireland (72 per cent), Belgium (71 per cent) and Germany (61
per cent). However, if we look at the wholesale level (AIP), the picture is slightly
different. Norway is now the cheapest country, followed by UK (0.4 per cent) and
Sweden (7 per cent). The most expensive countries are Belgium (71 per cent),
Germany (53 per cent) and Denmark (38 per cent). Ireland is only 22 per cent more
expensive than Norway at AIP level. The differences between AUP and AIP are due
to differences in pharmacy profit margins, which are very high in especially Ireland
but also Finland. On the contrary, UK has very low pharmacy margins, which
explains why they are so cheap at retail (AUP) level.
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Table 4.1: Bilateral price indices (AIP and AUP) based on prices of identical packs (same size and strenght).
Norway Sweden Denmark Finland UK Germany Netherlands Belgium Austria Ireland
All substances
AIP per pack 100 107,3 138,2 114,3 100,4 153,9 126,0 171,3 120,0 122,2
AUP per pack 100 108,1 137,8 137,9 82,8 161,8 120,5 171,8 124,5 172,9
Number of packs 190 164 161 68 134 77 93 76 63
Substances on patent (without generic competition)
AIP per pack 100 107,3 136,6 112,6 96,6 158,2 122,0 168,4 119,6 116,3
AUP per pack 100 106,9 138,4 136,5 80,8 160,8 115,7 168,4 124,3 165,4
Number of packs 108 96 89 43 77 51 62 52 42
Substances off patent (with generic competition)
AIP per pack 100 107,4 143,4 119,9 109,3 139,9 144,8 184,1 121,5 160,1
AUP per pack 100 111,2 136,2 141,9 87,1 164,9 141,1 186,2 125,2 214,8
Number of packs 82 68 72 25 57 26 31 24 21
Substances under reference pricing (trinnpris)
AIP per pack 100 111,4 149,5 124,8 175,8 185,1 251,5 235,2 146,8 211,1
AUP per pack 100 113.0 142,8 150,9 123,9 201,4 225,5 232,6 152,7 279,2
Number of packs 37 33 36 7 24 10 20 8 6
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Figure 4.2 below summarises the price indices for the on-patent prescription drugs.
We see that the picture is fairly consistent with the overall rankings. UK is 19.8 per
cent cheaper than Norway at pharmacy level, wheras Sweden is 6.9 percent more
expensive. In the other end, Belgium and Ireland have changed rankings. Belgium is
now the most expensive country with 68.4 per cent higher prices than Norway, while
Ireland has 65.4 per cent higher drug prices in the on-patent market segment at
pharmacy (AUP) level. If we look at AIP level, Ireland becomes even less expensive,
with the difference indicating high pharmacy margins.
Figure 4.2: Bilateral price indices, identical packs, on-patent market segment.
Finally, we take a look at the generic market segment. Figure 4.3 below illustrates the
price indices at AUP level for off-patent products with generic competition both at the
overall level and for the set of off-patent products under reference pricing (trinnpris)
in Norway.
Figure 4.3: Bilateral price indices, identical packs in the generic market segment and
under reference pricing (trinnpris), AUP.
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If we look at the price indices for top-selling packs with generic competition (called
“generic”), UK is still cheapest (12.9 per cent) followed by Norway and Sweden that
is 11.2 per cent more expensive than Norway. As before, Ireland, Belgium and
Germany are the most expensive countries. However, if we look at the products
subject to reference pricing (trinnpris) in Norway, then Norway is the cheapest
country followed by Sweden (13 per cent more expensive) and UK (23 per cent more
expensive). For these products also the price differences are much larger than for the
rest of the products. Ireland is for instance about 175 per cent more expensive on the
same packs as in Norway at retail level.
As mentioned above, a main problem with price indices based on identical packs is
that representativity is low.9 We therefore proceed by calculating price indices based
on the volume-weighted average prices per substance per dose.
4.3. Price indices based on average substance prices
We start out by calculating bilateral price indices. The procedure is the same as for
identical packs, apart from the fact that here we match active substances instead.
Table 4.2 below presents all bilateral price indices we have calculated based on the
volume-weighted average substance prices per dose. Here we only focus on the main
results.
Figur 4.4: Bilateral indices, average substance prices, AUP and AIP, all substances.
From the figure we see that UK is still the cheapest country when we compare prices
of all substances, but the price differences are much smaller than for identical packs
(see Figure 4.1). UK is now only 2.1 per cent less expensive than Norway. Sweden is
the third cheapest country, while Ireland and Belgium are the most expensive
countries. If we look at wholesale prices (AIP), Norway is the cheapest country
followed by Sweden and UK. This picture is fairly similar to the one we got when
comparing prices of identical packs.
9 See Danzon and Chao (2000) for a full discussion and analysis of the problems associated with basing
price indices on identical packs.
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Table 4.2. Bilateral price indices (AIP and AUP) based on volume-weighted average substance prices per dose.
