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Innovative methods for evaluating access to medicines in low and middle-income countries
How does the retail price of medicines compare in six Asia-Pacific low and middle-income countries and South Africa using a detailed medicine prices dataset?

What We Did

Our use of IMS data to construct a cross-country medicine price comparison of Asia-Pacific countries is innovative since this approach has previously been limited to high-income, OECD countries. We follow and adapted the approach of Danzon and colleagues in their analyses of OECD markets (Danzon and Chao 2000, Danzon and Furukawa 2004, Danzon and Furukawa 2006), and also emulated in a more recent study that covered some developing countries (Morel, McGuire, and Mossialos 2011).

We define the unit of comparison as pharmaceutical products with the same active ingredient and WHO ATC code at the 4th level. The unit price is defined as the price per kilogram/international unit of the molecule-ATC 4 combinations. By standardizing the units of analysis and prices we can make direct comparisons of prices of items in two or more countries. To combine this information to assess overall price differences, we constructed Laspeyres indexes to aggregate the comparisons.

The Laspeyres index allows us to estimate how much more or less it would cost a consumer to purchase a basket of medicines in another country if that basket was identical – same medicines and same quantities – to that purchased in their own country. Comparisons are done for both a bilaterally matching basket of medicines that are available in the comparison country and the base country, and a more limited basket of goods that are available in all seven countries.

Our Findings

We estimated comparative price indices using Sri Lanka (=100) as the base country, with the key results shown in Table 2. The indices computed using the common global basket of products are given in the top half of the table, whilst the lower half displays the indices based on bilateral baskets. For each set, we give the results using both market and PPP exchange rates.

Furthermore, in the most comparable study using IMS data from developing countries, Morel et al. (Morel, McGuire, and Mossialos 2011) argued that there is only a weak relationship between price levels and country income level. We compared the price levels in our list of countries with per capita GDP (Figure 2). The Laspeyres index gives a correlation of 0.83 (p=0.04) with income, which is substantially better than the correlation of only 0.18 reported by Morel et al. in their analysis, indicating that prices are positively correlated to per capita income levels.

Our analysis demonstrates that it is quite feasible to use IMS data to generate robust cross-country price comparisons in developing Asia-Pacific countries. Although IMS data is expensive to procure, it can be more cost effective to use this data than collecting price data using surveys, such as done by the WHO HAI Project and the World Bank ICP. While these surveys typically collect data on a selected basket of 40-50 drugs, IMS collects data for almost all drugs available in the market. This makes the results obtained from IMS data more representative than the other studies, and less subject to sampling bias.

Our innovative approach in using IMS data to compare price levels yield potentially more accurate results that can help countries like Sri Lanka that are concerned with using price control and regulation to improve medicines access.

Technical Notes

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