relationship between psychometric and utility based...

Quality qflL!fe Research 2, pp. 477-487

Relationship between psychometric andutility-based approaches to the measurement ofhealth-related quality of life

D. A. Revicki* and R. M. KaplanBattelle Medical TechnologyAssessment and Policy Research Center,901 D Street,SW, Washington, DC 20024 (D. A. Revicki). Division of Health Care Sciences,Departmentof Family and Preventive Medicine, School of Medicine, UniversityofCalifornia, San Diego, La Jolta, CA, USA (R. M. Kaplan).

This paper summarizes selectedevidence pertaining deficiency syndrome (AIDS), and other chronicto the relationship between psychometric health diseases, z Generic and disease specific healthstatus measures and utilitypreference measures of status measures are increasingly incorporated inhealth outcome. Few studies contain measures ofboth health status and utility/preference. The avid- randomized clinical trials of new medical treat-ence to date suggests that various health status merits and other medical outcomes studies. 2'3Thismeasuresare at best only moderatelycorrelated with paper discusses the advantages and disadvantagesstandard gamble (SG) and time trade-off (TTO) utili- associated with psychometric health status andties. Resultsfrom regressionanalysis, predictingSG utility/preference measures in health-related re-or TTO utilities from combinations of health statussca_es,typically have an R2 of 0.18 to 0.43. Prefer- search and summarizes selected studies on theantes determined by rating scale methods are more relationship between psychometric health statusstrongly related to health status scores, but ¢orrela- and utility/preference measures.tions are variable rangingfrom 0.17 to 0.46 and only Despite increasing consensus about the concep-about 27% to 34% of variance can be explained in tualization of HRQL, 2'4-6 alternatives exist in theregression models. The Quality of Well-Being Scaleand other multiattribute preference measures have operationalization and measurement of these con-low to moderate correlations with health status cepts. Two main approaches are used to evaluatemeasures (r = 0.03 to 0.71). Health utility/preference generic health status outcomes, psychometricmeasuresand psychometric health status scoresare health status and utility/preference measurement.only moderatelycorrelated.Health utility and psycho- Many advances have been made over the previousmetric health status scales may measure differentattributes of health, Although both approaches are 30 years, in the development of health statususeful for evaluating medical outcomes, they are not measures 2'3's'6 arid in the assessment of patientinterchangeable indicators of health-related quality of preferences and utility. _'7-14 Nonetheless, pro-life. portents of different measurement technologies

Key words: Utility measurement,psychometric methods, have failed to demonstrate an), clear superiorly" inhealth status assessment, preference measurement, evaluating medical interventions. There are trade-health-relatedqualityof life. offs in the assessment of health outcomes and no

single approach can be made to fit the objectives ofall studies. 6

Introduction

Health-related quality of life (HRQL) is viewed by Psychometric health statuspatients, clinicians, and society as an important assessmentoutcome of medical technology and disease control

and prevention programmes. HRQL assessment is Psychometric approaches to measuring HRQLoften considered a necessary component in the require the respondent to indicate the presence,evaluation of pharmaceutical treatments for hyper- frequency,, or intensity of symptoms, behaviours,tension, depression, cancer, acquired immuno- capabilities or feelings. Responses to individual

questions are aggregated to create individual ho-* To whomcorrespondenceshouldbe addressed mogeneous scales (e.g., physical function, sociaJ

© I993 Rapid Communfcations of Oxford Ltd Quality qfLJ/e Research . _.'ol2 . 2993 477

D. A. Revicki and R. M. Kaplan

function, mental health) or global summary scales. Utilities are numbers that represent the strength ofPsychometrically sound health status scales have an individual's preferences for different healthbeen successfully used to assess the outcomes of outcomes under conditions of uncertainty. 7'12'14'2_medical and surgical treatment and to compare Preferences are the values people assign to differ-patient outcomes under different systems of ent health outcomes when uncertainty is not acare, 2'3'1_Health status measures have been used condition of measurement. These numbers reflect

to discriminate among individuals with different a person's level of subjective satisfaction, distress,chronic diseases at a single point in time, predict or desirability associated with different healthfuture health outcomes, and to measure change conditions. 8 The utility approach uses one or moreover time.1_ scaling methods to assign numericalvalues (utili-