Norway Sweden Denmark Finland UK Germany Netherlands Belgium Austria Ireland
All substances
AIP per dose 100 114,4 141,5 122,1 116,8 144,7 126,9 216,0 140,6 228,3
AUP per dose 100 112,2 136,3 142,4 97,9 161,8 141,0 215,5 147,9 313,5
Number of substances 273 268 263 256 259 264 246 253 257
Substances on patent (without generic competition)
AIP per dose 100 118,2 144,9 120,4 102,7 144,2 133,5 175,9 125,1 135,3
AUP per dose 100 116,8 145,0 146,1 88,6 152,4 134,3 177,3 137,7 195,7
Number of substances 154 152 148 140 148 147 134 136 144
Substances off patent (with generic competition)
AIP per dose 100 107,3 135,0 125,2 138,6 145,7 114,3 291,1 169,2 400,9
AUP per dose 100 105,1 122,8 136,7 109,9 176,9 151,3 274,2 163,2 492,9
Number of substances 119 116 115 116 111 117 112 117 113
Substances under reference pricing (trinnpris)
AIP per dose 100 126,9 150,5 133,7 142,0 187,8 136,7 272,3 207,6 321,4
AUP per dose 100 114,5 135,6 144,0 112,9 187,0 167,3 244,7 199,7 397,9
Number of substances 44 45 45 44 43 44 44 45 45
Table 4.3. Global price indices (AIP and AUP) for substances present in all countries based on volume-weighted average substance prices per dose.
Norway Sweden Denmark Finland UK Germany Netherlands Belgium Austria Ireland
All substances (N = 198)
AIP per dose 100 117,7 139,3 124,1 110,4 146,2 125,7 184,0 141,7 174,0
AUP per dose 100 114,8 133,8 146,4 93,3 160,3 138,5 182,5 150,8 241,5
Substances on patent (without generic competition) (N = 104)
AIP per dose 100 119,9 143,8 120,6 104,2 145,7 138,0 176,6 125,4 129,5
AUP per dose 100 118,2 143,5 148,7 89,5 155,3 138,8 179,5 141,0 187,9
Substances off patent (with generic competition) (N = 94)
AIP per dose 100 114,0 131,9 129,9 120,7 146,9 105,4 196,3 168,6 247,5
AUP per dose 100 110,1 120,5 143,2 98,6 167,1 138,1 186,5 164,2 315,3
Substances under reference pricing (trinnpris) (N = 41 )
AIP per dose 100 129,9 148,5 137,4 139,6 190,0 137,3 270,6 204,7 317,9
AUP per dose 100 116,6 132,0 148,6 111,1 188,8 166,9 243,2 197,9 392,7
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We also calculate separate price indices for the patent and the generic market segments. We
see from Table 4.2 that the picture for the patent segment is quite similar to the one for all
substances. However, this is not the case for the off-patent market segment. The price indices
for this market segment are given by Figure 4.4 below.
Figure 4.4: Bilateral indices, average substance prices, generic market segment
If we look at the pharmacy prices (AUP), we see that Norway is now the cheapest country
followed by Sweden (5 per cent more expensive) and UK (9 per cent more expensive). Thus,
the results are sensitive to whether one compares prices of identical packs or average price per
dose for substances common to both countries. As before, Belgium and Ireland are by far the
most expensive countries in the generic market segment. This pattern is fairly similar if we
look at the wholesale prices, though the price differences become lower, and some countries
(Ireland, Germany and the Netherlands) become relatively less expensive. The change in
ranking and price differences between AUP and AIP reflects differences in retail pharmacy
margins.
A subset of substances in the generic market segment is subject to reference pricing
(trinnpris). Figure 4.5 shows the price indices for this segment. We see that Norway is even
cheaper than its reference countries for these products. UK is the second cheapest country
being 12.9 per cent more expensive than Norway, whereas Sweden is the third cheapest
country with 14.5 per cent higher prices than Norway. Belgium and Ireland are by far the
most expensive countries also for this set of substances.
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Figure 4.5: Bilateral indices, average substance prices, reference pricing (trinnpris)
4.4. Price indices for global substances
An alternative way of calculating price indices is to limit the sample to active substances for
which we have price observations in all countries, i.e. global matching. An advantage of this
approach is that we have price observations for all active substances in the sample. Another
advantage is that the comparison between two foreign countries, say, Sweden and UK, is now
more precise since we compare prices of products that are present in every country. When we
apply the requirement of global matching, the number of active substances in the sample is
reduced to 198, which equates to about 70% of the total sample of active substances in
Norway. While we lose some observations, the representativity is still very high and much
higher than the price comparisons of identical packs. We calculate several price indices based
on global substances, which all are reported in Table 4.3 above. Below we focus on the main
results from these figures.
Figure 4.6 shows the global price indices for all (198) active substances at both wholesale
(AIP) and retail (AUP) level. We see that UK is still the cheapest country if we look at retail,
pharmacy prices, being about 6.7 per cent less expensive than Norway. Norway is as before
the second cheapest country, followed by Sweden, where prices are on average 14.8 per cent
higher than in Norway. Belgium and Ireland are the two most expensive countries as usual. At
wholesale (AIP) level Norway is the cheapest country, which is also what we found using
bilateral price indices. The reason UK is cheaper than Norway is that they have lower
pharmacy margins. We also see that the price spread is lower at AIP level than at AUP level.
