REVIEW ARTIC LE ~canarrocs I (~) oIOO~!~, 1995 111(j.~SOo5O,(J

The Short-Form 36 (SF-36) Health Survey and Its Use in Pharmacoeconomic Evaluation Johll Brazier

Sheffield Centre for Health and Related Resea rch, University of Sheffield, Sheffield, England

Contents Summary I . The Short-Form 36 (Sf-36) Health Survey .

1.1 DescnptiOn 1.2 HiStory and Development

2. The PsychOmetriC FoundatiOns of the SF·36 . 2.1 Reliability. 2.2 Volldity

3. Using SF-36 ScOfes in Economic Evaluation 3,1 Cost-Minimisation Anolysis . 3,2 Cost-EHec tiveness Analysis 3.3 Cost-Utility Analysis .

4. Economic Criticisms of the SF·36 4.1 Item Selection. 4.2 Scoring of the SF-36 . 4.3 Risk 4 .4 Time .

5. The Sf-36 and Preference-Based Measures . 6. DerMng a Single Index from SF-36

6.1 Arbitrary Weights 6.2 Multi-Attribute Utility Theory 6.3 Scenario Approaches

7, Conclusion .

403

"" "" · "" · 406 · 406 · 406

408 408 408 408 '09 409 409 409

· 410 · 410 . 411

41' 412 41' 41'

Summary The S hon-Fonn 36 (SF-36) Health Survey is a brief self-administered question­naire that generates scores across 8 dimensions of health. It has been fou nd to be reliable, and valid in tenns of cri teria such as agreement with clinical diagnosis and disease severity, but its underlying values have not been tested against patient preferences.

The SF-36 was not devised for use in economic evaluation. The SF-36 may be used in cost-minimisation analyses. where the dimension scores can be shown to reflect people's values for health at an ordinal level, but it cannot be used in either cost-effectiveness or cost-utility analyses. The dimension scores of zero to 100 do nOI provide a common currency and, where there is confl ict between the dimension scores. there is no basis for establishing an overall health benefit.

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Furthermore. in clinical trials. the usual comparison is between mean or median scores. which assumes ri sk n eutrality and docs not take adequate account of the relat ionship between the value of health and time.

Although Ihey are under pressure to assess the cost effect iveness of health care interventions. researc hers and policy analysts must resist short-cut methods of deri ving a si ngle inde", from the SF-36 that aTC based on arbitrary aggregation sche mes. because these ignore people's preferences and the crucia! quanti tyl quality trade-off, and therefore cannot be used in economic evaluations. However. the rich descriptive material and muhidimensionality of the SF-36 may have potential for use in economic eva luation. Multi-attribute utility theory provides a way of deriving a single index based on elicited values. but it requires a major restructuring of the sc ales of the SF-36. Alternatively. SF-36 rcspon~es may provide material for constructing health scenarios that could then be valued on a holistic basis,

Purchasers of healthcare are bei ng forced to make difficu lt choices. One of the key criterion in ­creasingly used i s cost effectiveness,ll) but this is hindered by the a bsence of evidence on the costs and consequences of health interventions. The last 2 decades have witnessed the growth of what is now known as the 'outcomes movement '12) to promote the measurement of health, and one of its recent nagships has been the Shorl-Form 36 (SF-36) Heahh SurveyP·41 This is a brief and easy to usc self-administered questionnaire. which provides a general assess ment of the patient"s perceived health in terms of 8 dimen sions of heallh covering fu nctioning and well-being. Currently. it is being used in pharmacological and other clin ical trials across many countries and it is likel y that SF-36 data will be used to support claim s for the cost effectiveness of health interventions. In contrast. measures developed by econom ists, such a s the Health Ut ilities Index (HUI),15,61 Quality of Well ­Being Index[7-91 and the EuroQol ,I'OI are not being used as widely in clinical trials.

The aim of th is article is to examine whether SF-36 results can be used in the economic eval ua­tion of healthcare interventions.

1. The Short-Form 36 (SF-36) Health Survey

1.1 Description

The SF-36 is a standardi sed, 36-item question-

naire designed for completion by patients (although it can be interviewer-admin istered) in a cl inic or at home. It measures health on 8 multi-item dimen­sions that cover functional status. well-being and overall evaluation of health (fig. I and table I). For each item. there is a choice of responses on a Li kert scale, ranging (for example) from ' li mited a lot" to 'not li mited at all" or 'all of the time' to 'none of the time' (fig. I). The chosen item responses arc recoded onto an equal interval scale (except for 3 itemsllll). Scores arc computed for each dimension by adding the recoded item responses together and transformi ng the res ul ts onto a scale fro m zero (worst health on sca le) to 100 (best health on scale).III!