Generic measures cover a broad range of func- ties or preferences) on a scale from 0 (anchored astioning, disability and distress.l: These scales can death) to I (anchored as complete health).be applied across a range of different populations The utility scores reflect preferences for theand may be used to examine the impact of medical health states and allow morbidity and mortalitytreatment targeted at a range of different illnesses improvements to be combined into a singleand medical conditions. The strengths of generic weighted measure, qualiD'-adjusted life years, lz2_instruments include their often established relia- Standard gamble (SG), or lottery, procedures arebilitv and validity, the possibility of detecting used to generate utilities. Preferences can betreatment effects across a broad range of health generated by patients, clinicians, or the generaldimensions, and that they enable the comparison population using visual analogue rating scalesof outcomes across a range of different inter- (RS), time trade-off(TTO), multiattribute scales, orventions, conditions and populations. Generic other scaling methods. 8'9'12'14'21instruments mav not be as responsive to changes Either decomposed or holistic approaches can bein clinical status compared to specific measures, used to elicit health utilities. In the decomposedand they may not always focus on the most critical approach, patients are asked a series of questionshealth outcomes of interest. Despite the high face about their functioning in specific health domains.validity of disease specific measures, the literature Based on their responses, individuals are assigneddoes not uniformly support their greater sensi- to one of several categories and each of thesetivitv. _s categories has an associated utilit'v score. The

Ciinicians are sometimes concerned about the weights and utilities are developed from previousvalidity and importance of self-rated health, often ratings bv samples from the general population,preferring physiological and biomedical outcomes, clinicians or some other reference group. ForThey are sometimes uncertain about the respons- example, the Health Utility Index 14'24 and theiveness of these measures to small, clinically Quality of Well-Being Scale (QWB) 13,xs use ameaningful changes, and have difficult3' trans- decomposed approach to generate preferences. 'lating changes in scores in clinically meaningful In fact, the QWB and the Health Utility Indexways. 19'20There are concerns that most health represent hybrids of psychometric and utility-status scales do not incorporate mortality, duration based measures. However, there are differences inof survival, or patient preferences for health care how utility/preference scores are generated by theor outcomes. 7'13A4'21Health status measures are two scales. Measures like the QWB obtain informa-

responsive to clinically meaningful differences in tion about multidimensional health states and thenclinical symptoms and status in groups of patients use separate utility weights to combine them. Theexperiencing mild to severe disability. For exam- Health Utility Index requires respondents to rateple, a number of studies have demonstrated the their own health status using a multiattributediscriminant ability and clinical responsiveness of health status classification. The QWB uses a set ofthe General Well-Being Adjustment Scale. 22'23 utility weights that were previously estimated on

the basis of population surveys to convert a healthstatus measure into a preference/utility score. -"6

Health utility/preference The holistic method uses hypothetical healthassessment state scenarios or descriptions as stimuli to get

individuals to assign utilities to different healthUtility theory and measurement were developed, outcomes. These scenarios include several briefin part, as a normative model for individual statements that describe important aspects of thedecision making under conditions of uncertainty, health condition in terms of physical, psycholo-

478 QualityofLzfeResearch• Vo12• t993

Psychometric and utility-based approaches

gical and social functioning, pain, and sometimes, functional status scales in a randomized clinicalmedical treatment. It is also possible to use this trial comparing auranofin therapy to placebo inapproach to obtain ratings of the person's current patients with rheumatoid arthritis. Clinical out-health condition. Visual analogue, SG or TTO come measures were combined with functionalscaling procedures are most often used to obtain health status, pain, depression, health perceptionutilities or preferences using holistic health states, and health utility measures to evaluate the treat-These scaling methods involve presenting multiple ment over a 6 month period. The authors reportedstandardized health state descriptions to indi- that auranofin was superior to placebo on aviduals and eliciting directly or indirectly the number of clinical indicators, activities of dailyrelative preferences for each health state. The living, QWB, range of motion and pain assess-purpose of utility scores is to represent health ments. No differences were found on measures ofstatus and to estimate the value of this health state depression or general health perceptions. Differ-to a person. For example, a utility score of 0.50 on a ences favouring the active treatment were found0 to 1.0 scale values the health state as equidistant on the Patient Utility Measurement Set, a measurebetween death and optimum health, of the patient's perception of his or her current