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Figure 4.6: Global indices, average substance prices, all substances.
Figure 4.7 present the price indices at AUP level for the generic market segment, as well as
the subset of off-patent substances that are subject to reference pricing (trinnpris) in Norway.
We see that UK have only marginally lower (1.4 per cent) prices at the generic market
segment, while Norway is 11.1 per cent cheaper for the off-patent substances under reference
pricing (trinnpris). Sweden is third as usual, followed by Denmark.
Figure 4.7: Global indices, average substance price, off-patent market segment (AUP)
The overall conclusion is that the rankings seem to be fairly consistent and robust across the
various approaches in how to calculate the price indices. There are some differences across
market segments, but UK, Norway and Sweden are consistently the three cheapest countries
in all indices, and Germany, Belgium and Ireland are the three most expensive countries in
almost all price comparisons.
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Chapter 5. Changes in prices and price indices from 2007 to 2009
In this chapter we look at the changes in price indices for the three year period from 2007 until
2009. The data for 2007 and 2008 are obtained from our two previous reports on cross-country
price comparisons of pharmaceuticals in Europe (see Brekke, Holmås and Straume 2008, 2009).
Having data over time (not just across countries) allows us to examine potential trends in prices
in Norway and the reference countries. It also allows us to examine how sensitive price indices
are to exchange rate fluctuations. First, we compare the price indices across years. Second, we
check whether the changes in the indices are due to exchange rate fluctuations by computing this
year’s price indices using last year’s exchange rates. Finally, we look at the nominal price
changes for each country using products that were present in all years.
5.1. Development in price indices 2007-2009
Figure 5.1 below plots the bilateral (AUP) price indices based on volume-weighted average
substance prices per dose for all substances in our sample. The figures from 2007 and 2008 are
obtained from Brekke, Holmås and Straume (2008, 2009). In the figure below, we rank the
countries from cheapest to most expensive in 2009.
Figure 5.1: Bilateral indices, average substance prices (AUP), all substances, 2007-2009.
The main picture is that the ranking of countries is very consistent and robust across years with
one minor exception. UK has gone from being slightly more expensive than Norway to being
slightly less expensive. However, if we look at the differences in the price indices across years,
we see that while most countries became slightly less expensive relative to Norway between 2007
and 2008, the opposite is true between 2008 and 2009. In this period, most countries seem to
become more expensive relative to Norway. While the change is marginal for UK and Sweden,
this is not the case for the rest of the countries. Especially, Ireland is now 213.5 per cent more
expensive than Norway in 2009, wheras they were “only” 140.4 per cent more expensive in 2008.
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What can explain the observed development in the price indices? Generally, there are four
sources of change in the price indices over time.
1. Fluctuations in exchange rates
2. Different trends in prices of pharmaceuticals
3. Changes in the sample of substances and products
4. Changes in the Norwegian consumption weights.
We will first take a look at the most obvious source of change in the price indices, namely the
exchange rates. The obvious way to analyse the impact of exchange rate fluctuations is to
calculate this year’s price indices by using last year’s exchange rates. Table 5.1 reports all the
bilateral price indices for 2009 based on average substance prices (cf. Table 4.2) when using
2008 exchange rates.10 Figure 5.2 below illustrates the rankings of the overall price indices using
all substances.
Figure 5.2: Bilateral indices, average substance prices (AUP), all substances, 2008, 2009 and
2009 with 2008 exchange rate.
We see that all countries, except for UK and Sweden, get a lower 2009 price index when using
2008 exchange rates. The reason for this is that the EURO has become more valuable relative
NOK during this period. The same argument applies to Danish kroner, while the British Pounds
and Swedish kroner have become slightly less valuable relative to NOK. However, exchange rate
fluctuations do not explain the whole change in the price indices. Even when controlling for
exchange rates, we see that all countries become more expensive relative to Norway during this
from 2008 to 2009, though the changes are much weaker.
10 The same exercise is done in Brekke, Holmås and Straume (2009) for the years 2007 and 2008. There we also see
that exchange rate fluctuations explain quite a lot of the variation in the price indices across years.
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Tabell 5.1. Bilateral price indices (AIP and AUP) for average substance prices in 2009 using exchange rates from 2008.
Norway Sweden Denmark Finland UK Germany Netherlands Belgium Austria Ireland
All substances
AIP per dose 100 116,1 125,1 108,0 126,3 128,0 112,3 191,1 124,4 201,7
AUP per dose 100 113,9 120,5 125,9 105,9 143,1 124,7 190,6 130,8 277,1
Number of substances 273 268 263 256 259 264 246 253 257
Substances on patent (without generic competition)
AIP per dose 100 120,0 128,1 106,5 111,1 127,5 118,1 155,6 110,7 119,7
AUP per dose 100 118,6 128,2 129,3 95,8 134,8 118,8 157,0 121,8 173,2
Number of substances 154 152 148 140 148 147 134 136 144
Substances off patent (with generic competition)
AIP per dose 100 108,9 119,3 110,7 149,9 128,9 101,1 257,4 149,7 354,0
AUP per dose 100 106,6 108,5 120,9 118,8 156,4 133,9 242,5 144,4 435,2
Number of substances 119 116 115 116 111 117 112 117 113
Substances under reference pricing (trinnpris)
AIP per dose 100 128,7 133,0 118,2 153,6 166,1 120,9 240,9 183,6 284,3
AUP per dose 100 116,1 119,8 127,3 122,1 165,4 148,0 216,4 176,6 352,0
Number of substances 44 45 45 44 43 44 44 45 45
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5.2. Nominal changes in pharmaceutical prices 2007-2009
A second source of changes in the price indices is national variations in how prices develop over
time. Do prices decline faster in Norway than in the reference countries? In this section we
compare the prices for the same product in 2007, 2008 and 2009 in each country’s own currency.