1.2 History and Development

The SF-36 has evolved from 2 major research programmes in the US. The fi rst was the Health In surance Experiment (HIE) undertaken by Ihe Rand Corporation to examine the consequences (for costS and health) of alternat ive methods of or­ganis ing the delivery and finance of healthcare.l l21

The original survey contained 108 items, coveri ng a broad array of func tional status and well-being concepts, [131 [n the Medical Ou tcome Survey (MOS ), whic h examined how di ffere nt aspects of healthcare affect outcome, these scales were further developed and refined.l l41 Both of these studies were concerned with developing standardised measures

The SF-36 Health Survey 4Q5

I, The lol lowlng questions are about actlvltes you might do during a typk:al day

Does your health limit you in these activities? It so. how much?. .

Please circle one number on each Une

Yes, Yes, No. not limited a lot limited a little limited at all

Climbing severallf ights of stairs 2 3

Bending. kneet ing, or stooping 2 3

Walking ha~ a m ile 2 3

These questions are about how you feel . how things have been with you during the past mooth.

How mUCh time during the past month:

Please circle one number on each line

All of Most of A good Some of A little of None of

the time th(!time brt of the time the time the time the time

O,d you feel lu ll o f life? 2 3 , 5 6

Have you felt downhearted 2 3 , 5 6

and low?

Has your health limited 2 3 , 6

your SOCial activltes (l ike viSiting friends or close re latives)?

Fig, 1. Samples of questions from the Short-Form 36 (SF-36) Health Survey.l2't

of patient-perceived health, rather than conven­tional measures based on clinical judgement.

Items for the HI E and MOS originated from a review of the literature in the 1970s, and therefore the items selected for inclusion in the SF-36 have their roots in instruments that have exi sted for more than 20 years. ! I~! The usefulness of these fu ll ­length health batteries was seen to be limited by their size, particularly if they were administered along­side disease-specific measures. On the other hand. short single-item scales were not regarded as covering a sufficient range of health domains and

C> "'dis Inter()(]1iona1 Lmiled ...... right. ,e.erved.

have been fou nd to be unreliable and insensitive. particu larly for small groups in trials,! 151 The aim of the SF-36 developers was therefore to create a questionnaire that was " "a standardised health status survey that is com prehensive, psychometri­cally sound. and brief' ,l3J The application of psycho­metric methods in selecting and testing items was an important feature in the development of the SF-36. For econom ists, however, it is important 10 understand the basis of this approach, and its appropriateness in developing an economic mea­sure,

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406 Brinier

Table I. Summary of the 8 Short-Form 36 (SF-36) Health Survey ~ems. and the Hea~h Transrtion rteml" l

Dimension No. 01 items No. of levels

Physical fullClioning " " Role funct;oning - physical ,

Bodily pa in 2 " General heMh 5 " Vitality ,

" Social functioning 2 9

Role functiooing - emotional 3 ,

Menial health 5 26

Reported health lransrtion 5

2. The Psychometric Foundations of the SF-36

There is a well establ ished methodological tra­dition in psychology of measuring s ubjective con­cepts such as intelligence, attitudes and beliefs.116J originally derived from the field of psychophysics, known as psychometrics. The methods of psycho­metrics have been applied widely in health measure­ment!I? ) and were integral to both the construction and testing of the SF-36 dimension scales.l 3.I S.18J

2.1 Reliability

Any measure must be able to consistentl y re­produce a series of results over repeated measure­ments with the minimum amount of random error on an unchanged population. The types of reliabil­ity usually considered are: (i) internal consistency; and (ii) consistency over time ( test-retest reliabi lity).

2 . I. I Infernal Consistency Most published work has exami ned the internal

consistency of the SF-36 in terms of the correlation of items with their own scale. In general. the SF-36 was able to sat isfy the s tandard tests of internal consistency and homogeneity.119.211

C> ... dis Int9mOtiooo1 Umiloo. AI rights 'ew<Voo.

Summary 01 contan!

