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Original Article

Economic impact of extended time on peritoneal dialysis as a result of

using polyglucose: the application of a Markov chain model to forecast

changes in the development of the ESRD programme over time

Tom J. G. Weijnen

1

, Henk W. van Hamersvelt

2

, Paul M. Just

3

, Dick G. Struijk

4

, Yuvan I. Tjandra

5

,

Piet M. ter Wee

6

and Frank Th. de Charro

1

1

Centre for Health Policy and Law, Erasmus University Rotterdam, Rotterdam, The Netherlands,

2

Department of

Nephrology, University Hospital St Radboud, Nijmegen, The Netherlands,

3

Renal Division, Baxter Healthcare Inc.,

Deerﬁeld, IL, USA,

4

Renal Unit, AMC, University of Amsterdam, Amsterdam, The Netherlands,

5

Department of

Nephrology, Red Cross Hospital, The Hague, The Netherlands and

6

Department of Nephrology, Vrije Universiteit

Medical Center, Amsterdam, The Netherlands

Abstract

Background. The use of polyglucose as a peritoneal

dialysis (PD) ﬂuid extends time on PD treatment. It

is anticipated, therefore, that the share of patients

treated with PD will be positively inﬂuenced. The rela-

tionship between extension of PD treatment time and

an increase of the PD treatment share, however, is

complex and needs further investigation. In this paper,

a Markov chain model was applied to investigate the

impact of extended time on PD treatment for the PD

share in all dialysis patients in The Netherlands.

Furthermore, the economic impac t of the extended

time on treatment (ETOT) was explored.

Methods. Scenarios were forecast over a 10 year

period using aggregate data from the End-Stage

Renal Registry in The Netherlands (Renine). Three

scenarios were simulated in which the median PD

technique survival was extended by 8, 10 and 12

months. Two other scenarios explored the impact of

the combined effect of ETOT of 10 months together

with a 10% and 20% increase of PD inﬂow shares.

Reductions of costs to society due to ETOT were

estimated using Dutch cost data on renal replacement

therapies.

Results. PD share increa ses from 30.0% in the null

scenario to 34.5% in the scenario with an ETOT of

10 months and an increased PD inﬂow share of 20%.

The reduction in total costs to society of the renal

replacement therapies is 0.96%. The average societal

costs per discounted patient year for haemodialysis

(HD) are J84 100. For PD, these costs are J60 300.

A shift from HD to PD results in average cost savings

of 28% per patient year.

Conclusions. In view of high dialysis costs to society,

a reduction of 0.96% can be considered to be relevant

for healthcare policy makers.

Keywords: economic evaluation ; extended time on

treatment; Markov chain modelling; peritoneal

dialysis; polyglucose

Introduction

Although glucose is the principal osmotic agent used

in peritoneal dialysis (PD), it is sometimes associated

with a relatively short duration of effective ultraﬁltra-

tion. Research has sho wn that the use of polyglucose

as a PD ﬂuid extends time on PD treatment [1]. It can

therefore be expected that the PD share in dialysis

patients will be positively inﬂuenced. This implies that

the annual costs of an end-stage renal disease (ESRD)

programme will decrease, because costs to society of

PD are lower than costs of haemodialysis (HD) [2].

In this paper a Markov chain model was applied,

to investigate the impact of extended time on PD

treatment (ETOT) in The Netherlands. Anonymous

and aggregated data from the Dutch Renal Disease

Registry (Renine) was used to forecast patient numbers

over a 10 year period in six different scenarios. A null

scenario describes a situation where there is no impact

resulting from ETOT. To model the effects of ETOT,

three scenarios were deﬁned where the transition rates

in the Markov chain model were adapted. In addition,

two scenarios described the effects of ETOT together

with increased PD inﬂow shares. The effect measures

Correspondence and offprint requests to: T. J. G. Weijnen, MSc,

PO Box 1738, NL-3000 DR Rotterdam, The Netherlands. Email:

weijnen@frg.eur.nl

Nephrol Dial Transplant (2003) 18: 390–396

#

2003 European Renal Association–European Dialysis and Transplant Association

by guest on June 13, 2013http://ndt.oxfordjournals.org/Downloaded from

were: the PD share in total ESRD patients at the end

of the 10 year model period; the discounted patient

years shifted from HD to PD over the model period;

and the impact of this shift in patient years on the costs

of the ESRD programme.