Obviously, if a new product enter (or an “old” product exit) the sample, this product will not be
included in the price change. Thus, we compare the price development for products that are
present in all periods. Price changes are measured only at pharmacy retail price (AUP) level, and
the change is measured as follows:
1
1
change Price
t
tt
AUP
AUPAUP , where t = 2009 and t-1 = 2007 or 2008.
Price changes are not adjusted for inflation, implying that we look at nominal price changes in
each country. The price changes are also measured separately for the patent and the generic
market segments, as well as the reference priced products (trinnpris). Table 5.2 below presents
the results for the period of 2008-2009.
Tabell 5.2: Nominal changes in average pharmacy prices (AUP) from 2008 to 2009 (own
currency), the number of substances in parenthesis.
All substances On-patent
substances Off-patent
substances Reference priced
substances
Norway -0,014 (232) -0,029 (123) 0,002 (109) 0,000 (45)
Sweden -0,001 (227) 0,006 (119) -0,007 (108) -0,037 (43)
Denmark -0,007 (221) 0,026 (117) -0,045 (104) -0,110 (45)
Finland -0,023 (222) -0,014 (117) -0,032 (105) -0,094 (45)
UK -0,002 (219) -0,001 (113) -0,003 (106) 0,002 (44)
Germany -0,021 (217) 0,004 (118) -0,049 (99) -0,058 (42)
Netherlands -0,049 (226) -0,015 (120) -0,086 (106) -0,206 (43)
Belgium -0,008 (211) 0,003 (110) -0,021 (101) -0,023 (43)
Austria -0,004 (214) 0,002 (107) -0,010 (107) -0,051 (45)
Ireland -0,149 (219) -0,137 (133) -0,161 (106) -0,198 (45)
If we look at all substance, then prices decline in every country. The largest change is in Ireland,
with a 14.9 per cent price reduction. This is likely due to reductions in the regulated margins that
pharmacies are allowed to calculate in Ireland. In Norway the prices declined with 1.4 per cent.
Most countries have an even weaker reduction in the prices. In the on-patent segment, the price
reduction is 2.9 per cent on average for Norway. Only Ireland has a larger reduction than
Norway. In fact, several countries face a marginal price increase on products in this segment.
For the off-patent market segment, we see that prices decline in all countries, except for Norway.
At first glance this seems counterintuitive since Norway is the most or second cheapest country
according to the price indices for this market segment. However, a potential explanation is that
the prices decline instantaneously, especially for the drugs under reference pricing (trinnpris), but
then stay fairly constant at the lower price level afterwards. This is consistent with the results in
Table 5.3 below.
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Using the 2007 data, we can compare the price changes over three years. Table 5.3 below
summarises the findings.
Tabell 5.3: Nominal change in average pharmacy prices (AUP) from 2007 to 2009 (own
currency), the number of substances in parenthesis.
All substances On patent
substances Off patent
substances Reference priced
substances
Norway -0,027 (232) -0,035 (123) -0,017 (109) -0,079 (45)
Sweden -0,001 (227) 0,006 (119) -0,013 (108) -0,046 (43)
Denmark -0,040 (221) -0,003 (117) -0,081 (104) -0,152 (45)
Finland -0,033 (222) -0,012 (117) -0,056 (105) -0,126 (45)
UK 0,011 (219) 0,017 (113) 0,000 (106) -0,057 (44)
Germany -0,000 (217) 0,047 (118) -0,057 (99) -0,098 (42)
Netherlands 0,156 (226) 0,289 (120) 0,004 (106) -0,103 (43)
Belgium -0,018 (211) -0,004 (110) -0,034 (101) -0,066 (43)
Austria 0,008 (214) 0,042 (107) -0,026 (107) -0,097 (45)
Ireland -0,150 (219) -0,144 (113) -0,157 (106) -0,214 (45)
If we compare with 2007, we see that Norway has experienced a greater price reduction than
from 2008. For all substances, we have had a 2.7 per cent reduction, where 3.5 per cent is due to
price reductions in the on-patent segment and 1.7 is due to price reductions in the generic market
segment. Especially, for the substances under reference pricing, the price reductions have been
larger. Combining the figures in Table 5.2 and 5.3 suggest that while price reductions seem to be
consistent in the on-patent segment, the trend is weaker in the generic market segment, even for
the reference priced products.
For the rest of the countries, we see again that Ireland has the largest price reductions over the
period, while in fact the Netherlands has the highest price increases. The rest of the countries
experience fairly stable price trends over this time span.