Extent t o which health limrts physical activities such as seIf-care, walking, climbing stairs, bending, lilting and moderate and vigorous exercise Extent t o which physical health inter!eres with worlt or other claily activrties. including accomplishing less Ihan wanted, limitations in Ihe kind of activities. or ditliculty in performing activities

Intensity of pain and effect 01 pain on normal W{)rlt , both inside

and outside the home

Personal evaluation 01 health. including current health, health outlook and resistance to illness

Feeling energetic and lull of lije versus feeling tired and worn out

Extent to which physical health or emotional problems interfere with normal social activities

Extent to which emotional problems interfere with work or other da ily activ~ies . inctvding decreased time spent on ac~v~ies .

accomplishing less. and not wOl'k ing as carefully as usual

General mental health. inclvding depression. anXiety. behavioural·emotiorlal control and general pos~ive effect

Evaluahon of current health compared to one yea. ago

2. 1.2 rest·/tetest /tel/ability The underlying stability of scores between test

and retest has important implications for required sample size in trials. In a survey of general practice patients. test and 2-week retest scores of the SF-36 dimensions were found to have rank correlations of between 0.60 and 0.81.12 1J which i s withi n the range regarded as acceptable for group comparisons (0.5 to 0.7).1161 The mean differe nces between test and retest did not exceed I point on the 100 point scale. and the plots of these differences against the subjects' scores did not reveal any bias.121 1

2.2 Volidity

Validity has been defined as the extent to which an instrument measures what it is intended to mea­sure. However. as noted by McDowell and NewelJ,l1 7J it is not the instrument per se that is valid . but the way in which it is used. Many measures are origi­nally designed for one task. but subsequently be­come used for a variety of other purposes. The SF-36 has been validated by its abili ty to predict clinical diagnosis and health service ut ilisation. rather than how well it conforms to patients' values, and this is Ihe basis of crit icisms of using it in econom ic evalu ation. This subsection considers

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The SF-36 HC<llth Survey

the psychometric tests of validi ty that have so far been applied to SF-36.

2.2. ' Conlenl validity COnient validi ty i s defi ned as the ex tent t o

wh ich the c hoice of items is appropriate fo r the health domains being measured. Claims for content validity typicall y rest on the comprehensiveness of the domains and the method for generating items.

Health Domains The health domains fo r the SF-36 have been

choscn b y the developers to broadl y refl ect Ihe WHO definition of h ealth as a 'state o f complete ph ysical. mentlll and socilll well -be ing Hnd not merely the absence of disease or infirmity' .122J The 5 dimension s of physical health . me nt al hea lth , everyday funct ioning i n social and role activities, and general perceptions of well -bei ng were origin­ally regarded as 11 min imu m criterion for content validity.t 22 1 Later the role functioning domain was found to miss limitat ions att ributable to mental problems, a nd it was the refore divided into the 2 di mensions of role limitat ions attributable to phys­ical health , a nd those attributable to e mot ional problems. A dimension was also added for vi tality because i ts · ... sensitivity to the impact of disease and treatment has been d emonstrated in recent clinical trials in volving patients with hyperten· sion, prostate d isease, and those di ffe ring in se­verity o f AIDS' .13 1 Pain was regarded as important enough in its own ri ght to also require its own dimension.

Item The original items of the HIE, and subsequently

the MOS survey, were main ly taken fro m existing literature. Items were selected 10 include p osi tive as well as negative aspects of health . Thus. the mental health dimension in the UK version of the SF-36 includes ' have you been a happy person?' as well as 'have you f elt downhearted and low?' ) II J In selecti ng i tems for the SF-36 from the o riginal MOS long fonn, the developers employed a num­ber of strategies that the authors ac knowledged varied across d imens ions. II ~J In the original MOS study. a 20- item shortened version was produced,

407

known as the SF_20.t201 Subsequent analysis of thi s scale revealed a n umber of shortcomings in terms of compre hensiveness and sensitivity compared with the long form. The SF-36 was developed t o correspond more closely wi th equivalent scales in the long form. This ·expert" approach could be cri ticised for not being based d irectly on patient views. but it had the a dvantage of being able to select the best features of ex isting measures. The approach used by some other methodologists. such as the developers of the Nottingham Health Profi le (NHP), is to o btain the statements from i nterviews with palientslBJ and, for the Sickness Impact Profile (SIP), patients and professional s were inte r· viewed.1241

