Comparing costing results in across country economic evaluations: the use of technology specific...

HEALTH ECONOMICS

Health Econ. 14: 93–99 (2005)

Published online 14 June 2004 in Wiley InterScience (www.interscience.wiley.com). DOI:10.1002/hec.913

HEALTH ECONOMICS LETTER

Comparing costing results in across country economicevaluations: the use of technology speci¢c purchasingpower parities

Sarah Wordswortha,* and Anne LudbrookbaHealth Economics Research Centre, University of Oxford, Oxford, UKbHealth Economics Research Unit, University of Aberdeen, Aberdeen, UK

Summary

The number of economic evaluations conducted on a multinational basis is increasing. Therefore, techniquesare required to compare the results of such studies in a meaningful manner. This paper explores differentapproaches to comparing across country cost data applied to a European study of dialysis therapy for end-stagerenal disease. A price and volume index is created at the level of the individual health care technology and comparedto an exchange rate conversion and published purchasing power parities (PPPs). Both exchange rate andPPP conversions when published rates are used fail to accurately reflect the true resource use of the appliedhealth care example. These differences can be related to specific issues of input mix and price variation. Alternatively,the use of technology specific PPPs provided a more robust approach for international comparisons andalso have the potential for use in multi-centre economic evaluations within the same country. Copyright # 2004John Wiley & Sons, Ltd.

Keywords comparable costing; exchange rates; purchasing power parities; technology specific conversions; dialysistherapy

Introduction

Economic evaluations are increasingly conductedon a multinational basis, particularly alongsidelarge multicentre trials [1,2]. Studies from differentcountries are also brought together in systematicreviews [3]. The costing components of suchstudies have faced challenges regarding the collec-tion and analysis of data and advances have beenmade towards handling missing unit cost data andimproving the transferability of analysed databetween settings [4,5]. However, less emphasishas been directed towards making the cost basecomparable across the participating centres from

several countries within a study. In some cases,within country comparisons are sufficient foranalytical purposes and conversions to a commoncurrency are only for presentation. However,where a summary measure reflecting resourceinput is important, then a conversion factor isrequired to express cost in a common base.

Two main approaches have been used forconverting cost data across countries, namelyexchange rates and purchasing power parities(PPPs), both of which have had concerns raisedregarding their appropriateness in converting costdata [6–10]. Despite being described as poorconversion methods, exchange rates and PPPscontinue to be used as first line approaches,

Copyright # 2004 John Wiley & Sons, Ltd.Received 28 October 2002Accepted 25 March 2004

*Correspondence to: Health Economics Research Centre, University of Oxford, Old Road Campus, Oxford OX3 7LF, UK.E-mail: [email protected]

possibly due to the lack of alternatives [11]. The aimof this paper is to demonstrate empirically thedevelopment and application of a price and volumeindex at the level of a specific health care technology,end-stage renal disease (ESRD), using the sameprinciples as the more aggregate level publishedPPPs. An exchange rate conversion and publishedGDP and medical care PPPs are also applied tothe data. The results of these different approachesare presented and a discussion of the findings andsuggestions for future research are provided.

Methods

Data

The data were taken from the European Dialysisand Cost-Effectiveness Study (EURODICE), com-paring two dialysis modalities, hospital haemodia-lysis (HD) and continuous ambulatory peritonealdialysis (CAPD). These technologies involve dif-ferent mixes of resource input, particularly withrespect to staffing and consumables. The studyinvolved ten renal centres based in Scotland(Aberdeen and Dundee), France (Nantes), theNetherlands (Nijmegen), Hungary (Debrecen),Russia (St. Petersburg), Estonia (Tallinn), Greece(Thessaloniki and Veria) and Albania (Tirana). Sixcentres provide both HD and CAPD and four HDalone.

The costing data were collected using a con-sistent method throughout the ten centres. Acombination of detailed questionnaires on re-source use and site visits by health economistsand clinicians from the co-ordinating centrecollected information on the volume of resourceuse and prices for all items used for dialysis. Datapresented here are for the year 1999 and includestaff, capital, consumables and overheads produ-cing an annual dialysis cost per patient. Albaniawas not included in this analysis, due to difficultyinterpreting certain data.

Application of exchange rate and published

PPPs

The exchange rate comparison was performed byconverting costs from the currency of each centreinto Sterling. For the application of GDP PPPsand medical care PPPs to the dialysis costs,

published ‘off the shelf’ PPPs were used, withresults expressed in relation to one centre in theUnited Kingdom (UK), Aberdeen [7].