The utility/'preference approach has several ad- state of health relative to his or her state of healthvantages compared to the psychometric method, before treatment and relative to perfect health.First, it incorporates time and risk preferences for Standard and modified time trade-off and lotte D'different health-state outcomes into the measure- procedures were also used to elicit the patientment process and the scores are easily incorpor- utility values. The evaluation of HRQL contributedated in an economic analvsis. 7 Utility/preference to an understanding of the effect of the therapy onassessment has been successfully incorporated a broad range of outcomes important to the.... 71327-30into a number of chnlcal trials. ' • There is, rheumatoid arthritis patient. Unfortunately,, Bum-however, some controversy regarding the defini- bardier et al 29 did not report on the relationshipst-ion of utilities/'preferences and the methods used among the different preference and health statusto derive these values. 31 Utilities/preferences for measures.some health states vary widely among individualsand by the structure and content of health-statedescriptions, how duration of the health state is M@lhOd$incorporated into the measurement, the way out-comes are framed, and the different scaling The health status and utility/preference literaturemethods. 12'2° Other disadvantages include the was searched using Medline to identif'v studiescognitive complexity of the measurement task, published between January 1985 and March 1993imprecision of individual values, potential popula- which included both psychometric and utility ortion and contextual effects on utility values, and preference measures. Articles were retained if: (1)the interpretation of the scores. 7'10'12'_°'31'32 HRQL or health status scales were administered;

Utilities and preferences may not be sensitive to (2) health utilit)" or preference measures wererelatively small yet clinically meaningful changes administered; and (3) the relationship betweenin clinical status. Sometimes utility' based health status and utility/preference measures wasmeasures fail to detect differences that are cap- reported as correlations or using multiple regres-tured by traditional clinical indicators or psycho- sion analysis. In addition, recent presentationsmetric health status measures. Some clinicians and unpublished reports were solicited from in-believe that utilities or preferences mav not be vestigators active in this area of research. A total ofsensitive enough to detect these relatively small 15 studies were identified and are included in thisbut clinically meaningful changes in clinical status, review.On the other hand, advocates of utility basedmeasures argue that differences that cannot beperceived by human judges may be too small to be Characteristics of studiesclinically meaningful.

Only a limited number of studies have incorpor- Table 1 summarizes characteristics of the studiesated both psychometric health status and utility which include both health status and utility;prefer-assessments into evaluations of medical techno- ence measures. A wide range of different popula-

logv. In one of the earliest studies, Bombardier et tions have been studied including generalal._'9 used a number of clinical, health utility and community samples, 33-35 and patients with

Quality qfL!fe Research • Vol 2 . 1993 479


Table 1. Characteristics of studies with both health status and utility/preference measures

Study Population Health status measures Utility/preferencemeasures

Liang etal. (1985) Arthritis (n = 50) AIMS, FSI, HAQ, SIP QWBRead etal. (1987) Hypertension (n = 400) SIP, GHRI, MHI, EGFP QWBChurchill eta/. (1987) End stage renal disease (n = 108) Spitzer Quality of Life Index, HIE TTO

Physical, Social and Mental HealthIndex

Kaplan etal. (1989) Arthritis (n = 83) AIMS QWBWu eta/. (1990) AIDS/ARC (n = 31 ) Karnofsky QWBTsevat et al. (1991) Survivors of MI (n = 80) Karnofsky, SAS RS, TTOLaupacis etal. (1991) End stage renal disease (n = 118) SIP, KDQ TTONichol eta/. (t992) Angina (n = 41) CCSS, DASI SGRevicki (1992) Chronic renal disease SIP home management, RS, SG

(n = 73) alertness, social activity, MOSenergy, physical function, healthdistress, CESD, life satisfaction,sexual dysfunction

Tsevat eta/. (1992) HIV+ (n = 137), primary care SF-36, MHI T-I'Opatients (n = 117)

Fryback eta/. (1992) General Population SF-36, EVGFP TTO, QWB(n = 1356)

Revic_i et al. (1992) Hypertension (n = 180) SF-36, MOS cognitive function, RS, SGsleep function, sexual function,health distress, GWB

F"yback eta/. (1993) General Population SF-36 General health TTO, QWB(n = 1356) perceptions, EVGFP

Braz:er eta/. (1993) General population SFo36 EQ(n = 1582)