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6. Regression analyses
In this part of the report we analyse differences in pharmacy prices and margins using regression
analyses. An advantage of this kind of analysis compared with calculating indices is that it is
possible to study price differences between countries corrected for the fact that other aspects may
also vary. We have for example seen that pack size varies considerably. Correcting for pack size
in the regressions means (in somewhat simplified terms) that we compare prices between
countries for identical pack sizes. In the analyses we would also like to correct for the proportion
of each active substance sold as tablets. We have also tried to use the strength of the
pharmaceutical as an explanatory variable, but as this had no significant effect we have chosen to
omit this variable from the analyses. In analyses of this kind, we can also correct for the fact that
not all countries are represented with the same active substances in the data set. We do this by
including a dummy variable for each active substance11, which implies that we are comparing the
prices of the identical active substances. In these analyses, we will therefore expect the results
(the differences between the countries) to be less sensitive to which active substances we include
in the analyses.
6.1. Pharmacy prices (AUP)
In the regression analyses, we have chosen to focus on volume-weighted average prices (see
Chapter 4.1 for an explanation of how these have been calculated). In these analyses, we use
dummy variables to identify price differences between countries. In other words, we have, for
each country, constructed a variable with value 1 for all price observations for that country, while
the variable has the value 0 for price observations for all other countries. As we have 10
countries, we obtain 10 such dummy variables. To be able to identify the effect of these variables,
i.e. how much of the price differences they explain, we must omit a variable. We have chosen to
omit the variable for Norway, which means that we compare prices in the other countries with
prices in Norway. For example, we can see from the results in Table 6.1 below that the estimated
effect of the variable "Denmark" is 0.110, which means that prices in Denmark are 11 per cent
higher than in Norway (this interpretation is due to the fact that prices are in logarithmic form). A
negative value could accordingly be interpreted as how many per cent lower the average price
was, compared with the price level in Norway. However, it is important to note whether or not
the estimated effect of the variable is statistically significant. If we consider the coefficient for
"Sweden", this has a value equal to 0.051. As this is not statistically significant (coefficients that
are statistically significant are asterisked), we conclude that average prices in Sweden do not
differ from those in Norway.
In Table 6.1 we present the results from regression analyses where we use all active substances
(columns 2-4) and only global active substances (columns 5-7). We further distinguish the active
substances according to whether they are on or off patent. In the same way as when we compared
price levels using indices, we also find here that Norway proves to have low pharmaceutical
prices. As expected, the results are relatively similar if we analyse the entire sample of
11 We estimate fixed effect models.
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pharmaceuticals or only consider the sample of global pharmaceuticals. When discussing the
results, we therefore only focus on the total sample. We can also see from the table that the price
differences are not as great as when we compared the price indices in the previous chapter. Part
of the reason for this may be that, in this part of the analysis, we do not weight the prices with
Norwegian consumption weights.
If we focus on all substances for the entire sample (column 2), we find that Ireland has clearly the
highest prices, approximately 64 per cent higher than in Norway. Belgium and Germany also
have high prices (33 and 37 per cent higher respectively than in Norway), while Austria, Finland
and the Netherlands has a price level around 21-28 per cent higher than Norway. Denmark has a
price level 11 per cent higher than Norway, while the Swedish price level does not differ
significantly from the Norwegian price level. United Kingdom is the only country with a price
level lower than Norway (20 per cent).
Table 6.1 Differences in pharmacy prices (AUP), volume-weighted substance prices.
Total sample Global substances
All
substances Substances
without
generic
competition
Substances
with generic
competition
All
substances Substances
without
generic
competition
Substances
with generic
competition
Sweden 0.051
(0.039) 0.111***
(0.033) -0.028
(0.076) 0.071
(0.045) 0.138***
(0.037) -0.008
(0.083)
Denmark 0.110***
(0.039) 0.272***
(0.034) -0.098
(0.077) 0.086**
(0.044) 0.269***
(0.033) -0.115
(0.082)
Finland 0.243***
(0.039) 0.321***
(0.033) 0.141*
(0.076) 0.273***
(0.044) 0.361***
(0.037) 0.172**
(0.077)
Netherlands 0.276***
(0.034) 0.230***
(0.033) 0.337***
(0.076) 0.249***
(0.044) 0.251***
(0.037) 0.262***
(0.082)
Austria 0.210***
(0.040) 0.212***
(0.030) 0.204***
(0.077) 0.238***
(0.045) 0.253***
(0.036) 0.222***
(0.083)
United Kingdom -0.203***
(0.039) -0.204***
(0.034) -0.199***
(0.076) -0.217***
(0.044) -0.177***
(0.037) -0.255***
(0.082)
Belgium 0.329***
(0.040) 0.402***
(0.038) 0.251***
(0.090) 0.365***
(0.047) 0.455***
(0.040) 0.296***
(0.096)
Germany 0.365***
(0.039) 0.335***
(0.033) 0.403***
(0.077) 0.376***
(0.044) 0.374***
(0.036) 0.374***
(0.082)
Ireland 0.641***
(0.039) 0.532***
(0.033) 0.780***
(0.077) 0.615***
(0.044) 0.520***
(0.037) 0.726***
(0.082)
Pack size -0.0034***
(0.0004) -0.0026***
(0.0004) -0.0038***
(0.0005) -0.0037***
(0.0004) -0.0019***
(0.0005) -0.0048***
(0.0007)
Proportion tablets -0.157***
(0.046) -0.121***
(0.040) -0.167*
(0.098) -0.115**
(0.052) -0.114***
(0.040) -0.051
(0.107)
Constant 2.327***
(0.039) 2.984***
(0.033) 1.461***
(0.083) 2.102***
(0.046) 2.644***
(0.037) 1.435***
(0.094)
