A Kaarlola

Anne M. Rissanen

AS Pickard

C Granja

C Lamer

D Dowdy

DC Angus

GJ Peek

H Sintonen

Harri Sintonen

J Brazier

J Moock

K Stavem

P Dolan

P Rasanen

Pirjo Räsänen

Risto P. Roine

S Frick

S Karlsson

S Saarni

Tarja Vainiola

Ville Pettilä

X Badia

English

PubMed

Springer - Publisher Connector

Tarja Vainiola
Ville Pettila¨
Risto P. Roine
Pirjo Ra¨sa¨nen
Anne M. Rissanen
Harri Sintonen
Comparison of two utility instruments,
the EQ-5D and the 15D, in the critical
care setting
Received: 8 April 2009
Accepted: 11 May 2010
Published online: 6 August 2010
 The Author(s) 2010. This article is
published with open access at
Springerlink.com
Electronic supplementary material
The online version of this article
(doi:10.1007/s00134-010-1979-1) contains
supplementary material, which is available
to authorized users.
T. Vainiola ())
Department of Anaesthesiology
and Intensive Care Medicine,
Helsinki University Central Hospital,
P.O. Box 340, 00029 HUS,
Helsinki, Finland
e-mail: tvainiol@mappi.helsinki.fi
Tel.: ?358-50-3505216
Fax: ?358-9-47174059
V. Pettila¨
Department of Epidemiology
and Preventive Medicine,
Australian and New Zealand Intensive
Care Research Center, Monash University,
Melbourne, Australia
R. P. Roine  A. M. Rissanen
Helsinki and Uusimaa Hospital District,
Administration, P.O. Box 705,
00029 HUS, Helsinki, Finland
P. Ra¨sa¨nen
Helsinki and Uusimaa Hospital District,
Administration and Finnish Office for
Health Technology Assessment, Finland,
P.O. Box 30, 00271 Helsinki, Finland
H. Sintonen
Department of Public Health and Finnish
Office for Health Technology Assessment,
University of Helsinki, P.O. Box 41,
00014 Helsinki, Finland
Abstract Purpose: Reliable mea-
sures are required for proper cost–
utility analysis after critical care. No
gold standard is available, but the
EQ-5D health-related quality of life
instrument (HRQoL) has been pro-
posed. Our aim was to compare the
EQ-5D with another utility measure,
the 15D, after critical illness. Meth-
ods: A total of 929 patients filled in
both the EQ-5D and 15D HRQoL
instruments 6 and 12 months after
treatment at an intensive care or high-
dependency unit. The difference in
the medians and distributions of the
scores of the instruments was tested
with Wilcoxon signed-rank test and
their association with Spearman rank
correlation. Discriminatory power
was compared by the ceiling effect
and agreement between the
instruments regarding the direction of
the minimal clinically important
change in the HRQoL scores between
6 and 12 months was tested with the
McNemar-Bowker test and Cohen’s
kappa. Results: The utility scores
produced by the instruments and their
distributions were different. Agree-
ment between the instruments was
only moderate. The 15D appeared
more sensitive than the EQ-5D both
in terms of discriminatory power and
responsiveness to clinically important
change. Conclusion: The agreement
between the two utility measures was
only moderate. The choice of the
instrument may have a substantial
effect on cost-utility results. Our
results suggest that the 15D performs
well after critical illness, but further
large cohort studies comparing dif-
ferent utility instruments in this
patient population are warranted
before the gold standard for utility
measurement can be announced.
Keywords EQ-5D  15D  Intensive
care  Quality of life  Sensitivity 
Responsiveness
Introduction
Health-related quality of life (HRQoL) is an important
patient-reported outcome after critical illness. In the
intensive care context, several generic profile instruments,
such as the SF-36 [1], the Sickness Impact Profile [2], and
the Nottingham Health Profile [3], have been used. Also,
the EQ-5D, a generic utility instrument enabling the
Intensive Care Med (2010) 36:2090–2093
DOI 10.1007/s00134-010-1979-1 ORIGINAL
calculation of quality-adjusted life years (QALYs) and
allowing the comparison of the cost-utility of interven-
tions across different medical specialities, has been used
[4–8]. Although no HRQoL instrument can claim to be
the gold standard, the 2002 Brussels Roundtable Con-
sensus meeting recommended the SF-36 and EQ-5D as
the preferred HRQoL instruments in the critical care
setting [9], but at the same time encouraged further
methodological research and instrument design.
There is still an evident lack of comparisons between