Subjects and methods

In general, patients in an ESRD programme are vulnerable

to competing risks. A patient has a certain probability of

staying on the same treatment, being transferred to other

treatments, recovering hisuher renal functioning or dying. If

technique survival on PD is extended through the use of

polyglucose in all patients, ETOT could be directly trans-

lated into a higher PD share. However, polyglucose is only

effective in reducing technique failure in patients suffering

from ultraﬁltration failure. Other patients leave PD treat-

ment for different reasons, such as peritonitis. Moreover,

patients can receive a kidney transplant or die during the

additional time they could have stayed on PD treatment as

a result of using polyglucose. Consequently, the beneﬁts of

ETOT are not transparent.

The total effect of the use of polyglucose in ultraﬁltration

patients can be divided into direct and indirect effects. The

direct effect results from the increase in PD treatment time.

The indirect effect results from the increase in the number of

patients starting on PD instead of HD. It is expected that

more patients will start on PD because the chances of staying

for a longer period on stable PD treatment are higher.

Markov chain model

A Markov chain model simulates the dynamics in a patient

population, distributed over a number of treatment and age

groups. Continuous time is divided into a sequence of

discrete periods. The model estimates the number of patients

in the different treatment and age groups at the end of each

period. In this application of the Markov chain model, a

period equals 1 month. Consequently, a scenario covering

10 years consists of 120 periods. In the ﬁrst month of the

model period, the calculations begin with a known distribu-

tion of patients over treatment and age groups. The number

of patients per treatment and age groups at the end of the

month are derived from: (a) the number of patients entering

the ESRD treatment—this is the inﬂow; (b) the distribu-

tion of inﬂow over the treatment and age groups; (c) the

application of the transition rates that indicate the number

of patients moving to another treatment or age group

within the period; and (d) the transition rates of patients

ending the treatment—this is the outﬂow from the model.

The transition rates and the relative distribution of the

new patients over the groups are exogenously determined.

The transition rates were calculated from the actual transi-

tions that occurred in The Netherlands in the period 1997–

1999. The relative distribution of the new patients over the

groups equals the average relative distribution over the years

1997–1999.

Figure 1 shows a simpliﬁed representation of the Markov

chain for three treatment groups and two calculation periods.

The number of patients in each group at the end of the

month is used as a starting point for the calculations in

the next period. Again, the patients entering the different

treatment and age groups are added to the patient numbers

at the start and the transition rates are applied.

Since transitions differ over age, four age groups were

distinguished in the model: 0–44, 45–64, 65–74 and 75q

years. Patients can move from a younger age group to an

older group. Five modes of treatment were distinguished:

full care-centre haemodialysis (FCCHD); limited care-centre

haemodialysis (LCCHD); home haemodialysis (HHD); PD;

and living with a functioning donor kidney (KTX).

Within treatment groups, two sub-treatments were dis-

tinguished for transitions occurring in the ﬁrst year of treat-

ment and transitions occurring in later years. The reason for

this is that in some treatments, transitions in the ﬁrst year

are higher than in later years. The model has a total of

40 different groups (4 age groups

3 5 modes of treatment3 2

sub-treatments) to describe developments in the patient

population. In addition to the 40 treatment groups, the

model has two ‘absorbing states’. These states are related to

death and to recovery of patients’ own kidney function. Both

death and recovery constitute the ‘outﬂow’ from the model.

Data

Anonymous and aggregated data were provided by the End-

Stage Renal Registry in The Netherlands (Renine). Renine

Fig. 1. The Markov chain.

391Economic impact of using polyglucose

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has data available for transitions between modes of treat-

ment, incidence in the ESRD programme and mortality [3].

These data were used to calculate the transition rates and the

distribution of the new patients over the treatment and age

groups

On the basis of the number of new patients per age group

in the period 1990–1999, a linear trend was estimated

describing the incidence in the four age groups per million

of the population. This trend, combined with predictions of

the age-speciﬁc growth of the Dutch population, was used to

calculate the absolute number of new patients per age group

in the 10 year model period [4,5].

The null scenario

The null scenario explores the developments without ETOT.