Hughes (1993) HIV+ (n = 100) MOS SF-34 QWB

RS = rating scale; "]'TO = time trade-off; SG = standard gamble; QWB = quality of well-being index; EQ = EuroQol;AIMS = Arthritis Impact Measurement Scale; FSl = Functional Status Index; HAQ = Health Assessment Questionnaire;SIP = S_ckrqess Impact Profile; GHRI = General Health Rating Index; MHI = Mental Health Index; EGFP = self-ratedhealth (excellent, good, fair, poor); MOS = Medical Outcomes Study; SF-36 = MOS short form 36; CESD = Center forEpidemiological Studies Depression Scale; EVGFP = self-rated health (excellent, very good, good, fair, poor);SAS = Specific Activity Scale; KDQ = Kidney Disease Questionnaire; GWB = General Well-Being Adjustment Scale;CCSS = Canadian Cardiovascular Society Scale; DASl = Duke Activity Specific Index; HIE = Health InsuranceExperiment.

hypertension, 36'37 chronic renal disease, 19'27'28'38 very good, good, fair or poor (EVGFP). The moreHIV-related disease, 3°'39'4° arthritis, _3'29'41 breast recent studies use the SF-36, or some variant of the

cancer 42 and cardiovascular disease. 43'44 Sample Medical Outcomes Study (MOS) questionnairessizes range from 31 to 1582, with most (67%) under as the measure of psychometric health

200. Most frequently, the QWB (47%) or TTO status. 28"34'35_37'39'40

(40%) approaches were used to measure prefer-ences. Only two studies examined the relationship

between standard gamble and psychometric Relationship between health status andhealth status measures. 2°'37'44 preferencemeasures

A vadetv of health status scales have been

included in these studies including the Sickness The relationship between psychometric health

Impact Profile (SIP), Medical Outcomes Study status and the utility/preference measures areshort-form 36 (SF-36), General Health Rating In- reported by preference measurement method.

dex, Spitzer Quality of Life Index, Karnofsky Table 2 summarizes the correlations and squared

Scale, and the Specific Activity Scale. The Beaver multiple correlations found in each study. Table 3Dam Study 3435 also includes a single-item measure contains findings of studies reporting multivariate

of health, rating self-reportedhealth as excellent, analyses.

480 Ql_alityofLl[eResearch• Vol2 • 1993


Table 2. Findings from selected studies with both health status and utility/preference measures

Study Health Utility/preference measurestatusmeasure RS SG TTO QWB Other

Liang eta/. AIMS - - - r = 0.62 -(1985) FSI r = 0.50

HAQ r = 0.60SIP r = 0.59

Read etal. SIP - - - r = 0.55 -(1987) GHRI r = 0.46

MHI r = 0.33EGFP r = 0.71

Churchill et al. Spitzer QOL Index - - r = 43 - -(1987) Rand HIE NR

Kaplan etal. AIMS Physical - - - r = -0.57 -(1989) AIMS Pain r = -0.40

AIMS Psychological r = -0.17

Wu et al. Karnofsky - - - r = 0.44 -

(1990)Tsevat et al. Karnofsky r = 0.40 - r = 0.27 - -(1991) SAS r = - 0.35 r = -0.03

Laupacis eta/. SIP - - r = -0.15--0.23 - -(1991 ) KDQ r = 0.35-0.49Nichol et al. CCSS - r = 0.40 - - -(1992) DASI r = 0.42Revicki SIP r = 0.17-0.35 r = 0.07-0.30 - - -(1992) SF-36 R2 = 0.27 R2 = 0.25

Tsevat etal. SF-36 - - r = 0.25-0.06 - -(t992) MHI r = 0.28-0.42

R 2 = 0.35-0.43

Fryback etal. SF-36 r = 0.15-0.43 r = 0.17-0.69(1992) - - R2 = 0.25 R2 = 0.56 -Revicki etal. SF-36 r = 0.20-0.43 r = 0.01-0.20 - - -(1992) GWB R2 = 0.33-0.34 R2 = 0.18-0.25

Fryback et al. General health(1993) perceptions - - r = 0.39 r = 0.52 -

EGVFP r = 0,34 r = 0.47

Brazier et al. SF-36 .... r = 0.48-0.60(1993)