utility instruments in the critical care setting. The RAND-
36 (SF-36) and the EQ-5D have been compared, and the
former turned out to have slightly more discriminatory
power [10]. However, the EQ-5D is currently the most
widely used utility instrument worldwide for the calcu-
lation of QALYs [11]. Thus, it seemed appropriate to
choose it in this study as the comparator to the 15D,
which is the most frequently used utility instrument in
Finland, although a possibility to generate a utility score
(SF-6D) also from the SF-36 data has been introduced
[12]. The 15D and EQ-5D have previously been com-
pared in a number of other populations and patient groups
[13–15], but not in critical care.
Materials and methods
Patients
The data were collected prospectively in the Helsinki
University Hospital between 1 January 2003 and 31
December 2004. The study was approved by the local
Ethics Committee. Informed consent was obtained from
the patients. The study population consisted of 3,600
patients treated in two intensive care (ICU) and three
high-dependency units (HDU).
HRQoL instruments
The EQ-5D and 15D were mailed to patients alive and
with a known address 6 and 12 months after admission to
the ICU or HDU together with an accompanying letter
and an informed consent form. The patients were asked to
return the questionnaires and the consent in a prepaid
envelope. In case of non-response, one reminder was sent.
Possible readmissions after the index admission did not
start a new follow-up.
The EQ-5D consists of five dimensions: mobility, self-
care, usual activities, pain or discomfort, and anxiety or
depression. Each dimension is divided into three levels:
no problems, some problems and severe problems.
Instead of the Finnish VAS-based valuation algorithm
used in some earlier Finnish critical care studies [5, 16],
we used the UK time-trade-off (TTO) ‘‘tariff,’’ which is
the most commonly used valuation system for the EQ-5D.
According to it the utility scores range from -0.59 to 1,
where 1 means full health and 0 stands for death. No
health state can obtain a score between 0.88 and 0.99, and
negative scores indicate health states worse than death
[17]. The minimal clinically important difference (MID)
for the EQ-5D TTO is about 0.08 [18].
The 15D consists of 15 dimensions: breathing, mental
function, speech, vision, mobility, usual activity, vitality,
hearing, eating, elimination, sleeping, distress, discomfort
and symptoms, depression and sexual activity. Each
dimension is divided into five levels from no problems to
extreme problems. The utility scores of the 15D range from
0 to 1, with 1 being equivalent to full health and 0 to death
[19]. The MID of the 15D has been estimated as 0.03 [20].
Statistical analysis
The mean and median scores of the two instruments at
6 months were calculated. The visual inspection of the
distribution of the EQ-5D scores suggested that the use of
classical parametric tests to compare the two sets of
scores may not be appropriate. Therefore, the Wilcoxon
signed-rank test was used to test the difference in medians
and distributions. The Spearman rank correlation coeffi-
cient was used to measure the association and a Bland-
Altman plot to describe the agreement between the sets at
6 months. The discriminatory power of the instruments
was explored by comparing the proportion of patients
obtaining the ceiling score of 1 (ceiling effect). To ana-
lyse the agreement in the direction of change of the
HRQoL scores between 6 and 12 months, a 3 9 3 matrix
was constructed. The changes were classified according to
MID as negative, if the change was B-0.08 and B-0.03,
and positive, if the change was C0.08 and C0.03 for the
EQ-5D and 15D, respectively. Other values were classi-
fied as unchanged. The McNemar-Bowker test was used
to test whether the instruments give a similar picture of
the changes (the matrix is symmetric) and Cohen’s kappa
to test the agreement between the instruments. The
p values \0.05 were considered statistically significant.
Results
Both the 6- and 12-month questionnaires were returned by
998 patients (38% of the 2,600 patients alive). However,
69 of the EQ-5D questionnaires were not filled in com-
pletely, leaving 929 patients for final analysis. Of them,
31% had been treated in an ICU and 69% in a HDU. For
