Introduction
Utility values are commonly used in economic evaluations to calculate quality adjusted life years (QALYs), an index encompassing duration and quality of life. The basic construct of a QALY is that people move through different health states over time, all of which have a certain value attached to it [
1]. Such values, referred to as utility values, can be estimated using multiple sources, including preferences from patients, carers, health professionals, and members of the general public [
1,
2]. Currently, there is no agreement on whose preferences should be used to obtain utility values. Agencies, such as the United Kingdom National Institute for Health and Care Excellence and the Dutch Health Care Institute, advocate the use of general public preferences for the assessment of new healthcare services [
3,
4]. By contrast, the Swedish Dental and Pharmaceutical Benefits Agency prefers the use of patient preferences [
3‐
5].
There are theoretical arguments in support of the use of either patient or general public preferences [
5,
6]. For example, claims exist in favor of using general public preferences, as members of the general public are those paying for healthcare services in most healthcare systems. By contrast, patients’ preferences may be preferred because healthcare systems ultimately aim to improve patients’ health, and patients have a better understanding of their own health than members of the general public who can only imagine it [
1,
2,
6‐
11] As a conclusive justification for using either one of those preferences seems to be lacking, Versteegh and Brouwer (2016) argued that the most elegant solution would be to include both patient and general public preferences [
7].
The issue of whose preferences should be used is not the only important one. Another important aspect is what should be valued. General public preferences are typically obtained using hypothetical health state descriptions. The most commonly used health state descriptions are generic preference-based measures, such as the EQ-5D and the SF-6D, but alternatives, such as disease-specific measures or vignettes, are also viable options [
2,
12]. More rarely, members of the general public are asked to value their own health directly, a procedure that has been recently named experience-based utility [
13]. Patient preferences, on the other hand, are most commonly obtained by asking patients to value their own health state, with the use of hypothetical health states being rare, but not non-existent (e.g. [
14]) [
2,
12].
Despite the existence of different combinations between whose preferences should be used and what should be valued, the debate in the literature has traditionally focused on comparing general public values obtained from hypothetical health states (further referred to as “general public values”) and patients’ values obtained from self-assessments of their own health (further referred to as “patient values”). Within this framework, there is substantial evidence that values obtained from both of these populations differ (e.g. [
15]). More specifically, values elicited by patients tend to be higher than those elicited by members of the general public. This indicates that patients perceive their own health as better than members of the general public do [
15‐
18]. However, there are also studies reporting the opposite [
19‐
22].
Preliminary evidence indicates that the magnitude of the identified disagreements between patient and general public values differs across patient sub-groups [
22‐
24]. In one study, for example, the magnitude of disagreement between patient and general public values was found to differ by socio-demographic group [
23], whereas another study found it to depend on a patient’s health status [
22]. Gaining further insight into this issue is important, as it increases our understanding of whether the identified disagreements between patient and general public values are related to the EQ-5D instrument itself, inherent characteristics of the raters, or a combination of both [
23]. If the identified disagreements would be largely related to inherent characteristics of the raters, this would also mean that some patient sub-groups rate their own health systematically different than others. From an equity perspective, this would be unacceptable, as certain sub-groups may then get a higher priority in the competition for already scarce healthcare resources than others [
24].
In a previous study, the current research group has already found patient values to be higher than general public values among low back pain patients [
25]. However, due to a relatively small sample size and little information on the patients’ socio-demographic and health status characteristics, it was not possible to explore whether the magnitude of disagreement between both values differed by socio-demographic group and/or health status. This study aims to build on the previous work by exploring whether the magnitude of disagreement between patient and general public values differs by socio-demographic group and/or health status in a large consecutive cohort of chronic low back pain patients.
Results
A total of 5492 out of 5659 low back pain patients completed the screening questionnaire (response rate = 97.2%). Of them, 455 were excluded from the analyses, because they experienced low back pain complaints for less than 3 months (
n = 272) or had missing educational level data (
n = 183). Data were complete for all remaining patients (
n = 5037). An overview of the patients’ socio-demographic and health status characteristics is provided in Table
2.