2.2.2 Construct validity Psychometric researchers assess the validi ty of

health measures on correlational evidence, where relat ionships between measures and variables afe hypothesised (·constructs '). and t hen tested empir­ically. The S F-36 has been validated on a w ide range of common cond itions by comparing SF-36 scores with measures of disease severity and other health ind icators.12HII Researchers have found evidence of validity across a range of constructs. including visiting a general practi tioner and attend­ing a hospital-based clinic.ll lJ Furthermore, using thi s a pproach. the S F-36 has been shown to be more sensiti ve than the NHP and the EuroQol classifi­cati on because o f its abil ity to detect l eve ls of perceived ill-health amongst patients who had achieved 'good health ' according to these i nstTU­ments.l2 1.321 These tests of construct v<ll idity can . however. be criticised for thei r dependence on cl in­ical judgement and o ther supply factors. IJ31

2.2.3 ResponJ/veneu The purpose of health status assessment is to

measure health chllnge. Responsiveness is the ability of a n instrument to measure significant changes in health . a nd as such i s a fo rm of validity. However, responsiveness is usually assessed as a statistical characte risti c of an instrument, using meas ures such as effect sizes (I.e. the mean score change di­vided by the standard devialion at baseli ne) and t he standardised responsc mean (mean score change

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divided by its standard deviation), and is linked 10 the sample size required to delect a c hangcJ34J In a reccm SlUdy.(31] the SF·36. another generic measure (the SIP) and several disease-specific measures (including the Arthritics Impact Measure) were ad­ministered pre- and postoperatively to patients under­going IOta! hip arthroplasty. The degree of responsive­ness of the measures was found 10 be comparable. However, there are few data currently published on the responsiveness of the SF-36 in other patient groups.

3. Using SF-36 Scores in Economic Evaluation

Cl inical trials currently in progress will be re­porting changes in scores for the 8 SF-36 dimen­sions alongside other outcomes such as survi val. 10 exami ne whe ther one treatment is more effective than another. There are 3 types of outcomes scenar­ios when 2 treatments, A and B, are compared:

0) The outcomes of treatments A and B are the same for all OUicome measures, including the SF-36 dimensions;

(ii) Some outcomes are e ither better or the same in treatment A compared with treatment B: and

(iii) Some outcomes are better and others are worse for treatment A compared with treatment B,

For the purposes of this discussion, we will assume that SF-36 is a valid description of the health con­sequences of treatment.

The economist, of course. has the addi ti onal problem of relating each of these health outcome scenarios to cost data. using one of the following techniques of economic evaluation in healthcare.(35J

3.1. Cost-Minimisation Analysis

In cost-minimisation analysis it is necessary to demonstrate the ordinal properties of the outcome measures. If this can be shown. scenario (i) wou ld seem to provide the basis for establish ing that the 2 treatments are equally effective, and hence the analysis can focus on costs. In scenario (ii ). if lreat­ment A was s hown to be cheaper than B as well as more effective. again it may be possible to judge cost effectiveness.

8rt1zier

3.2 Cost-Effectiveness Analysis

Where treatment A is more cosIly and more effecti ve than treatment B. then the marginal cost must be weighed against its marginal benefit over B. This can be appraised in cost-effectiveness anal­ysis by comparing costs with a si ngle outcome such as life-years. However, the SF-36 would. in addi­tion. generate 8 cost-per-dimension-score ratios, and it is therefore possi ble for treatment A to be more cost e ffective than B in some d imensions, but less cost effective in others. Th is result would pres­ent considerable difficulties in applyi ng the con­ven tional economic decision ruies.l3S1 Selecting only one dimension would solve the analytical problem but is likely to lead 10 fa lse conclusions about relati ve effectiveness where the interven ­tions have multiple outcomes. Furthermore, SF-36 dimension scores have not been shown to have in­terval properties (Le. where the scores represent equal interval s) and thus the cost-effectiveness ratios are likel y to be meaningless.

Where there is any connict between costs and health outcomes, it is no t possible to apply cost­e ffectiveness analysis using SF-36.

3.3 Cost-Utility AnalYSis

The SF-36 was not designed t o incorporate the preferences of individuals and hence the economist's notion of 'utility'. The developers of the MOS measures adv ised' ... when multiple items arc combined into a score, scores are possible over a range of numbers and the score has no inherent meaning ',(18] Scores on SF-36 dimensions range between zero and 100 but they are not comparable, and there is currently no basis for combin ing them into a single index. There has been work to reduce the number of dimensions using factor analytic techniques, which helps to overcome the statisti­cal problem, but at best thi s reduces the dimen­sions down to 2 or 3(25( and is nOI based on prefer­ences.