characteristics of the study population, see electronic
material.
The distributions of the EQ-5D and 15D scores at
6 months are presented in Fig. 1. The distribution of the
2091
EQ-5D scores was wide, three-peaked and discontinuous,
whereas that of the 15D was one-peaked and continuous.
The rank correlation between the two sets of scores was
0.811 (p \ 0.001). The mean (median) utilities at 6 months
were 0.832 (0.859) and 0.731 (0.760) for the 15D and EQ-
5D, respectively. The medians and distributions were dif-
ferent (p \ 0.001) and the agreement between the sets poor
(Bland-Altman plot in electronic material). The EQ-5D
detected fewer health states than the 15D (at 6 months 79
vs. 767, at 12 months 70 vs. 745). Using the EQ-5D, 26%
of patients had a ceiling score of 1 compared to 6% for the
15D. Regarding the clinically important change in the
HRQoL scores between 6 and 12 months, the instruments
had the same direction of change in 53% of the patients.
The EQ-5D showed no change in 61% of patients, the 15D
in 46%. Overall, the instruments gave a different picture of
the changes (Bowker 53.9, p \ 0.001), and the agreement
between them was only fair (kappa 0.24, 95% CI 0.19,
0.29; (Table 1).
Discussion
Patient-reported outcomes such as HRQoL have gained
increased importance as measures of effectiveness of
health care. Of the HRQoL instruments used in the
assessment of critical care, only a few produce a utility
score necessary for the calculation of QALYs. These
include the EQ-5D and 15D, which we compared in this
large cohort study. Regardless of the statistical test used,
the agreement between the instruments was only moderate.
The main reason for this may be the wide, three-
peaked and discontinuous distribution of the TTO-based
EQ-5D scores with a high ceiling effect. Because of these
features of the EQ-5D scores, classical methodology used
for comparisons and evaluation of agreement between
scores may not be applicable. The existence of negative
utilities implies that HRQoL could be improved by dying,
which is not logically congruent with the objectives of
care, although from an ethical and economic point of
view, a permanent non-independent health state may be
worse than death. The distribution of the 15D scores (all
positive values) was one-peaked and continuous and,
importantly, only 6% of the patients evaluated their health
state as perfect at 6 months after critical illness, indicating
better discriminatory power of the 15D in minor health
problems. The EQ-5D detected fewer health states and
clinically important changes in HRQoL than the 15D. In
this light, the 15D appeared more sensitive than the EQ-
5D in terms of discriminatory power and responsiveness
to clinically important change, although in the absence of
a gold standard, it is not possible to say which instrument
is ‘‘right.’’ In these respects our results agree with those
obtained previously in a number of populations and
patient groups [13–15].
Strengths and limitations
One strength is that HRQoL was measured simulta-
neously by both instruments. Our comparison revealed,
therefore, differences and agreement regarding the
instruments. In addition, the patient population was large
(despite of the response rate of 38%). In general, the lack
of baseline HRQoL scores may be seen as a limitation,
Fig. 1 The distributions of the EQ-5D and 15D scores at 6 months
Table 1 The direction of the minimal clinically important change (MID) in the HRQoL scores between 6 and 12 months
Change greater than the MID (0.08) in the EQ-5D score Total
Negative (%) Unchanged (%) Positive (%)
Change greater than the MID (0.03)
in the 15D score
Negative (%) 10.1 11.8 2.8 24.7
Unchanged (%) 6.4 32.4 7.2 46.0
Positive (%) 1.6 16.8 10.9 29.3
Total (%) 18.1 61.0 20.9 100.0
2092
but in the comparison of two instruments, as in our study,
does not pose a problem. ICU and HDU patients were
analysed together, but as only 34% of the sample belon-
ged to the ICU subset, our results do not necessarily
reveal how the instruments may work in comparison
when applied exclusively to ICU patients.
Conclusion
In conclusion, the 15D may be more sensitive than the
EQ-5D in terms of discriminatory power and respon-
siveness to clinically important change. The agreement
between the EQ-5D and 15D utilities was only moderate.