Creating technology specific PPPs

Producing technology specific PPPs for dialysiswas undertaken in four stages. Firstly, the majorcost drivers common to all centres for HD andCAPD were identified and placed into a ‘basket’ ina stepwise process, starting with the item with thelargest cost in the base centre (Aberdeen). For thepurpose of this example, costs were entered at afairly aggregate level to simplify the presentation(see Tables 4 and 5).

For HD, the cost of nursing staff, erythropoietin(a drug used to reduce the anaemia suffered bythose on dialysis), dialysers (artificial kidneys) andcapital (mainly dialysis machine costs) werechosen. For CAPD, bags of peritoneal fluid,nursing staff and erythropoietin were selected. Toassess whether the resource inputs were homo-genous, detailed descriptive information was col-lected. Additional items (medical staff and lines)were added to the HD basket to demonstrate theeffect on the index value and its convergenceproperties.

Secondly, price relatives were produced bytaking the price of an item (such as nurses)from the basket of HD goods in one centre,for example Nantes (France), and dividingit through by the cost of the same item inAberdeen. This process was repeated for theremaining basket items, creating price relativesfor the six items between these two centresfor HD (Equation (1)). The third stage involvedcreating expenditure weights for these items ineach of the two centres. This establishedthe proportion of the combined total cost of theentire basket that each item accounted for(Equation (2)).

The final stage combined the price relatives withthe expenditure weights from each of the twocentres. The overall Nantes–Aberdeen PPP is thegeometric mean of the two resulting values(Equation (3)). The entire process was repeatedfor all remaining centres for both HD and CAPD.Stages 2–4 follow the method for aggregation ofbasic heading PPPs [7, pp. 24–25] and result in aFischer type PPP by combining results based onthe expenditure weights of both countries (seeappendix for an example).

Copyright # 2004 John Wiley & Sons, Ltd. Health Econ. 14: 93–99 (2005)

S.Wordsworth and A. Ludbrook94

Dialysis PPPs were calculated as each item wasadded to the basket in order to demonstrate thevariation in the PPPs at each stage and the

convergence to a final value as the total proportionof cost included in the basket increased. Thiswould help identify the proportion of total costnecessary to include for robust results.

Results

Comparison of conversion rates

Table 1 compares the technology specific PPPscalculated for HD and CAPD with the otheravailable methods of currency conversion. For allthe PPP calculations, a higher figure than theexchange rate will produce a lower treatment costthan simple exchange rate conversion and viceversa.

Comparisons of technology specific rates withexchange rates. The western European centresNantes, Nijmegen and Thessaloniki all have ratesabove the exchange rate (Table 1, Column 5). Thisreflects higher prices relative to Aberdeen in theprovision of dialysis, which are not fully reflectedin the exchange rate. The eastern Europeancentres, Debrecen, Tallinn and St. Petersburg allhave rates below the exchange rate reflecting lowerprices, particularly for labour inputs.

Comparisons of technology specific rates withpublished PPPs. For the western Europeancountries, the technology specific PPPs are alsohigher than both published PPPs. This impliesthat the higher prices in dialysis provision

Table 1. Conversion rates

Centre Sterlingexchange

rate

GDPPPP

(GBP)a

Medical carePPP (GBP)a

Dialysis PPPfor HD (GBP)

Dialysis PPPfor CAPD (GBP)

Dundee 1.00 1.00 1.00 0.95 0.71Nantes 10.07 9.72 10.60 15.72 N/aNijmegen 3.38 3.12 3.16 3.81 3.65Thessaloniki 497.66 356.61 288.37 727.28 733.07Debrecen 382.81 154.09 64.88 210.17 N/aTallinn 24.02 9.22 N/a 18.54 22.14St. Petersburg 38.05 6.24b 2.56b 28.80 N/a

Dundee (UK), Nantes (France), Nijmegen (the Netherlands), Thessaloniki (Greece), Debrecen (Hungary), Tallinn (Estonia), St.

Petersburg (Russia). Aberdeen is the base case for the calculations and Veria is not shown, as its results are similar to Thessaloniki.aSource OECD (1999).bWorld Bank (1999).