Table 2
Participant characteristics
Socio-demographic | Age (years) [mean (SD)] | 50.5 (14.9) |
Female [n (%)] | 2921 (58.0) |
Educational level [n (%)] | |
Low | 3579 (71.1) |
Intermediate | 401 (8.0) |
High | 1056 (21.0) |
Social support (yes) [n (%)] | 2862 (56.8) |
Health Status | Back pain intensity (0–10) [mean (SD)] | 7.1 (1.7) |
Leg pain intensity (0–10) [mean (SD)] | 5.3 (3.2) |
Functional status (Oswestry Disability Index 0- range: 0- | 42.7 (15.9) |
100) [mean (SD)] | |
Comorbidities (yes) [n (%)] | 1486 (29.5) |
Catastrophizing (yes) [n (%)] | 1886 (37.5) |
Positive treatment expectations (yes) [n (%)] | 2873 (57.1) |
On average, patient values (mean = 0.515; SD = 0.240) were statistically significantly higher than general public values (mean = 0.445; SD = 0.187)(mean difference = 0.069; 95%CI: 0.063 to 0.076).
The magnitude of disagreement between patient and general public values was found to be statistically significantly associated with
all socio-demographic variables, i.e. age, gender, education level, and social support as well as
two health status variables, i.e. functioning and comorbidities (Table
3). Associations with the health status variables back pain intensity, leg pain intensity, catastrophizing, and treatment expectations were not statistically significant.
Table 3
Associations of socio-demographic and health status characteristics with the disagreement between patient and general public values, adjusted for all other socio-demographic and health status characteristics
Socio-demographic | Age (years) | −0.001* | 1% | 0.000 | −0.001 | 0.000 |
Gender (ref: Male) | | | | | |
Female | −0.016* | 23% | 0.007 | −0.029 | −0.003 |
Educational level (ref: Low) | | | | | |
Intermediate | −0.006 | 9% | 0.011 | −0.028 | 0.016 |
High | −0.017* | 25% | 0.008 | −0.033 | −0.001 |
Social support (ref: No) | | | | | |
Yes | 0.022* | 32% | 0.007 | 0.008 | 0.037 |
Health Status | Back pain intensity (0–10) | 0.001 | 1% | 0.001 | −0.001 | 0.004 |
Leg pain intensity (0–10) | 0.003 | 3% | 0.002 | −0.001 | 0.007 |
Functional status (Oswestry Disability | | | | | |
Index) (range: 0–100) | 0.001* | 1% | 0.000 | 0.001 | 0.002 |
Co-morbidities (ref: No) | | | | | |
Yes | −0.037* | 54% | 0.008 | −0.053 | −0.023 |
Catastrophizing (ref: No) | | | | | |
Yes | −0.012 | 16% | 0.007 | −0.026 | 0.002 |
Positive treatment expectations (ref: No) | | | | | |
Yes | 0.015 | 20% | 0.007 | −0.002 | 0.028 |
Constant | 0.021 | 30% | 0.018 | −0.014 | 0.056 |
As for the socio-demographic characteristics, the magnitude of disagreement was found to decline with age, to be smaller among females compared with males, to be smaller among patients with a high level of education compared with patients with a low level of education, and to be larger among patients who had social support compared with those who did not (Table
3). Of them, social support had the strongest impact on the magnitude of disagreement.
As for the health status characteristics, the magnitude of disagreement was found to increase with a decreasing functioning level and to be smaller among patients with co-morbidities compared with patients without comorbidities (Table
3). Of them, co-morbidities had the strongest impact on the magnitude of disagreement.
Discussion
In this study, patient values were found to be 0.069 (95%CI: 0.063 to 0.076) points higher than general public values in a large cohort of chronic low back pain patients. This difference is not only statistically significant, but also exceeds the minimal clinically important difference of 0.03 for the EQ-5D-3L among Dutch chronic low back pain patients [
39]. This indicates that, on average, chronic low back pain patients perceive their own health state to be better than members of the general public do. Additionally, it was found that the magnitude of disagreement between patient and general public values differed by various socio-demographic and health status characteristics.
Our finding that patient values were higher than general public values is in line with the majority of research on this topic [
15‐
18,
25]. Peeters et al., for example, found patient values to be higher than general public values in a meta-analysis of 30 studies in various patient populations [
15]. More recent studies also found patient values to be higher than general public values among injured people [
40], prostate cancer patients [
41], and heart disease patients [
42]. Similarly, the current research group found patient values to be higher than those of the general public in a relatively small sample of low back pain patients [
43].
The magnitude of disagreement between patient and general public values was found to differ by the socio-demographic characteristics age, gender, education level, and social support as well as the health status characteristics functioning and comorbidities. This is more or less in line with previous studies assessing the source of differences between patient values and general public values. Franks et al., for example, found the magnitude of disagreement between patient values and general public values to statistically significantly differ by gender and education level, but not by age and the number of health conditions a patient suffered from [
24]. Insinga et al. and Mann et al. found the magnitude of disagreement between patient values and general public values to be statistically significantly associated with illness severity [
23] and health condition [
22]. However, some of these authors were of the opinion that the statistically significant associations were too small to be considered relevant [
23,
24]. We respectfully disagree with this interpretation, as –in the study of Franks et al. for example – the statistically significant regression coefficients accounted for as much as 22% of the average mean difference between patient and general public values; something which we consider highly relevant [
24].