As utilities differ depending on the HRQoL instrument
used, the results of the cost-utility studies in the critically
ill are difficult to compare. In the future, large cohort
studies are warranted to produce sufficient comparative
evidence regarding utility measures, including the SF-6D
and the 15D, before the gold standard for utility mea-
surement may be announced.
Open Access This article is distributed under the terms of the
Creative Commons Attribution Noncommercial License which
permits any noncommercial use, distribution, and reproduction in
any medium, provided the original author(s) and source are
credited.
References
1. Kaarlola A, Pettila¨ V, Kekki P (2003)
Quality of life 6 years after intensive
care. Intensive Care Med 29:1294–1299
2. Frick S, Uehlinger DE, Zu¨rcher
Zenklusen RM (2002) Assessment of
former ICU patients’ quality of life:
comparison of different quality-of-life
measures. Intensive Care Med
28:1405–1410
3. Lamer C, Harboun M, Knani L, Moreau
D, Tric L, LeGuillou J-L, Gasquet I,
Moreau T (2004) Quality of life after
complicated elective surgery requiring
intensive care. Intensive Care Med
30:1594–1601
4. Dowdy D, Eid M, Sedrakyan A,
Mendeze-Tellez P, Pronovost P,
Herrdige M, Needham D (2005) Quality
of life in adult survivors of critical
illness: a systematic review of the
literature. Intensive Care Med
31:611–620
5. Kaarlola A, Tallgren M, Pettila¨ V
(2006) Long term survival, quality of
life and quality-adjusted life-years
among critically ill elderly patients. Crit
Care Med 34:2116–2120
6. Badia X, Diaz-Prieto A, Gorriz M,
Herdman M, Torrado H, Farrero E,
Cavanilles J (2001) Using the EuroQol-
5D to measure changes in quality of life
12 months after discharge from an
intensive care unit. Intensive Care Med
27:1901–1907
7. Granja C, Teixeira-Pinto A, Costa-
Pereira A (2002) Quality of life after
intensive care—evaluation with EQ-5D
questionnaire. Intensive Care Med
28:898–907
8. Peek GJ, Mugford M, Tiruvoipati R,
Wilson A, Allen E, Thalanany MM,
Hibbert CL, Truesdale A, Clemens F,
Cooper N, Firmin RK, Elbourne D, for
the CESAR trial collaboration (2009)
Efficacy and economic assessment of
conventional ventilatory support versus
extracorporeal membrane oxygenation
for severe adult respiratory failure
(CESAR): a multicentre randomised
controlled trial. Lancet 374:1351–1363
9. Angus DC, Carlet J (2003) Surviving
intensive care: a report from the 2002
Brussels Roundtable. Intensive Care
Med 29:368–377
10. Kaarlola A, Pettila¨ V, Kekki P (2004)
Performance of two measures of
general health-related quality of life, the
EQ-5D and the RAND-36 among
critically ill patients. Intensive Care
Med 30:2245–2252
11. Rasanen P, Roine E, Sintonen H,
Semberg-Konttinen V, Ryynanen OP,
Roine R (2006) Use of quality-adjusted
life years for the estimation of
effectiveness of health care: a
systematic literature review. Int J
Technol Assess Health Care
22:235–241
12. Brazier J, Roberts J, Deverill M (2002)
The estimation of a preference-based
measure of health from the SF-36.
J Health Econ 21:271–292
13. Stavem K (1999) Reliability, validity
and responsiveness of two
multiattribute utility measures in
patients with chronic obstructive
pulmonary disease. Qual Life Res
8:45–54
14. Saarni S, Ha¨rka¨nen T, Sintonen H,
Suvisaari J, Koskinen S, Aromaa A,
Lo¨nnqvist J (2006) The impact of 29
chronic conditions on health-related
quality of life: a general population
survey in Finland using 15D and EQ-
5D. Qual Life Res 15:1403–1414
15. Moock J, Kohlman T (2008)
Comparing preference-based quality-
of-life measures: results from
rehabilitation patients with
musculoskeletal, cardiovascular or
psychosomatic disorders. Qual Life Res
17:485–495
16. Karlsson S, Ruokonen E, Varpula T,
Ala-Kokko TI, Pettila¨ V (2009) Long
term outcome and quality-adjusted life
years after severe sepsis. Crit Care Med
37:1–7
17. Dolan P (1997) Modeling valuations for
EuroQol health states. Med Care
35:1095–1108
18. Pickard AS, Neary MP, Cella D (2007)
Estimation of minimally important
differences in EQ-5D utility and VAS
scores in cancer. Health Qual Life
Outcomes 5:70
19. Sintonen H (2001) The15D instrument
of health-related quality of life:
properties and applications. Ann Med
33:328–336
20. Sintonen H (1994) Outcome
measurement in acid-related diseases.
PharmacoEconomics 5(Suppl. 3):17–26
2093