Box } method for calculation of PPPs

Price relativesThe price ratio or price relative (PR) is definedfor each input i ði ¼ 12nÞ and for each pair ofcentres, j and k, (where P is the unit cost of abasket item) as follows:

PRijk ¼ Pij=Pik ð1Þ

Expenditure weightsExpenditure weights, wij, are defined for eachinput ðiÞ and each centre ðj; kÞ as follows(where E is the annual expenditure per patientfor each basket item):

wij ¼ Eij=Xni¼1

Eij ð2Þ

wik ¼ Eik=Xni¼1

Eik

Dialysis PPPsThe PPP for centres j and k is given by thegeometric mean of the weighted price relativesusing each centre’s weights:

ffip Xni¼1

PRijk wij

! Xni¼1

PRijk wik

!ð3Þ

The Use of Technology Speci¢c Purchasing Power Parities 95


compared with Aberdeen are not fully reflected inthe published indexes. This is perhaps unsurprisingfor the GDP index, which would not necessarilyreflect institutional differences in medical care coststructures, but the medical care index also does notaddress the cost differences observed in a specifictreatment area. For the Greek centres, the medicalcare PPP is low (far below the exchange rate),reflecting the relative low labour costs in agenerally labour intensive sector. However, thetechnology specific PPP is high and driven byrelatively high prices for consumables, whichdominate this particular technology.

In the eastern European centres, the technologyspecific PPPs are also higher than the GDP ormedical care PPPs. Many consumable and equip-ment items for dialysis are purchased in interna-tional markets, at international prices, and theseprice effects offset, to some extent, the low labourcosts. GDP and medical care PPPs cannot takethis fully into account.

Comparisons of technology specific rates betweenthe treatments. The technology specific PPPs candiffer significantly for HD and CAPD and producea centre effect in the UK, with Dundee experien-cing lower prices than Aberdeen for CAPDconsumables. In Tallinn, the difference resultsfrom the lower proportion of low cost staff timeand higher proportion of high cost consumablesfor CAPD.

Effect on annual treatment cost comparisons

Tables 2 and 3 present the average annual costper patient for HD and CAPD based on the threePPP methods, compared with an exchange rateconversion (Sterling). With regard to HD costresults, differences are observed both betweencentres in the same country and between countries.In particular, Nantes and Nijmegen appear tohave higher costs than Aberdeen, based on

Table 2. Haemodialysis average annual converted costs per patient

PPPs Exchange rate

Centre Dialysis GDPa Medical carea Sterling

Aberdeen 16 096 16 096 16 096 16 096Dundee 15 856 15 063 15 063 15 063Nantes 14 043 22 712 20 827 21 923Nijmegen 18 588 22 699 22 412 20 953Thessaloniki 8684 17 711 21 902 12 691Debrecen 12 054 16 441 39 048 6618Tallinn 11 005 22 130 N/a 8495St. Petersburg 7474 34 494 84 078b 5657

Veria is not shown, as its results are similar to Thessaloniki.aSource OECD (1999).bWorld Bank (1999).

Table 3. Continuous ambulatory peritoneal dialysis average annual converted costs per patient

PPPs Exchange rate

Centre Dialysis GDPa Medical carea Sterling

Aberdeena 14 218 14 218 14 218 14 218Dundee 16 218 11 515 11 515 11 515Nijmegen 13 914 16 278 16 072 15 025Thessaloniki 11 932 24 527 30 332 17 576Tallinn 14 065 33 198 N/a 12 964

Veria is not shown, as its results are similar to Thessaloniki.aSource OECD (1999).



exchange rates or published PPPs, but thetechnology specific index brings them closer. Theseresults are important in interpreting any outcomedifferences between centres. For CAPD Dundeehas the lowest cost in exchange rate terms andThessaloniki the highest, but these positions arereversed when considering the dialysis PPP.

Table 4 illustrates the technology specific PPPresults for HD. Table 5 provides the results forCAPD, again with Aberdeen as the base case forthe calculations. The PPP columns provide anindex value for converting expenditure based onan increasing number of resource inputs. Thetables illustrate the variability in the calculatedPPP as the number of items added to the basket ofinputs is increased and demonstrates the conver-gence occurring as the percentage of total resourceincreases. Most notable in Table 4 is the effect ofrelatively low nursing costs in St. Petersburg,Debrecen and Thessaloniki. In all cases, the PPPstarts at a low rate and is pulled upwards, byadding relatively higher priced consumables. Thereis more variation in the PPPs for HD and moreitems were required to establish convergence in allcentres.

Discussion

The difficulty of interpreting cost-effectivenessresults from international studies, using exchangerates or published PPPs, has been highlightedrecently in the context of hormone replacementtherapy [12]. The authors suggest that UK pricesshould be applied to resource volumes taken fromnon-UK studies. Whilst this may be a necessaryapproach where UK resource volumes are notavailable, it does not allow for differences in thevolume of inputs and the effect that this could haveon outcomes.