Hughes (1993) SF-34 - - - r = 0.23-0.64 -

RS = rating scale; TTO = time trade-off; SG = standard gamble; QWB = quality of well-being index; EQ = EuroQot;AIMS = Arthritis Impact Measurement Scale; FSI = Functional Status Index; HAQ = Health Assessment Questionnaire;SIP = Sickness Impact Profile; GHRI = General Health Rating Index; MHI = Mental Health Index; EGFP = self-ratedhealth (excellent, good, fair, poor); MOS = Medical Outcomes Study; SF-36 = MOS short form 36; CESD = Center forEpidemiological Studies Depression Scale; EVGFP= self-rated health (excellent, very good, good, fair, poor):SAS = Specific Activity Scale; KDQ = Kidney Disease Questionnaire; GWB = General Well-Being Adjustment Scale;CCSS = Canadian Cardiovascular Society Scale; DASI = Duke Activity Specific Index; HIE = Health InsuranceExperiment.

Rating scale. Revicki, 2° Revicki et a1.37 and Tsevat values and related these measures to health statuset al. "_3examined the association between rating scores (i.e., Duke-University of North Carolina

scale (RS) preferences and various measures of Health Profile). Correlations between the holisticfunctioning and well-being. Llewellyn-Thomas et and decomposed assessments of emotional well-

ai.42 explored the relationship between holistic and being and mobility were poorly correlated with

decomposed approaches to measuring health comparable health status dimensions (r = 0.05 to

Quality qfLife Research• Vol2 . 1993 481


Table3. Summary of studies predicting utilities/prefer- In summary, RS preferences and health statusences using healthstatus measures scores are correlated 0.17 to 0.46. From 3% to 21%

of the variance in RS scores can be predicted byStudy Utility/preference* individual health status measures. Regression ana-

RS TTO SG ivses suggest that combinations of health statusscores can account for 27% to 34% in RS values.

Tsevat et al. (1992) - 0.35-0.43 -Frybacketal. (1992) - 0.25Revicki(1992) 0.27 - 0.25Revicki eta/. (1992) 0.33-0.34 - 0.18-0.25 Time trade-off. Studies bv Churchill et al. 38Tsevat

et al. 43 Tsevat et ai.39 and Fryback et aI. 34'35used* R2 from regressionmodels predicting utility/preference TTO techniques to assess preferences. Churchill etmeasureusingcombinationsof health statusmeasures, ai.38 in a study of end-stage renal disease (ESRD)RS = rating scale; T'TO= time trade-off; SG = standard patients on home or hospital haemodialysis orgamble, who receivedkidney transplants, found that TTO

" scores were correlated 0.43 with Spitzer Quality of0.20). Tsevat et al. 43 in a study of 80 survivors of Life Index scores. Although the exact correlationsmyocardial infarction, used a 10 cm visual an- are not reported, the authors indicate that TTOalogue scale, anchored at death (0) and perfect scores were more closely related to Rand Healthhealth (1), and a verbal RS anchored at death (0) Insurance Experiment (HIE) physical functionand perfect health (100) to measure preferences for scale scores than social function or tnental healththeir current health condition. The two RS were scale scores.

correlated 0.93. They found that a visual analogue A randomized trial of erythropoietin treatmentRS was correlated 6.44 with the Karnofsky Scale for anaemia in ESRD incorporated TTO, the SIP,and -0.34 with the Specific Activity Scale. The and the Kidney Disease Questionnaire (KDQ). 27Averbal RS was correlated 0.46 with Karnofskv Scale total of 118 patients received either a placebo orscores and -0.35 with Specific Activity Scale r-HuEPO treatment and were followed for 6scores, months. Compared to the placebo group, ervthro-

Rev_cki2° found that the RS was significantly poietin treated patients demonstrated significantcorrelated with SF-36 energy (r = 0.33), SF-36 improvements in measures of fatigue, physicalphysical function (r = 0.25), SIP home manage- symptoms, social relationships and depression onment (r = -0.35), alertness behaviour (r = -0.24) the KDQ and SIP total physical scores. No differ-and social activities (r =-0.29), life satisfaction ences between the treated and placebo groups(r = -0.34), and Center for Epidemiologic Studies were detected using the TTO measure. Laupacis etDepression (r = -0.23). A regression model in- al. 45reported that TTO scores were correlated 0.35cluding all these health status measures explained to 0.49 with KDQ scales and -0.15 to -0.23 with27% of the variance in RS values. SIP aggregate scores. KDQ depression (r = 0.49)