The current findings contradict the conclusion of Insinga et al. that socio-demographic and health status characteristics account for a negligible fraction of the disagreements between patient and general public values, and that differences between both values can mainly be ascribed to the EQ-5D instrument itself [
23]. Rather, they suggest that patient characteristics do account for a relevant fraction of the identified disagreements between patient and general public values, and that mechanisms thought to be responsible for these disagreements, such as
adaptation and
response shift, have a differential impact across patient sub-groups [
6]. For example, the identified negative association between the magnitude of disagreement and age suggests that the degree to which patients value a certain EQ-5D-3L health state higher than members of the general public do decreases with age. This may be due to older people being less able to
adapt to longer-term ill health than younger people and/or older people being are less influenced by
response shift. In line with findings of Cubi-Molla et al. (2019), this also suggests that older people value their own health state lower than younger people do. Please note that this is true because general public values are fixed, meaning that every EQ-5D-3L health state is only associated with one utility value, whereas patient values are variable and may thus in- or decrease with age [
44].
One should bear in mind that the present study does not provide an answer to the questions of
“Who should value health?” and
“What mechanism(s) are responsible for the identified disagreements between patient and general public values?”. The first question remains a “normative issue”, whereas more empirical research is needed to establish what mechanisms are responsible for the identified disagreements between patient and general public values. However, the present findings do highlight an important ethical issue, namely that LBP patients with the same EQ-5D-3L health state do not necessarily value their own health equally and that the identified differences across patients are associated with various socio-demographic and health status characteristics. This in turn suggests that the use of patient values in economic evaluations may lead to socio-demographic and/or health status inequalities. To illustrate, in line with previous research [
44], older patients were found to systematically rate their own health lower than younger patients. As a consequence, the incremental gain from restoring older people to full health will likely be greater than that of younger people. From an equity standpoint, this would be unacceptable, as interventions aimed at older populations will then be more likely to be cost-effective compared with interventions aimed at younger populations, and will thus get a higher priority in the competition for already scarce healthcare resources. This issue may be dealt with by using both patient and general public valuations, as previously suggested by Versteegh and Brouwer [
7]. Conversely, it might also be possible that a certain intervention is not cost-effective on average, but cost-effective for a sub-group of older patients. In such instances, preference sub-group analyses can be used to recognize that there may be certain sub-groups whose preferences are significantly different from the overall average to produce meaningfully different cost-effectiveness outcomes [
44].
Strengths of this study are the fact that it was one of the first to explore whether the magnitude of the disagreement between patient and general public values differs by socio-demographic group and/or health status, its use of a large cohort of consecutive patient data (
n = 5037) as well as its high response rate (i.e. 97.5%). Some limitations are noteworthy as well. First, in this study, only Dutch chronic low back pain patients were included. As a consequence, it is unknown whether the present findings are generalizable to other patient populations, healthcare settings, and countries. Future research is needed to establish this. Second, this study relied heavily on EQ-VAS valuations, whereas VAS values are generally considered to be inferior to choice-based scaling methods, such as the Standard Gamble and the Time Trade Off. Future research is needed to explore whether the current findings hold when using the Standard Gamble and the Time Trade Off [
27]. Third, as routinely collected patient data were used in the present study, we could only assess the impact of socio-demographic and health status variables that were part of the hospital’s spine registry. As a consequence, we may have missed important variables or/and variables may have been assessed in a way that is more relevant to clinical practice than to the current research question. Fourth, for transforming EQ-VAS scores into utility values, the patients’ preferences for the health states “dead” and “full health” are required. In the present study, however, patients did not value these health states and we therefore had to rely on previously published general public data for converting the patients’ EQ-VAS scores into utility values. Strictly speaking, we were therefore not able to achieve full comparability between patient and general public values [
22]. Another design aspect that may have hampered full comparability is that experience-based patient values were compared with hypothetical general public values. This limitation may have been dealt with by using an experience-based EQ-5D-3L value set, such as the Swedish one [
45]. Currently, however, an experience-based value set is not available for the Netherlands. A third design aspect that may have hampered full comparability is the fact that patients seem to think about different health aspects when completing the EQ-VAS and the EQ-5D. That is, overall health for the EQ-VAS and mobility, self-care, usual activities, pain/discomfort, and anxiety/depression for the EQ-5D [
46].
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