Dummy for molecule yes yes yes yes yes yes
Number of molecules 279 159 120 199 104 95
Number of
observations 2618 1462 1156 1990 1040 950
R2 0.252 0.375 0.246 0.259 0.418 0.251
***: significant at 1 percent level. **: significant at 5 percent level. *: significant at 10 percent level.
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In the same way as previously, we also distinguish active substances according to whether or not
they have generic competition in Norway. If we focus on the total sample of active substances for
which we do not observe generic competition (column 3 in the Table), we see that Norway has
lower pharmaceutical prices than all other countries with the exception of the United Kingdom.
Average pharmaceutical prices for active substances without generic competition are
approximately 20 per cent lower in the United Kingdom than in Norway. If we consider the other
countries, the ranking is as follows (with the relative price difference from Norway in brackets):
Ireland (53%), Belgium (40%), Germany (34%), Finland (32%), Denmark (27%), the
Netherlands (23%), Austria (11%) and Sweden (11%).
If we consider price differences for pharmaceuticals with generic competition, we still find that
most countries have higher pharmaceutical prices than Norway (see column 4). If we rank the
countries according to how expensive they are compared with Norway, we find the following:
Ireland (78%), Germany (40%), Netherlands (34%), Belgium (25%) and Finland (14%). For
Sweden and Denmark we do not find significantly different prices compared to Norway, while
the price level in United Kingdom is approximately 20 per cent lower than in Norway.
6.2. Pharmacy margins
In Table 6.2 below, we present the results from regression analyses in which we analyse how
pharmacy margins vary between countries. We carry out the same classification of active
substances as above (all active substances in the sample, active substances available in all
countries (global), active substances without generic competition in Norway and active
substances with generic competition in Norway) and use the same explanatory variables. The
dependent variable (pharmacy percentage margin) is given by
AUP
AIPAUP
M
,
where AUP and AIP are calculated as volume-weighted average prices. In the same way as
previously, we use dummy variables to identify differences between countries. We use Norway
as a comparison country; if we look at Table 6.2, column 2, we find for example that Finland has
a value equal to 0.121. This means that the (percentage) margin is on average 12.1 percentage
points higher in Finland than in Norway. If we start by looking at all active substances, we see, as
above, that the results vary little whether we use the total sample or only the global active
substances. Focusing on the former, we find that Ireland has clearly the highest percentage
margins, 25 percentage points higher than in Norway. The average margin in Norway is approx.
18 per cent (given by the constant in the model), i.e. the average margin in Ireland is approx. 43
per cent (18 + 25). Finland, the Netherlands and Germany also seem to have relatively high
percentage margins, with the same applying to a lesser extent to Austria and the United Kingdom.
Pharmacy margins in Sweden, Denmark and Belgium are not significantly different from those in
Norway.
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Table 6.2 Differences in pharmacy percentage margins.
Total sample Global substances
All
substances Substances
without
generic
competition
Substances
with generic
competition
All
substances Substances
without
generic
competition
Substances
with generic
competition
Sweden 0.004
(0.008) -0.008
(0.008) 0.022*
(0.013) -0.001
(0.010) -0.015*
(0.009) 0.020
(0.015)
Denmark -0.013
(0.008) -0.005
(0.007) -0.023*
(0.014) -0.014
(0.010) -0.008
(0.009) -0.018
(0.015)
Finland 0.121***
(0.008) 0.153***
(0.007) 0.082***
(0.014) 0.119***
(0.009) 0.153***
(0.008) 0.084***
(0.015)
Netherlands 0.114***
(0.008) 0.059***
(0.007) 0.184***
(0.014) 0.121***
(0.009) 0.055***
(0.008) 0.196***
(0.015)
Austria 0.027***
(0.008) 0.064***
(0.08) -0.018
(0.014) 0.027***
(0.010) 0.071***
(0.009) -0.026*
(0.015)
United Kingdom 0.017**
(0.008) -0.042***
(0.008) 0.087***
(0.014) 0.015
(0.010) -0.056***
(0.008) 0.091***
(0.015)
Belgium 0.006
(0.009) 0.021**
(0.009) -0.017
(0.017) 0.001
(0.011) 0.019**
(0.009) -0.026
(0.019)
Germany 0.087***
(0.008) 0.051***
(0.007) 0.137***
(0.014) 0.088***
(0.009) 0.049***
(0.008) 0.132***
(0.015)
Ireland 0.252***
(0.008) 0.288***
(0.008) 0.202***
(0.014) 0.246***
(0.009) 0.286***
(0.008) 0.200***
(0.015)
Pack size 0.0001
(0.0001) -0.0003***
(0.0001) 0.0001
(0.0001) -0.0001
(0.0001) -0.0001
(0.0001) -0.0002**
(0.0001)
Proportion tablets 0.0152
(0.0096) 0.0127
(0.0085) 0.0097
(0.0175) 0.0092
(0.0111) 0.0167*
(0.0092) -0.0037
(0.0172)
Constant 0.183***
(0.008) 0.139***
(0.007) 0.260***
(0.015) 0.199***
(0.010) 0.137***
(0.009) 0.283***
(0.017)