A more recent study by Revicki et ai.37 examined and fatigue scores (r = 0.48) showed the largestthe relationship between SF-36 scales, General correlations with TTO scores.Well-Being (GWB) Adjustment Scale, selected Tsevat et al.43 compared TTO scores with Kar-physical symptoms, RS preferences, and SG utili- nofsky and Specific Activity Scale scores in aties in 180 patients with hypertension recruited sample of 80 survivors of myocardial infractionfrom a large work-place hypertension screening (MI). Karnofsky scores were correlated 0.27 withand treatment programme. All of the GWB and TTO scores. Specific Activity Scale scores were notSF-36 scores were moderately correlated with RS associated with TTO scores, but were correlatedvalues. These correlations ranged from 0.20 to with Karnofsky Scale scores (Table 2). A longitu-0.43, with most exceeding 0.30. Several regression dinal study of these same patients found thatmodels were analysed to predict RS preferences changes in TTO scores were not correlated withfrom combinations of the health status measures, changes in Karnofsky scores (Kendal t = 0.14), butThirty-three per cent of the variance in the RS were correlated with changes in Specific Activity ---scores were explained by the health status scales. Scale class (Kendal t = 0.23), although this correla-The addition of quadratic terms increased the R2 to tion was in the opposite direction expected. 460.34. Incorporating a physical symptom index in Another study by Tsevat et al. 39 found that TTOthe regression model further increased the R2 to scores were correlated 0.25 to 0.60 with different

0.37. subscalesOfthe SF-36in individualswit]_varying

482 Quality of LzlfeResearch . Vol 2 • 1993


severity of HIV-related disease and controls. The (0.67 versus 0.57, p < 0.06), but after 48 weeks thisSF-36 scales most correlated with TTO scores difference had largely disappeared (0.69 versusincluded the health perceptions scale (r = 0.58 to 0.68, p = 0.98). Correlations between different0.60), physical function scale (r = 0.42 to 0.50), health status measures (e.g. SIP and SF-36) and SGenergy scale (r = 0.51 to 0.53), and the social utilities ranged from 0.07 to 0.30. 2o For example,function scale (r = 0.46 to 0.50). The Mental SG utilities were significantly correlated with onlyHealth Index (MHI) was correlated 0.28 in the HIV SIP home management scores; the remainder ofinfected group and 0.42 in the control group. 39A correlations ranged from -0.07 with the Center forregression analysis found that the combination of Epidemiologic Studies Depression scale to 0.15indMdual SF-36 scales explained 35% of the with a single-item measure of life satisfaction.variance in TTO scores in HIV positive patients Only 25% of the variance in SG utilities wasand 43% of the variance in TTO scores of the explained in a regression model including all thecontrols, healthstatusmeasures.

Tsevat and colleagues 47'4smeasured TTO prefer- Nichol et at.44 obtained SG utilities and disease-ences and other health status indicators in a specific functional status scores on a sample of 41sample of 1438 patients with one of nine chronic patients referred for cardiac catheterization. SGdiseases with a median 6-month survival of 50%. utilities were correlated 0.40 with the Canadian

These authors found that TTO scores were only Cardiovascular Society scale and 0.42 with thepoorly correlated with indicators of activities of Duke ActMtv Specific Index.daily living (r =0.14 to 0.26) and physiologic Revicki et'al. 37 examined the relationship be-reserve (r= 0.17). Profile of Mood States depress- tween SF-36 and other MOS scales, the GWBion and anxiety scores were moderately related physical symptoms, RS and SG utilities in a samplewith TTO scores, with correlations of -0.45 and of patients with hypertension. The correlations-0.32, respectively, between SG utilities and the health status scores

Frvback et al. 35 compared TTO with QWB and ranged from 0.01 to 0.20. GWB energy (r = 0.17)SF-36 scores in a large community sample. SF-36 and general health (r= 0.17), and SF-36 painscale scores correlated 0.15 to 0.43 with TTO (r = 0.16) and energy (r = 0.20) were significantlyscores. 34 _F-36 health perception scores were correlated with SG utilities. In general, the phys-correlated 0.39 and the EVGFP was correlated 0.34 ical symptoms were not correlated with SG utili-with TTO scores. The SF-36 health perception scale ties. Several regression models involving combina-is essentially an expanded measure of self-rated tions of the health status and physical symptoms

health (r = 0.80 in this stud}'). A regression model were specified and analysed in this stud)'. Revickicontaining all the SF-36 scales explained about 25% et a].3' were only able to explain 18°,0 of theof the variance in TTO scores. 34 variance in SG utilities with the best combination