The incidence per million of the age-speciﬁc population in

the 10 year model period is assessed according to the calcu-

lated linear trend. The distribution of these new patients over

treatment groups is equal to the average distribution in the

period 1997–1999. In the null scenario, the transition rates

are the average transition rates from the 3 year period 1997–

1999. Monthly transition rates were calculated as the ratio of

the transitions actually observed in a month and the number

of patients at the beginning of that month.

Scenarios with extended time on PD

Three scenarios were deﬁned to explore the direct effects of

ETOT. These scenarios differ from the null scenario in the

transition rates from PD to HD. For the period 1990–1999,

technique survival on PD was calculated. Figure 2 shows

the technique survival on PD, for patients starting their PD

treatment in the period 1990–1999. Using the Renine data,

it was found that for The Netherlands, median time on PD

until a transition to HD was 3.9 years for all PD patients.

In PD patients with ultraﬁltration failure, Wilkie et al. [1]

found a median extension of technique survival on PD of

22 months as a result of the use of polyglucose as a dialysis

ﬂuid. Peers et al. [6] found an extended continuous ambu-

latory peritoneal dialysis (CAPD) technique survival of at

least 1 year. It was estimated that incidence of ultraﬁltra-

tion failure in PD patients is 5% in the ﬁrst year of treatment,

30% after 3 years of PD treatment and 50% after 4 years [7,8].

To represent these estimates in the Markov model, the transi-

tion rates from PD to HD in the ﬁrst year of treatment

were kept constant. The assumption is that in the ﬁrst year

of treatment there is no effect of the use of polyglucose. In

one scenario it was assumed that the median time until

technique failure on PD increases by 10 months for all PD

patients. This corresponds with ;22 months of ETOT for

the 50% of patients with ultraﬁltration failure. Two other

scenarios were deﬁned, a scenario with a lower median

ETOT of 8 months and a scenario with a higher extension of

median technique survival of 12 months.

The monthly transition rates for later years on treatment

in the Markov model were adjusted to express the increased

time on PD treatment in such a way that the median time

on PD of 3.9 years increased by 8, 10 and 12 months.

Figure 2 shows the survival curve for the scenario with the

ETOT of 10 months, compared with the observed survival

curve in the period 1990–1999.

The adjusted transition rates were obtained by correcting

for the adjusted failure rate as an impact of ETOT. The

theoretical survival (s

t

) can be deﬁned as:

s

t

~(1{r)

t

ð1Þ

where r is the failure rate and t is the number of periods. If

T is the median time on PD in months, the failure rate r

can be described as:

r~1{e

(ln(0:5)=T)

ð2Þ

The extended median time is T

e

sTqextension. The

adjusted failure for each ETOT can be described as:

r

e

~1{e

(ln(0:5)=T

e

)

ð3Þ

where r

e

is the adjusted failure rate for ETOT.

The adjusted transition rates were calculated by multi-

plying all transition rates from PD to HD with a factor r

e

ur.

With a median time on PD of 3.9 years, the monthly failure

rate (r) is equal to 0.0147 and the failure rate for an extended

Fig. 2. Technique survival on PD with adjusted failure-rate.

392 T. J. G. Weijnen et al.

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time on PD (r

e

) of 8 months is equal to 0.0126. As a

consequence, the correction factor for all transition rates

from PD to HD is 0.8649. For the extended times of 10 and

12 months, the correction factors for all transition rates

are 0.8366 and 0.8101, respectively.

Scenarios with increased PD incidence and extended

time of 10 months

Because of ETOT, PD treatment will be more attractive to

patients and doctors. It can therefore be anticipated that the

share of patients starting their renal replacement therapy

with PD will increase. The relationship between ETOT and

increasing incidence in PD is unknown. Two scenarios have

been deﬁned in which the PD incidence increases by 10% or

by 20% compared with the inﬂow share in the null scenario.

The relative distribution of PD incidence over the age groups

has been kept equal to this distribution in the null scenario.

Compared with the null scenario, total ESRD incidence does

not change. Also, the share of transplants in the new patient

does not differ. In these two scenarios with increased PD

incidence, the extended time on PD treatment is 10 months.

Costs

To estimate the cost impact of extended time on PD treat-

ment, total costs of the renal replacement programme in ﬁve

scenarios were compared with total costs in the null scenario.