Comparison of two utility instruments, the EQ-5D and the 15D, in the critical care setting

Crossref

Intensive Care Medicine

Comparing preference-based qualityof-life measures: results from rehabilitation patients with musculoskeletal, cardiovascular or psychosomatic disorders.

CostaPereira A

Estimation of minimally important differences in EQ-5D utility and VAS scores in cancer.

for the CESAR trial collaboration (2009) Efﬁcacy and economic assessment of conventional ventilatory support versus extracorporeal membrane oxygenation for severe adult respiratory failure (CESAR): a multicentre randomised controlled trial.

Long term outcome and quality-adjusted life years after severe sepsis. Crit Care Med 37:1–7

Long term survival, quality of life and quality-adjusted life-years among critically ill elderly patients. Crit Care Med 34:2116–2120

Modeling valuations for EuroQol health states.

Outcome measurement in acid-related diseases.

Performance of two measures of general health-related quality of life, the EQ-5D and the RAND-36 among critically ill patients. Intensive Care Med 30:2245–2252

Quality of life 6 years after intensive care. Intensive Care Med 29:1294–1299

Quality of life after complicated elective surgery requiring intensive care. Intensive Care Med 30:1594–1601

Quality of life in adult survivors of critical illness: a systematic review of the literature. Intensive Care Med 31:611–620

Reliability, validity and responsiveness of two multiattribute utility measures in patients with chronic obstructive pulmonary disease.

Surviving intensive care: a report from the 2002 Brussels Roundtable. Intensive Care Med

The estimation of a preference-based measure of health from the SF-36.

The impact of 29 chronic conditions on health-related quality of life: a general population survey in Finland using 15D and EQ5D.

The15D instrument of health-related quality of life: properties and applications.

Use of quality-adjusted life years for the estimation of effectiveness of health care: a systematic literature review.

Using the EuroQol5D to measure changes in quality of life 12 months after discharge from an intensive care unit. Intensive Care Med

Zu ¨rcher Zenklusen RM (2002) Assessment of former ICU patients’ quality of life: comparison of different quality-of-life measures. Intensive Care Med 28:1405–1410

https://link.springer.com/content/pdf/10.1007%2Fs00134-010-1979-1.pdf

Comparison of two utility instruments, the EQ-5D and the 15D, in the critical care setting

Abstract

Similar works

Full text

Available Versions

Springer - Publisher Connector

Crossref