In summary, studies completed to date suggest of health status scores. Including quadratic termsthat health status scores and TTO preferences in the regression model increased the R2 to 0.25.share between less than one percent to 43% of Only SF-36 energy, GWB mental health, andvariance. Most studies observe small to moderate Medical Outcome Study health distress con-correlations between TTO and various measures of tributed significantly in the prediction equations.healthstatus. The addition of a physical symptom index in-

creased R2 to 0.26.

Standard gamble. Few studies have included SG utilities are poorly to moderately related toboth psychometric health status and SG health status measures. Correlations across theutilities. 20'28'27A randomized clinical trial evalu- limited number of studies range from 0.01 to 0.30.ated the clinical and HRQL outcomes of r-HuEPO Health status scales and SG utilities apparently

therapy for patients with anaemia associated with share only about 1% to 25% of common variance,chronic renalinsufficiency. 28 depending on the measure of health status.

This study found that after 48 weeks of treat- However, these conclusions are based on onlyment, the r-HuEPO group showed significant three studiesin chronic disease populations.

improvements compared to the placebo group onenerg?' and vitality (p < 0.02), sleep and rest Quality of Well-Being Scale. Studies by Liang etbehaviour (p < 0.05), and home management al.,41 Read et al., 36Kaplan et al., 13Wu et al., 3° and(p < 0.04). After one month of treatment the Fwback et al. 34'35 contained the QWB as ther-HuEPO group had higher health utility scores preference measure. Research to date suggests

Quality of LifleResearch . Vol 2 • 1993 483

D. A. Rcvicki ami R. M. Kaplan

that the QWB correlates 0.44 to 0.71 with different sample of general practice patients in York. Spear-health status scales. For example, Liang et al. 41 man Rank correlations between the EQ and SF-36found that the QWB was correlated 0.50 to 0.62 scales ranged from 0.48 to 0.60. Unfortunately, the

with generic and disease-specific health status authors did not summarize correlations by indi-scales. Read, Quinn and Hoefer 36 compared the vidual SF-36 scales.

practicality and validity of three generic healthmeasures in a sample of outpatients with hyper-tension. They found that the QWB was correlated0.71 with self-rated health, 0.46 with the General DiscussionHealth Rating Index, 0.33 with the Mental HealthIndex, and 0.55 with SIP total scores. SIP physical Little research has been completed on the relation-and psychosocial scores were correlated with the ship between health utility and psychometricQWB 0.57 and 0.39, respectively. Wu et al.3° found health status outcomes. The findings of this reviewthat the QWB was correlated 0.44 with Karnofsky suggest that psychometric health status scales areScale scores in a sample of AIDS patients treated poorly to moderately, correlated with SG and TTOwith zidovudine, scores. Utilities/preferences correlate 0.01 to 0.60

Frvback et al.33 found that the QWB was cor- with various individual health status measures.

related 0.52 with the general health perceptions When combinations of different health statusscale from the SF-36 and 0.47 with self-rated scales are used to predict utilities in regressionhealth. QWB scores correlated 0.17 to 0.69 with models, explained variance ranges from 18% toSF-36 scale scores and approximately 56% of the 438/0(see Table 3). Only 27% to 348/0of rating scalevariance in QWB scores was explained by a preferences can be explained by measures ofregression model including all the SF-36 scales. 34 functioning and well-being. Rating scale prefer-Hughes, 4_in a study of 100 HIV infected patients, ences are more closely correlated with variousfound that the Q',_,;B was correlated 0123 to 0.64 individual health status measures.with the sub-scales on the MOS HIV Health The QWB is more closely related to psycho-