The cost estimates were based on a cost study in The

Netherlands [5]. In this study, total costs to society were

calculated per patient per year for different treatment and

age groups. Treatment groups were: FCCHD, LCCHD,

HHD, CAPD, continuous cycling peritoneal dialysis (CCPD)

and KTX; age groups were: 0–44, 45–64, 65–74 and 75q

years. The costs of PD used in the estimates consisted of

a weighted average of CAPD and CCPD costs. The weights

were the age-related shares of CAPD and CCPD patients in

total PD patients. Costs to society included costs of dialysis,

other dialysis-related healthcare costs and patient costs.

Costs of home adaptation for PD patients and travel costs

for HD and PD patients were also included.

Costs in the ﬁrst year on treatment and costs in the later

years on treatment were distinguished for each treatment and

age group. Total costs in the ﬁrst year of treatment were

higher than in the later years. In the ﬁrst year, costs of

hospitalization, vascular access operations and of training

of patients are higher than in later years. In the dialysis

treatment groups, costs in the two older age groups of

65–74 and 75q are higher than costs in the two younger age

groups. This is due to the higher costs of hospitalization in

the older age groups.

In the original cost study, additional costs of polyglucose

were not taken into account. In The Netherlands, these

costs amount to J3313 per patient per year. The extra costs

of polyglucose were added to the costs of PD for the

additional patient years as a result of ETOT. In general,

resource use was valued at real cost to society, not at

reimbursement rates. Originally costs were calculated at a

1996 price level. Using a price index for healthcare services,

costs have been updated to 1999 prices. To calculate total

costs of dialysis over a 10 year period in the six scenarios,

yearly costs were discounted using a rate of 4%.

Results

Figure 3 presents total estimated inﬂow per million

of the population per age group of ESRD patients in

the period 1990–2009. Figures from 1990 to 1999 are

actual inﬂow ﬁgures. The ﬁgures from 2000 to 2009 are

estimates using linear trend extrapolations for the

10 year period. This estimated trend has been used to

calculate the total number of new patients in the

estimation period.

The estimated trend indicates a stronger growth

of incidence in ESRD patients per million of the

population in the older age groups of 65–74 and 75q

compared with the age groups 0–44 and 45–64.

Table 1 summarizes the distribution of total number

of new patients over HD and PD treatment in shares

of total new patients per age group. The shares in the

Fig. 3. Inﬂow of ESRD patients per age group per million of the population. Realized inﬂow in the period 1991–1999 and estimated trend.

393Economic impact of using polyglucose

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null scenario are derived from the average relative

distribution of new patients over treatment and age

groups in the period 1997–1999 in The Netherlands.

Table 1 also presents the relative distribution in the

two scenarios with a 10% or 20% increased PD inﬂow

share.

Figure 4 presents the development of the PD shares

in the six scenarios in the 10 year model period from

2000 to 2009. The realized PD shares for 1999 are also

presented. The predicted PD share in the null scenario

initially increases from 30.5% at the beginning of 2000

to 31.0%, but decreases to 30.0% at the end of 2009

as a result of changes in the age distribution of the

dialysis population. The scenarios in which the median

time on PD treatment was increased by 8, 10 and

12 months, result in PD shares at the end of 2009

increasing to 30.8%, 31.0% and 31.1%, respectively.

If the PD inﬂ ow share increases by 10% or 20%, the

share of PD in total dialysis patients increases to

32.7% or 34.5% at the end of 2009.

Extended time on PD treatment results in a shift

of life years from HD to PD. The increase of PD

inﬂow shares enhances this shift of life years from HD

to PD. In Table 2, the total number of discounted

life-years on HD for the different scenarios over the

10 year modelling period are presented. The decrease

of patient years in HD equals the shift to PD. In the

scenario with an ETOT of 10 months, 1.0% of the

discounted life-years in the null scenario shifts from

HD to PD. In the scenarios with an ETOT of 8 or 12

months, this shift is 0.8% and 1.1%, respectively. In the

scenarios with an ETOT of 10 months and increased

inﬂow shares of 10% or 20%, the proportion of shifted

discounted life-years is 2.9% and 4.9%, respectively.

Table 3 shows the total discounted costs to society

of HD and PD treatment forecasted in different

scenarios.