In scenario (iii), there can be a connie! between survival and SF-36 scores. An important feature of cost-utility analysis is the combination of survi val

The SF-36 Health Survey

with health-related quality of life to produce qual ity-adjusted life years (QALYs) . SF-36 scores cannot be combined with surv ival on the same scale, and therefore the necessary trade-offs between these 2 types of outcome required in cost-utili ty analysis is not explicitly addressed. Thus, SF-36 results cannot currently be used in cost-utility analysis.

4. Economic Criticisms of the SF-36

The SF-36 currently has only a very limited potential for use in conventional economic evalu­ations. Despite this, many economists will be asked to assess the relative efficiency of different inter­ventions from SF-36 trial data. It is. therefore. worth­while examining these data more critically from an economic perspective.

4.1 Item Selection

There is a danger of ruling out an item simply because it does not fit neatly into one of the hypothesised domains. Some health prob lems. such as limitations in bathing and dressing (an SF-36 physical function ing item), are extremely import­ant to people's quality of life but their infrequency in a population can result in a poorcorretation with other items. Conventional tests of internal consis­tency can therefore reduce the validity of a question­naire. unless applied with care. (The 'bathing and dressing' item was retained in the SF-36 despite this problem.)

4.2 Scoring the SF-36

The interval properties of SF-36 scales as meas­ures of patient values have not been tested. It is assumed that being limited in 2 items equals twice the interval ofa single limitation. Even the ordinal­ity of the dimension scores may be in some doubt. For example, physical funct ioni ng incl udes items for 'lifting and carrying groceries' and 'bending, kneeling or stooping ', which are assumed to be equal, but one could be regarded as far worse than the other by many patients. The econom ist would want to test the implicit weights investigated

CI Adtl lnt",rnolior><>l UrY"Wtad. AI right> re-servOO.

against the value of these limitations to patients. society o r whoever's values are deemed relevant. (In contrast, the developers of the SF-36 have been more concerned with the statistical assumptions underlying these scoring procedures. includi ng 'the distribution of responses to items within the same scale and item variances are rough ly equal· .I 1SI)

A test of validity used by economists is to examine whether the scores correspond to values revealed in the choices made by patients.l 281 For example, whether an informed patient would actually choose the treatment that results in a higher SF-36 score, and whether the strength of this preference correlates strongly with the SF-36 scores. However, these 'revealed preferences' of patients in healthcare tend 10 be contaminated by their outcomes and the influence of professionals. At best, it might be pos­sible to test the ordinality of some scores, but it is not likely 10 provide a usable technique for testing the strength of the values underlying the dimension scores. For this, stated preference techniques have been applied. such as the rating scale used by Cairns and colleagues.l361 They have attempted to compare the implicit values of 3 condition-specific measures of health with stated preferences. Patients were asked to rank and rate a sample of scenarios describ­ing hypothetical patients drawn from these scales. Disagreement was found between the ran kings derived from the origi nal scales and the raters ' stated preferences, and the scales did not appear 10 have simple interval properties. The authors con­cluded that a large number of scenarios would have to be valued to estimate any relationshi p between the scales, and that it may be necessary to revalue them completely.

4.3 Risk

Health statu s measures such as the SF-36 can be critici sed for their failure to take account of risk. Analyses of trial results typically focus on the mean, or occasionally median, change in health scores. Variance in the data is used to establish the statistical significance of a change, but the impli­cations of the distribution of these changes fo r

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'10

risk-taking are ignored. A very wide range of out­comes has been found for common treatments such as cholecystectomy, with negative consequences from complications including mortality. The rank­ing of utility expected from a prospect such as a surgical trcalmen! is not necessarily the same as its mean value. For a risk-averse person, uncertainly reduces the util ity of a mean outcome or prospect. and the maximisation of utility may involve choosing a Ireatment that achieves a lower improve­ment in the SF-36 scores, but with less variance. T he distributioll of hcahh outcomes should not be ignored when comparing the effectiveness o[lreal­mcnts. However, there is no agreed method for incorporating risk into the valuation of health out­come. Expected utility theory (EUT) is usually claimed to be the theoretical basis of economic val­uation techniques such as standard gamble, but the assumptions of EUT have been heavily criticised on empirical grounds.lJ7J Even with in the paradigm of EUT, there is no agreement on how risk should be incorporated p g·39]