In this paper, the use of technology specific PPPscreated results which adjusted for price differencesacross countries and centres on an item by itembasis and reflected resource use more accuratelythan exchange rates or published PPPs. In effect,the technology specific PPP is a price and volumeindex for the resource inputs into dialysis therapy.As such, it avoids some problems associated withexchange rates and differences in basket composi-tion that affect other conversion methods.

Technology specific PPPs provide a more robustapproach for international comparisons and haveT

able

4.Haem

odialysisPPPsandconvergentlevels

Centres

Nantes

Nijmegen

Tallinn

Thessaloniki

Debrecen

St.Petersburg

Dundee

Basket

item

sCumulative

%PPP

Cumulative

%PPP

Cumulative

%PPP

Cumulative

%PPP

Cumulative

%PPP

Cumulative

%PPP

Cumulative

%PPP

1.Nursingstaff

0.41

16.08

0.36

3.51

0.06

3.07

0.13

281.38

0.11

46.75

0.005

0.04

0.39

0.94

2.Erythropoietin

0.52

14.11

0.48

3.35

0.31

11.06

0.35

389.31

0.36

132.89

0.14

16.81

0.49

0.94

3.Dialysers

0.69

17.21

0.58

3.76

0.49

15.10

0.72

851.7

0.60

218.24

0.51

30.12

0.55

0.95

4.Capital

0.73

16.68

0.64

3.86

0.70

19.61

0.76

780.25

0.63

209.35

0.62

29.40

0.62

0.95

5.Medicalstaff

0.8

16.1

0.73

3.81

0.72

18.63

0.8

736.03

0.65

198.82

0.62

28.07

0.64

0.95

6.Lines

0.83

15.72

0.77

3.81

0.76

18.54

0.83

727.28

0.75

210.17

0.74

28.80

0.68

0.95

Aberdeenisthebase

case

forthecalculationsandVeria

isnotshown,asitsresultsare

similarto

Thessaloniki.



potential for application in within country com-parisons. The results presented here comparedcosts between two Scottish centres (Aberdeen andDundee) and show the effect of systematic pricedifferences. The annual cost per patient year forCAPD was lower in Dundee, in terms of actualexpenditure, but when price effects were elimi-nated, the resource cost was higher (Table 3). Thiscould be useful in interpreting data from multi-centre economic evaluations within one countryand builds on the best practice approach ofreporting both cost and volume of resource use.

Several issues require consideration when creat-ing technology specific PPPs. Firstly, it will beimportant to examine the amount of informationrequired to produce these PPPs. The relative pricesfor different inputs varied considerably in thisexample, and the results in Tables 4 and 5demonstrate the importance of ensuring that theindex covers the majority of resources. Furtherwork is required to consider whether the resultswould be affected by entering data at a moredisaggregated level. In other studies the workinvolved could vary greatly depending on theavailability and level of detail of cost information.The dialysis example produced very detailed costdata, which other technologies might not. How-ever, detailed cost and volume information is oftenavailable from economic evaluations in largemulti-centre trials, particularly when centre spe-cific units costs are produced.

A more fundamental issue concerns the inputcosts and quality relationship. The straightforwardcreation of the index assumes that units ofresources are the same. For certain inputs, suchas dialysers, some price differences relate to the useof a different type of dialyser, which could havequality implications and in turn, could affectoutcomes. Similar challenges are likely to arise incomparing staff inputs, although in this study,detailed comparisons of staff grades and qualifica-

tions were carried out and price relatives werecalculated for specific grades of staff. Where thereis evidence that the quality of input is related toeffectiveness, different quality inputs may need tobe treated as separate inputs.

In conclusion, considerable time and effort isdevoted to collecting and analysing cost data,however, less emphasis is given to making theresults comparable across countries. Conversionfactors can affect the interpretation of results fromeconomic evaluations, particularly where inputmix and relative prices vary substantially. Thesignificance of this issue will be greatest wherethere are large differences in the levels of thenational economies, such as between eastern andwestern Europe, in this example, or in interpretingresults for less developed countries. Makingconversions using a technology specific PPPrepresents a theoretically robust solution to thecomparability issue. It remains important to per-form sensitivity analysis using alternative ap-proaches and to explore the influence of alteringthe composition of the inputs for the baskets.

The approach used to compare costing resultswill become particularly important when effective-ness data are incorporated, as the choice ofmethod could affect conclusions drawn for policy-making. Future research should explore furtherthe methods of construction and the application oftechnology specific PPPs, rather than the use ofexchange rate conversions or published PPP ratesas first choice methods for comparing the resultsfrom across country costing studies.