Dummy for molecule yes yes yes yes yes yes
Number of molecules 279 159 120 199 104 95
Number of
observations 2618 1462 1156 1990 1040 950
R2 0.442 0.698 0.408 0.440 0.735 0.423
***: significant at 1 percent level. **: significant at 5 percent level. *: significant at 10 percent level.
If we distinguish the active substances according to whether or not we observe generic
competition (column 3 and 4), the results change somewhat. We see that, compared to Norway,
pharmacy percentage margins in Germany and Netherlands are particularly high for substances
with generic competition, while Finish margins are highest for substances without generic
competition. Pharmacy percentage margins in United Kingdom are lower than in Norway for
substances without generic competition, while the opposite is the case for substances with generic
competition. Sweden and Denmark have the same percentage margins as Norway for substances
without generic competition, while Swedish margins are slightly higher and Danish margins are
slightly lower than Norwegian margins for substances with generic competition.
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7. Concluding remarks
In this study we have compared prices of prescription drugs in Norway and the following nine
Western European countries: Austria, Belgium, Denmark, Finland, Germany, Ireland, the
Netherlands, UK and Sweden. These countries comprise the basket for the Norwegian price cap
regulation and are considered to be fairly similar and comparable countries.
Data are obtained from IMS Health and contain detailed information of all prescription bound
sales within the top 300 substances on the Norwegian market for the first half of 2009. The data
have information of prices at wholesale (AIP) and retail (AUP) level per pack and per standard
dose. The data also contain information about sales volumes (packs and doses), patent status,
brand-name or generic, presentation form, strength, etc.
Based on these data, we compare prices of prescription drugs across countries using several
different approaches. We start out with the standard approach by calculating price indices for
identical packs (same pack size and strength), where we pick the most selling pack in Norway for
each substance and compare the price of this pack with the price of corresponding packs in each
of the reference countries. However, this approach involves several problems. First, we ignore
information on all other packs sold within a given substance in Norway and abroad. Second, the
top selling packs in Norway are not necessarily the top selling packs abroad and in many cases
these packs are not available in the reference countries. We therefore also calculate volume-
weighted average prices per dose for each substance. This approach uses all price information
and provides us with a representative price for each country. Based on these prices, we calculate
bilateral price indices (substances common to Norway and a given foreign country) and global
price indices (substances common to all countries). Finally, we have estimated price difference
across countries by using regression analysis. This approach allows us to test whether price
differences are statistically significant. It also allows us to control for differences in pack size and
the fraction of tablets sold within each substance. When using regression analysis we can also
correct for the fact that not all countries have the same set of substances in their market.
Table 7.1 below summarises the findings by presenting the ranking of countries for each of the
price comparisons that we perform, also for the different market segments. The main finding is
that UK, Norway and Sweden consistently have the lowest pharmacy prices (AUP) of
prescription drugs, whereas Ireland, Belgium and (most of the time) Germany have the highest
prices.
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Tabell 7.1 Summary of rankings according to price indices and regression analysis at pharmacy price (AUP) level.
All substances Patent market segment
Bilateral indices,
pack prices Bilateral indices,
substance prices Global indices,
substance prices Regression
analysis Bilateral indices,
pack prices Bilateral indices,
substance prices Global indices,
substance prices Regression
analysis
1 UK UK UK UK UK UK UK UK
2 Norway Norway Norway Norway Norway Norway Norway Norway
3 Sweden Sweden Sweden Sweden Sweden Sweden Sweden Sweden
4 Netherlands Denmark Denmark Denmark Netherlands Netherlands Netherlands Austria
5 Austria Netherlands Netherlands Austria Austria Austria Austria Netherlands
6 Denmark Finland Finland Finland Finland Denmark Denmark Denmark
7 Finland Austria Austria Netherlands Denmark Finland Finland Finland
8 Germany Germany Germany Belgium Germany Germany Germany Germany
9 Belgium Belgium Belgium Germany Ireland Belgium Belgium Belgium
10 Ireland Ireland Ireland Ireland Belgium Ireland Ireland Ireland
Generic market segment Reference priced (trinnpris) drugs
Bilateral indices,
pack prices Bilateral indices,
substance prices Global indices,
substance prices Regression
analysis Bilateral indices,
pack prices Bilateral indices,
substance prices Global indices,
substance prices Regression
analysis
1 UK Norway UK UK Norway Norway Norway -
2 Norway Sweden Norway Sweden Sweden UK UK -
3 Sweden UK Sweden Denmark UK Sweden Sweden -
4 Austria Denmark Denmark Norway Denmark Denmark Denmark -
5 Denmark Finland Netherlands Finland Finland Finland Finland -
6 Netherlands Netherlands Finland Austria Austria Netherlands Netherlands -
7 Finland Austria Austria Belgium Netherlands Germany Germany -
8 Germany Germany Germany Netherlands Germany Austria Austria -
9 Belgium Belgium Belgium Germany Belgium Belgium Belgium -
10 Ireland Ireland Ireland Ireland Ireland Ireland Ireland -
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We have also taken a closer look at the development in price indices from 2007 to 2009 by
including the data from our two previous studies (Brekke, Holmås and Straume, 2008, 2009).