4.4 Time

In clinical trials, the frequency and length of follow-up is often inadequate to obtain an accurate description of the duration and pattern of health gai n. In the simplest trial design, the outcome of a treatment is the difference between heal th scores assessed before and after treatment. A more sophis­ticated approach is to estimate the health change for every patient as the difference between the pre­treatment scores and a weighted average of scores at the post-treatment assessment, with the weights proportional to the time spent between each assess­ment.140)

The method of weighting scores by durat ion as­sumes the value of a health state is independen t of when it occurs, the length of time a patient is in the state, and where it occurs in relat ion to other health states. Usually in economic evaluation a con­stant posit ive rate of time preference is assumed a nd d iscounting is recommended when analysi ng QALYs.l411 However, it has been suggested that peop le's time preferences have a more complex

o Adis Inlernohonol lJmjled. All fights feseN{j(j.

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pattern, which may be linked with 'thresholds' in a person's life cycleP7 J For example, health may be more important to a person when they have young children. The length of time endured in a health state can also be important. Sackett and Torrance(42) asked patients and members of the general popula­tion to value a variety of health states, including hospital dialysis. for durations of 3 months, 8 years and life, and found the mean daily health state util ities declined with duration. More generally, Richardson and colleagues[43[ have argued that the utility of a health state may be directly related 10 a person's prognosis: 'A poor health state may be more tolerable if it is perceived as a temporary hardship to be endured to obtain subsequent healt h. Conversely, the enjoyment of an otherwise satisfactory healt h state may be dimin ished by the knowledge that it will end in suffering and death', Simi larly, it can be argued that a person adjusts to a health problem and that th is alleviates its conse­quences.

The importance of the context of a health state is someth ing that could be missed by a narrowly defined measure of health focusing on disability or pain. However, the SF-36 is a more broadly based measure, and may be able to describe the conse­quences of duration and prognosis. In the second example of Richardson and colleagues,[43[ a person who has cancer and is very depressed about the prognosis would respond accordingly 10 items on the SF·36 Health Survey.

5. The SF-36 and Preference-Based Measures

An alternative approach used by many econo­mists is to employ preference measures such as standard gamble or time trade-off in clinical trials to obtain a single index value for each patient's health state. These elicitation procedures have been developed from theories of choice to obtai n uti li ty scores for different states of health, and a llow health-related quality of life to be combined with survival to generate a single index number from zero (death) to I (full health), such as the QAL yt441

Phormocol'c onomk;s 7 (5) I~

The SF·36 Health Survey

A recent review of studies containing both health status and preference measures fou nd them to be poorl y or moderately correlated (r = 0.01 to 0.60), and health status scores were on ly able to predict 18 to 43% of 'utility' scores in regression mode ls.l4S1 The direct assessment o f preferences in clinical trial s is likely to be innuenced by a range of facto rs o ther than the patient's health status, such as attitudes to risk and time, degree of under­standing the valuation task, and the palient's circum­stances.l-l6l These other factors may be regarded as contaminants, but some of them, such as attitudes to ri sk and time, should be included in the valuation of the benefit s of most heaJthcare. In their review of these 2 approaches, Revicki and Kaplanl4SJ advo­cate the use of both, but in practice this may not be feasible and would present a dilemma where the results do not agree.

Economic measures have not been found to be as responsive as general health status measures. A recently published comparison by Katz and col­leaguesl471 of measures used on patients undergo­ing hip arthroplasty found' ... the utility measure [time trade -ofll is less responsive to clinical change than the SIP, and the quality of life rating scale [the 'feeling themlometer' I is the least responsive of all three measures'. The Canadian Erythropoietin Study G roupl48] found significant differences be­tween the experimemal and placebo gro ups in di­mensions of a di sease· spec ific (Kidney Disease Questionnairc) and a generic profile (S IP) measure, but not the time trade-off at 6 months after treat­ment.1481 Direct utility assessment in trials wou ld seem to require larger sample sizes than measures of health status, particularly where the expected differences are small.

In practice, direct preference assessment is comparatively rare, a fact that may be attributable to resistance from clinical researchers concerned about the distress to patients from valuation exercises that incorporate life and death choices. An alter­nati ve approach pioneered by Kaplan and Bushl91

and by Torrancels.61 has been to combine these ap­proaches by estimating weights using preference­based methods for the items and dimensio ns of

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the health statuS instrument. to generate a single index measure of health (e.g. QALYs).