Acknowledgements

Funding from the BIOMED 2 programme of theEuropean Commission is acknowledged. The HealthEconomics Research Unit (HERU) is funded by the

Table 5. Continuous ambulatory peritoneal dialysis PPPs and convergent levels

Centres

Basket items Nijmegen Tallinn Thessaloniki Dundee

Cumulative % PPP Cumulative % PPP Cumulative % PPP Cumulative % PPP

1. Fluid bags 0.63 3.76 0.67 24.59 0.77 799.48 0.46 0.632. Nursing staff 0.73 3.72 0.68 22.93 0.79 754.91 0.57 0.683. Erythropoietin 0.84 3.65 0.71 22.14 0.88 733.07 0.65 0.71

Aberdeen is the base case for the calculations and Veria is not shown, as its results are similar to Thessaloniki.



Chief Scientist Office of the Scottish Executive HealthDepartment (SEHD). The views expressed in this paperare those of the authors and are not attributable toeither funding body. Thanks go to the other members of

the EURODICE project for help with data collectionand to John Cairns, Anthony Scott and anonymousreferees for helpful comments on earlier drafts.

Appendix A

Creating technology specific PPPS: Example withthree basket items (Table A1)

References1. Koopmanscap MR, Touw KCR, Rutten FFH.

Analysis of costs and cost-effectiveness in multi-national trials. Health Policy 2001; 58: 175–186.

2. Willke RJ, Glick HA, Polsky D, Schulman K.Estimating country-specific cost-effectiveness frommultinational clinical trials. Health Econ 1998; 7:481–493.

3. Jefferson T, Demicheli V, Vale L. Quality ofsystematic reviews of economic evaluations in healthcare. J Am Med Assoc 2002; 287(21): 2809–2812.

4. Schulman K, Burke J, Drummond M, Davies L,Carlsson P, Gruger J, Harris A, Lucioni C, GisbertR,Llana T, Tom E, Bloom B, Willke R, Glick H.Resource costing for multinational neurologic clin-ical trials: methods and results. Health Econ 1998; 7:629–638.

5. Drummond MF, Bloom BS, Carrin G, et al. Issuesin the cross-national assessment of health technology.Int J Technol Assess Health Care 1992; 8(4): 671–682.

6. Kanavos P, Mossialos E. International comparisonsof health care expenditures: what we know and whatwe do not know. J Health Services Res Policy 1999;4(2): 122–125.

7. Purchasing power parities and real expenditures:1996. Organisation for Economic Co-operation andDevelopment (OECD), Benchmark 1999 Edition.

8. Parkin D, McGuire A, Yule B. Aggregate healthcare expenditures and national income: ishealth care a luxury good? J Health Econ 1987; 6:109–127.

9. Gerdtham UG, Jonsson B. Conversion factorinstability in international comparisons of healthcare expenditure. J Health Econ 1991; 10: 227–234.

10. Jefferson T, Mugford M, Gray A, Demicheli V. Anexercise on the feasibility of carrying out secondaryeconomic analyses. Health Econ 1996; 5: 155–165.

11. Goeree R, Gafni A, Hannah M, Myhr T, Black-house G. Hospital selection for unit cost estimates inmulticentre economic evaluations. Does the choiceof hospitals make a difference? Pharmacoeconomics1999; 15(6): 561–572.

12. Gosden TB, Torgerson DJ. Converting interna-tional cost effectiveness data to UK prices. Br MedJ 2002; 325: 275–276.

13. Khan IH, Campbell MK, Cantarovich D, et al.Survival on renal replacement therapy in Europe: isthere a centre effect? Nephrol Dialysis Transplant1996; 11: 300–307.

Table A1. Creating technology specific PPPs: Example with three basket items

Costdrivers

Weightsa Prices Pricerelativesa

Expenditureweightsa

PPPsa

Nantes AberdeenBasket 1 Nurse 289380 18000 16.08 16.08

Nantes Aberdeen Nantes Aberdeen Nantes Aberdeen

Basket 2 Nurse 0.79 0.69 289380 18000 16.08 12.70 11.09EPO 0.21 0.31 7800 913.12 8.54 1.79 2.65

14.49 13.74 14.11Nantes Aberdeen Nantes Aberdeen Nantes Aberdeen

Basket 3 Nurse 0.60 0.61 289380 18000 16.08 9.65 9.81EPO 0.15 0.27 7800 913.12 8.54 1.28 2.31Dialysers 0.25 0.12 37552 1209 31.06 7.77 3.73

18.69 15.84 17.21

aDenote the key stages in developing technology specific PPPs, see methods section.



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