In the ‘median survivalq10 months’ scenario, the

reduction in total co sts is 0.19% compared with the

null scenario. In the ‘median survivalq8 months’ and

in the ‘median survivalq12 months’ scenarios, the cost

reduction is 0.15% and 0.22%, respectively. In the

scenarios where the PD inﬂow share increases by 10%

and 20% together with an ETOT of 10 months, the

cost reduction is 0.58% and 0.96%, respectively. In the

null scenario the total costs per discounted patient

Table 1. Incidence per age group in the null scenario and the two scenarios with increased inﬂow shares, in shares of total new patients per age

group

Age group Scenarios HD PD KTX

0–44 Null scenario 52.3 41.5 6.2

10% increased PD inﬂow shareqETOT of 10 months 48.2 45.7 6.2

20% increased PD inﬂow shareqETOT of 20 months 44.0 49.8 6.2

45–64 Null scenario 60.9 35.5 3.7

10% increased PD inﬂow shareqETOT of 10 months 57.3 39.1 3.7

20% increased PD inﬂow shareqETOT of 20 months 53.7 42.6 3.7

65–74 Null scenario 76.6 23.0 0.4

10% increased PD inﬂow shareqETOT of 10 months 74.3 25.3 0.4

20% increased PD inﬂow shareqETOT of 20 months 72.0 27.6 0.4

75q Null scenario 84.6 15.4 0.0

10% increased PD inﬂow shareqETOT of 10 months 83.1 16.9 0.0

20% increased PD inﬂow shareqETOT of 20 months 81.5 18.5 0.0

Fig. 4. The PD share in the six scenarios over a 10 year model period (2000–2009) and the start value for the analysis at the end of 1999.

394 T. J. G. Weijnen et al.

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year for HD are J84 100. The total costs per

discounted patient year for PD are J60 300. These

costs constitute average HD and PD costs over the

model period, weighed by the total patient years per

treatment and age group. In the model period, a shift

from HD to PD results in cost savings of on average

28% per patient year.

Discussion

A Markov chain model was used to estimate the effect

of the use of polyglucose as a dialysis ﬂuid in patients

with ultraﬁltration failure over a 10 year period. The

total effect was distinguished between a direct effect

and an indirect effect. The direct effect results from

the extended time on PD treatment and the indir ect

effect occurs as the impact of increased PD inﬂow

shares. These increasing PD inﬂow shares are expected

to result from the improved perspect ive for patients

who stay longer on a stable PD treatment. Thr ee

scenarios were deﬁned in which the direct effect of

ETOT was modelled by increased median technique

survival of 8, 10 and 12 months for all PD patients.

Two other scenarios combined the extended time of

treatment of 10 months with increased PD inﬂow

shares of 10% and 20%. The null scenario was based

on technique success for HD, PD and KTX, as it was

observed in the Dutch ESRD regis try in the period

1997–1999. The effect measures were: the increased

PD share in the total ESRD programme at the end of

the 10 year period; the shift of discounted patient years

from HD to PD in the model period; and the cost

impact as a result of ETOT.

In the scenarios in which the median time on PD

treatment increases by 8, 10 and 12 months, the pre-

dicted PD share at the end of 2009 increases to 30.8%,

31.0% and 31.1%, respectively. The scenario with the

10 mon ths extended time on PD treatment and a 10%

increase of the PD inﬂow shares shows a PD share of

32.7% at the end of 2009. When the PD inﬂow share

increases by 20%, the share of PD in total dialysis

patients increases to 34.5% at the end of the model

period.

Compared with the null scenario, the scenarios in

which median technique success increases by 10 months

combined with increased PD inﬂow shares of 10%

and 20%, show a shift in discounted patient years

from HD to PD of 2.9% and 4.9%, respectively.

Although this seems to be low, the absolute number of

discounted patient years shifted from HD to PD is 988

and 1638 patient years respectively. The scenarios

with an ETOT of 8, 10 and 12 months show a shift

in patient years from HD to PD of 0.8%, 1.0% and

1.1%, respectively. In the model period, average

societal costs per patient on PD are estimated to be

28% lower than average societal costs per HD patie nt

(PD: J60 300 per year; HD J84 100 per year). Total

societal costs of dialysis can decrease by 0.6% to 1.0%

as a result of both the direct and indirect effects. This

implies for The Netherlands that societal costs

decrease by J35.4 million in the scenario with an

ETOT of 10 months and an increased PD inﬂow

share by 20%.