6, Deriving c Single Index from SF·36

To use SF-36 in economic evaluation it will be necessary to deri ve a single index measure that reflects the strength of people's prefe rences fo r different aspects of health. The fo llowing discus­sion considers how such an index might be de· rived.

6.1 Arbitrary Weights

One approach is simply 10 combine the dimen­sion scores o r item responses into a si ngle index using an assumed set of weights. A research team at Brunei University in the UK aggregated the NHP into a single index to estimate the QALYs gained from a heart transplantation programme.l491 Three methods of aggregation were utilised: (i) the pro­portion of affirmative responses to the 38 state­ments in the NHP; Oi) weighting the affirmative responses by weights estimated by the NHP de­velopers. u sing Thurstone 's method of paired com­parisons;f231 and (i ii ) using unitary statement weights within dimen sion s and then weighting the dime nsions by their proportion of the 38 Slate­ments. Similar results were obtained wi th each method of aggregation, although the range of val­ues examined was very limited and other weight· ing schemes may have led to different results.

Two of the devisors of the NHP. who originally argued against deriving a single index from their profile measure, have recently published a method for obtaining an index of di stress to be used in con­junc tion with another measure of dependency in cost-utili ty studies.l$()l Their index contains 23 out of the original 38 statements in the NHP (since it excludes mobility) but otherwise is the same as BruneI's fi rs t aggregation scheme.

A wide range of aggregation schemes could be applied to the SF·36, involving the summing of dimension scores or items responses, using differ­ent assumed weights. The easiest method would be to weight the dimension scores as follows:

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412

(Eq. I )

where: Kj = the dimension weight applied to dimension) : n = the number of dimensions: Xj = the dimension score of dimensio n) ; and:

Lj~I Kj = 1

Such arbit rary weighting schemes cou ld easily be applied to the results of a trial, bUI they would not generate an index that could be legit imately used in an economic evaluation , because the dimen­sion scores are not measures of uti lily and have not been based on people's preferences. Funhcnnorc, there is no allowance fo r any possible interaction between the dimensions. The consequences of having pain and limitations in physical funct ioning may be more. or indeed less. than the sum of the 2 separate dimensions. Finally. for use in cost-utili ty analysis. the index would have 10 becombincd with surv ival. something O ' Bricn and colleagues did not feel able to ach icve with the N HP.I4Jr The Brunei team argued that 'a more forma l process is required for translating health IJroji/e information, be it from the NHP or S IP with their richness and multi-dimensionality, in to relative 1'O/lllIlions of typical health statcs. which can then be used 10 in­dicatc relative quantity/quality of life trade-offs or preferences' .

The wcights could be based on the strength of association of items or dimension scores with events such as survival or usc of health services. Aside from the statistical problems. again the main objec­tion 10 this is the absence o f values derived from patients.

6.2 Multi-Attribute Utility Theory

An alternative approach is to value all the health states defined b y the SF·36 - that is , every con­ceivable combination of responses to the question­naire using preference-based techniques. The SF-36 is a complex multidimensional scale that defines more than I million possible states, presenting a formidab le va luation task. Torrance and col-

Bra~ ier

leaguest6.S11 have pioneered an approach to val ua­tion using multi-attribute utility theory (MAUT) from the operational research li terature . By making a number of assumpt ion s about the form ofa utility or value function it is sufficient to value a small sample of poss ible slales. This function can then be used to e stimate values fo r all possible states. An example of such a func ti on is the addi tive model as follows:

(Eq.2)

where:

Xj; represents levc l i (i = 1 to 111 levels) on att ribute j: and U(Xj;) is the utilit y associated with leve l ion attri­butej.

This is similar to equation 1. but the arbit rary weights Kj are now replaced by the utility valucs associated wi th each attribute. This requires each attribute 10 be additively independent of all other attributes. and therefore docs not allow for any inter­action between attributes. Us ing this approach, the utility funct ion for eac h attribulecan bedetermined separately by asking respondents to value health states where the levels o f only I dimension arc varied at a time.

