Converting international cost effectiveness data to UK pricesBMJ 2002; 325 doi: https://doi.org/10.1136/bmj.325.7358.275 (Published 03 August 2002) Cite this as: BMJ 2002;325:275
- aNational Primary Care Research and Development Centre, University of Manchester, Manchester M13 9PL
- bNational Primary Care Research and Development Centre, Centre for Health Economics, University of York, York YO1 5DD
- Correspondence to: T B Gosden.
To facilitate decision making the Department of Health commissioned a systematic review of all published economic evaluations (not just UK studies) with a view to constructing an economic evaluation database.1 This systematic approach has been influenced by the Cochrane style systematic review process of clinical evaluations and is a progression from the widely publicised “QALY league table” approach. A QALY (quality adjusted life year) league table ranks interventions according to the extra cost per extra quality adjusted life year gained. Ideally this approach should help direct health care resources to those interventions which produce the most QALYs for the least cost. However, economic data are often specific to time and place, and extrapolation of economic results between localities and especially between countries should be treated with extreme caution. We aim here to show that the uncertainty over only one aspect of translating and interpreting non-UK evaluations—currency conversion factors—makes the use of foreign evaluations in UK health care decision making unreliable.
At present it is uncertain which is the best method of converting international cost data into UK prices. Exchange rates are unsatisfactory because they can vary considerably within the space of a few months. To avoid this, and other methodological problems of exchange rates, purchasing power parities (PPPs) are used to convert the costs of goods and services which are priced in different currencies to UK costs. PPPs relate to the prices of the same basket of goods in different countries and can eliminate some of the drawbacks of using exchange rates. However, it is unclear which type of PPP, health service specific or related to gross domestic product (GDP), is the more appropriate conversion method. If £1.50 bought the same goods and services in the UK as $1 does in the United States this would result in a GDP PPP of 1.5. Health PPPs are calculated using only the prices of a basket of health related goods and services whereas GDP PPPs are based on the prices of a basket of all goods in the economy. Previous attempts to establish the stability of either health PPP or GDP PPP conversion factors have reached different conclusions. 2 3 The Department of Health register of cost effectiveness studies1 recommends the use of GDP PPPs, though others argue that the choice makes no difference.4
In the table we show the results of converting a number of economic evaluations5–12 of hormone replacement therapy identified in a recent systematic review.15 Though each study contained several different scenarios of use of hormone replacement therapy and different types of patients, we show just two scenarios: 10 years of use for symptomatic women and 10 years of use for asymptomatic women (all studies used similar measures of health gain). As the table shows, different conversion methods give very different cost utility ratios, with a considerable range in results. A UK study5 is included for comparison. The difficulty with respect to UK decision making is: which is the right answer? There is, as yet, no consensus among health economists on this question.
This uncertainty is compounded by the differences between countries in the amount, productivity, and price of resources used to provide health care. For example, countries may use different numbers and types of staff, with widely varying pay scales and costs, to deliver the same quality of life improvements in women receiving hormone replacement therapy. A better method of using non-UK evaluations may be to derive UK costs based on reported physical units of resources used rather than convert costs using currently available techniques. However, this will tend only to reduce uncertainty due to problems with conversion factors, not remove it altogether.