The analysis indicates that the impact resulting from

increased inﬂow shares is larger than the direct effect

of the ETOT. An additional analysis was performed

to investiga te the sensitivity of different assumptions

for our conclusion. In this sensitivity analysis, a

number of scenarios was used to investigate the

inﬂuence of increasing PD inﬂow sh ares and increased

time on treatment on the overall PD share. In one

group of scenarios, the PD-inﬂow share was increased

by 50%, in 10 steps of 5%. In another group of

scenarios the time on treatment was increased in

36 steps of 1 month. The model results from these

scenarios were used to estimate the inﬂuence of

increased PD-inﬂow shares and ETOT on overall

PD shares. Ordinary least square regressions were

applied to estimate these relationships. The regres sions

Table 2. Discounted patient years shifted from HD to PD over the

10 year model period

Scenarios Total number

of discounted

patient years in

HD patients

Discounted

patient years

shifted from

HD to PD

Share of

discounted patient

years shifted from

HD to PD

Null scenario 33641.7

ETOT of

8 months

33374.9 266.8 0.8%

ETOT of

10 months

33316.7 325.0 1.0%

ETOT of

12 months

33261.4 380.3 1.1%

10% increased

PD inﬂow

shareqETOT

of 10 months

32654.2 987.5 2.9%

20% increased

PD inﬂow

shareqETOT

of 10 months

32004.2 1637.5 4.9%

Table 3. Discounted societal costs of dialysis over the 10 year model

period (millions of Euros)

Scenarios HD PD Total

costs

Cost savings

compared

with the

null scenario

Savings

as % of

total costs

Null scenario 2828.9 898.6 3727.5

ETOT of

8 months

2806.5 915.3 3721.8 5.7 0.15%

ETOT of

10 months

2801.6 918.9 3720.5 7.0 0.19%

ETOT of

12 months

2797.0 922.4 3719.4 8.1 0.22%

10% increased

PD inﬂow

shareqETOT

of 10 months

2746.2 959.6 3705.8 21.7 0.58%

20% increased

PD inﬂow

shareqETOT

of 10 months

2691.9 1000.2 3692.1 35.4 0.96%

395Economic impact of using polyglucose

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indicated that an increase of the PD inﬂow by 1%

causes the PD shares to increase by 0.57%. An increase

of the technique survival on PD by 1% causes the PD

share to increase by 0.11%. The sensitivity analysis

conﬁrmed our conclusion that the inﬂuence of

increasing PD shares is larger than the inﬂuence of

ETOT.

It is possible that PD patients with ultraﬁltration

failure switch to CCPD when using polyglucose to

extend time on PD treatment. This could have an

impact on costs because CCPD is more expensive

than CAPD. It is unknown whether ETOT would

result in a substantial increase in CCPD. The possible

cost impact has already been partially incorporated

into our cost estimates. The PD costs per patient per

year used in the cost estimates are an average of

CAPD and CCPD costs weighted by the age-speciﬁc

shares of CAPD and CCPD in total PD patients. The

question is whether ETOT changes these age-speciﬁc

shares. The relationship between ETOT and a switch

from CAPD to CCPD needs further investigation

before a possible impact on costs can be estimated.

This study concentrated on the effect the use of

polyglucose has on PD shares in total renal replace-

ment therapy. The results from the Markov modelling

indicated higher PD shares. Consequently, direct and

indirect effects of extended time on PD treatment

result in cost savings that can amount to 1.0% of the

total cost of dialysis treatment in The Netherlands.

Although the relative cost savings are low, the absolute

cost savings are substantial. These cost savings make

it possible to offer dialysis treatment to more patients

with equal budgets. In The Netherlands, the cost

savings would allow for 452 more HD patient years or

635 more PD patient years in the 10 year model period.

On a worl dwide scale, the dialysis budget is estimated

to be $100 billion [9]. In view of these high dialysis

costs to society, a saving of 1.0% can be considered to

be relevant for healthcare policy makers.

Acknowledgements. The authors would like to thank Martin

Nieuwenhuizen of Renine for his help with the data gathering and

analysis. Preliminary results from this study were presented at the

ERA-ETDA Conference, 17–20 September 2000, Nice; at the ASN

Conference, 13–16 October 2000, Toronto; and at the ISPD

Conference, 26–29 June 2001, Montreal. This work was supported

by an unrestricted grant from Baxter USA.

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Received for publication: 1.2.02

Accepted in revised form: 19.9.02

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