More complex equat ions can be used, which make less stringent assumptions about the fonn of the relationship between the dimensions than addi­tive independcnce.ls2J For example, they can include terms for possible interaction between 2 or more attributes. In the MAUT literature, there are exam­ples of multilinear and multipliclltive fUllctiolllll forms. However. increasing the compl exity of the mode ls can make them far more difficu lt 10 esti ­mate and difficult to interpret. Greater complexi ty must bejustified by a significant gain in the modcl, such as improvements in predictive power. Which­ever model is used, it will be necessary to test its assumptions.

MAUT is a powerful techn ique that co uld pro­vide a p ractical method fo r deriving a single index from the SF-36. However, existing instrumenls us­ing MAUT, such as the HSJ and EuroQol. have fewe r dimension items than the SF-36. The HUI

","lOll I iOCOEC(In()ITIicf 7 (~) 1995

The SF-36 Health Survey

(Mark I) developed by Torrance and assoc iates defined 960 health states.161 and the EuroQol (ver­sion 2) a modest 243.1101 Furthermore. the items within each dimension have a clear ordinal relation­ship. which substantially simplifies the mathemat­ical modelling. Many items in the SF-36 do not have an obv ious ordinal relationship with in each dimension. and there is another layer of complex­ity in that most items have more than 2 responses. Consequently, MAUT cannot easily be applied to the current structure of the SF-36.

One way forward that is being explored by a team of researchers in Sheffield has been to both reduce the size of the SF-36. and to simplify its structure into sets of ranked items or attribute lev­els.l53J The first version has 6 dimensions. and be­tween 2 and 6 levels. A sample of states defined by thi s scale has been valued by groups of pat ients and professionals using standard gamble and rating scales. The study aims to determine whether a pro­fi le measure such as the SF-36. with its rich de­scri ptive material. can be translated into an index for estimating QALYs.l541

6.3 Scenario Approaches

Under the MAUT approach, a single index is derived for each state from zero (death) to I (per­fec t health), and this is multiplied by survival to obtain a total number of QALYs. The QALY meth­odology has been criticised in the literature for ig­noring the effects of duration and overall prognosis on the patient's valuation of a health state (see section 4.4). Gafni and associatesl3~1 at McMaster Un iversity have argued that equation 2 cannot be regarded as representing a utility function. In it s place. Ihey advocate a 2-stage algorithm for valuing a health stale where the duration ofa slate is treated as a variable. Gafni and colleaguesl381 also argue that their method of val uation is a superior tech­nique for measuring utility to standard gamble and time trade-off. but these arguments extend beyond the scope of this article. This approach has not, however, been used widely because it substantially increases the valuat ion task. particularly if the sce­narios arc to be linked accurately 10 the wide range

413

of outcomes found for many common procedures in clinical trials. 1401 A simpler approach has been proposed by Hall and colleagueslSSI where specific 'vignettes' or health scenarios arc valued. using a single valuation procedure.

The SF-36 could be used to generate these sce­narios directly from trial evidence, assuming it was shown to be sufficiently comprehensive fo r the condition bei ng studied. II would be a major re­search task, since it would not benefit from the short-cut offered by MAUT, but would provide an important opportunity to test the additional as­sumptions of MAUT.

7. Conclusion

The SF-36 has not been designed for use in economic evaluation. It may be used in cost ­minimisation analysis, provided the scales can be demonstrated to reflect people's ordinal preferences. However. it cannot be used in cost-effectiveness or cost-utility analysis, and any attempt to assess cost effectiveness in less formal ways using SF-36 data must be viewed with caut ion . A single index deriv ed from SF-36 us ing arbitrary aggregate procedures would not be appropriate for use in eco­nomic evaluation. SF-36 data could be more useful in economic evaluation if it was feasible to derive a single index based on explic it valuation tech­niques. MAUT may provide one approach, but it requires a major modification of the struct ure and size of the existing SF-36. FUl1hennore. this approach requires a number of assumptions about the form of a utility funct ion that must be tested. Were s uch research success fu l. it would add consi derable value to SF-36 as a research tool.

Acknowledgements

The author would like 10 thank Rosemary Harper and olher members of the Sheffield SF-36 team. and Ihe referees for Iheir perceptive commenls on earlier drafts of Ihis paper. The aUlhor's post is supported by Trent Health.

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Correspondence and reprints: fohl! Bmzi", Senior Lecturer in Heallh Economics, Sheffield Centre for Health and Related Research, Universi ty of Sheffield, Regent Cou rt, JO Regent Street, Sheffield SI 4DA, England.