First, we find that there are large changes in the price indices from 2008 to 2009. All countries
become more expensive than Norway. Using 2008 exchange rates to recalculate the 2009 price
indices, we find that a significant part of the changes are driven by exchange rate fluctuations.
However, even when correcting for exchange rate fluctuations, all countries become more
expensive than Norway, though the difference is much smaller. We therefore proceed by looking
at the nominal price changes in each country. Here we find that Norway has a fairly large
reduction in prices compared with most of the reference countries (except for the generic market
segment), which might explain some of the residual differences in the price indices over time.
However, we cannot rule out that also changes in consumption patterns and changes in the top
300 sample over the years might also contribute somewhat to the changes in the price indices.
Finally, we have looked at the pharmacy margins. Using regression analysis, we find that Ireland
has clearly the highest margins, 25 percentage points higher than in Norway. The average margin
in Norway is approximately 18 per cent, i.e. the average margin in Ireland is approx. 43 per cent
(18 + 25). Finland, the Netherlands and Germany also seem to have relatively high margins, with
the same applying to a lesser extent to Austria and the United Kingdom. Pharmacy margins in
Sweden, Denmark and Belgium are not significantly different from those in Norway. If we
decompose the pharmacy margins on the generic and the patent segments, we find that the
margins in United Kingdom are lower than in Norway for substances without generic
competition, while the opposite is the case for substances with generic competition. Sweden and
Denmark have the same margins as Norway for substances without generic competition, while
Swedish margins are slightly higher and Danish margins are slightly lower than Norwegian
margins for substances with generic competition.
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Appendix
Table A1. Bilateral indices (AIP and AUP) by sales volume, Norwegian weights.
50 top-selling active substances
Norway Sweden Denmark Finland UK Germany Netherland Belgium Austria Ireland
All substances
AIP 100 119.0 145.7 122.6 91.8 148.5 125.9 237.8 139.5 235.5
AUP 100 115.5 141.6 143.1 88.2 161.7 140.0 240.4 148.6 340.9
Number molecules 50 49 48 46 47 47 48 46 49
Active substances on patent
AIP 100 118.8 147.5 121.8 92.4 147.8 129.5 177.7 125.5 121.6
AUP 100 117.1 149.7 148.0 87.9 152.9 135.4 180.8 139.7 186.3
Number molecules 27 27 26 24 27 26 26 25 27
Active substances off patent
AIP 100 119.3 141.2 124.6 90.6 150.1 116.4 383.7 176.6 517.5
AUP 100 112.3 125.5 133.5 88.7 180.6 149.3 355.2 167.3 645.1
Number molecules 23 22 22 22 20 21 22 21 22
100 top-selling active substances
All substances
AIP 100 114.9 141.3 123.0 92.6 145.9 120.8 222.7 138.1 212.9
AUP 100 112.1 136.8 144.0 90.8 161,1 137.0 223.0 146.4 307.5
Number molecules 99 96 95 94 91 95 94 93 94
Active substances on patent
AIP 100 117.9 146.7 119.8 94.2 145.0 126.3 176.9 125.4 119.6
AUP 100 115.6 147.5 145.5 88.8 151.1 132.2 178.3 138.5 181.4
Number molecules 54 53 51 50 51 53 53 50 51
Active substances off patent
AIP 100 108.6 129.6 129.7 89.8 147.9 108.4 321.4 165.6 407.0
AUP 100 106.3 118.1 141.5 93.6 179.6 145.4 302.3 160.0 522.7
Number molecules 45 43 44 40 42 41 43
150 top-selling active substances
All substances
AIP 100 114.7 139.6 123.3 96.2 145.7 120.7 219.9 138.7 214.5
AUP 100 112.3 134.5 143.6 96.1 161,7 138.7 119.2 146.1 307.8
Number molecules 148 144 142 140 138 144 137 141 142
Active substances on patent
AIP 100 118.0 146.4 120.8 93.6 145.4 126.1 175.7 124.9 119.3
AUP 100 116.3 146.9 146.8 88.2 151.8 132.6 177.0 137.9 180.8
Number molecules 79 76 74 71 74 77 73 73 74
Active substances off patent
AIP 100 108.4 126.3 128.1 100.3 146.4 109.7 307.4 165.8 396.9
AUP 100 105.8 114.8 139.5 106.3 178.2 148.5 287.4 159.2 505.9
Number molecules 69 68 68 69 64 67 64 68 68
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