Survey. The largest correlations were with phys- metric health status scores. For example, Frvback,ical fu,action (r = 0.62), role function (r = 0.64), et ai.34 was able to account for 56°'o of the variance

general health (r = 0.57) and energy (r = 0.47). in QWB scores using a combination of SF-36 scales.Kaplan et al. _3 demonstrated that the QWB is In general, there are stronger correlations betweencorrelated with different measures of functioning a number of different measures of health statusand well-being in arthritis patients. QWB scores and function and QWB scores. However,were correlated -0.57 with Arthritis Impact measures of psychological function (e.g., depress-Measurement Scale (AIMS) physical, -0.17 with ion, anxiety, mental health) tend to have a weakerpsychological, and -0.40 with pain scores, relationship with QWB scores compared to otherChanges in QWB was correlated -0.28 to -0.32 measures of health status, such as physical func-with changes in AIMS scores, tion, mobility, general healt h perceptions, and role

A number of studies by Kaplan and associates function. These findings mav be, in part, due toexamining the validity of the QWB have found overlap between the dimensions that make up themoderate correlations between the QWB and QWB (e.g., physical activity, social activiD', mobil-measures of health status and functioning, ity, symptoms) and these health status scales. ThisApproximately 11% to 50% of the variance in QWB is not surprising since the QWB and several otherscores are accounted for by different health status health status measures have common origins inmeasures. In general, these studies show that some of the earl}, health and disability survevs. _sQWB scores are more highly correlated with Various health status scales, such as the HIE andmeasures of physical function than psychological MOS measures, were developed from physicalfunction. 13'18'34'35'40'49 function parts of these earlier health surveys.

The QWB does not contain a specific mental

Other multiattribute preference measures. Brazier health dimension, although some measures ofet ai.33 reported on a study comparing SF-36 scores psychological function and severity of mentalto the recently developed EuroQol (EQ) of 1582 illness are correlated with the QWB. 12'1sThere ispatients from two primary care practices in the also some debate as to whether mental healthUK. The EQ consists of a series of questions that needs to be a conceptually separate dimension.

have been preference-weighted by a different The impact 0f mental health on general health

484 QualityofLifeResearch. Vol2 •1993


status is expressed through its impact on life and knowledge and non-health related factorsexpectancy, functioning, and symptoms. Thus, a (e.g., financial status, social networks). 2°'32person with an anxiety disorder might report an Preference/utility measures and psychometricanxiety symptom on a utility measure or have health status measures are constructed to addresslower MHI scores in the MOS. Severe anxiety may different purposes. The strengths and weaknessesdisrupt role and social functioning. Some indi- of each approach are reflected in their purpose ofviduals experiencing symptoms of depression may measurement. The psychometric measures arereport no disruption in their role function, while designed to arrange persons along different con-others may need to be hospitalized. Therefore, the tinuums of function or well-being. The generalimpact of depression on functioning and well- purpose is to discriminate levels of functioningbeing may be very similar to the impact of a between groups and to detect changes in functionphysical health problem, such as shortness of over time. The preference/utility scales are de-breath. A combined conceptualization of physical signed for application in cost-effectiveness ana-and mental health allows the impact of mental lyses and to help decisions about resource alloca-health programmes to be compared directly with tion. A single metric on a scale from death tothose of physical health programmes. 49 complete health is useful for making judgements

The low to moderate association between health about the impact of different health care technolo-status and utility/preference measures can be gies on health outcomes. Both measurementexplained by how risk and time is introduced into approaches are useful in evaluating health inter-the assessment process, the measurement task and ventions and are not interchangeable measures ofthe cognitive evaluation processes invoh'ed with HRQL.SG and TTO techniques. 2° Persons determine their Health status scales and health utility/preferencepreferences by implicitly or explicitly weighting scales measure different, although related, aspectsdifferent attributes of a health state, and then of health-related quality of life. The utility

make judgements depending on the measurement measures involve individual judgements of healthtask. A series of information processing activities outcomes relative to death and complete health.are invoh'ed m perceiving and understanding Different utility/preference assessment methodshealth state stimuli, construction of subjective produce different values for preferences that max"values for dimensions (within stimuli), combining not entirely be accounted for by measures of

multiple attributes, and then making a response physical, social and psychological functioning, andwithin the context of a preference measurement well-being. Conversely, psychometric healthtask. 12'1s'5_A number of different attributes of the status scales measure dimensions of HRQL, and

measurement task and stimuli (i.e., health states, supply additional information useful for under-

questions) and the individual influence the assign- standing health outcomes.ment of pr6ferences. These attributes include Health status and utility/preference scalesframing effects, health state description, duration measure different components of health. The twoof the health state, attitudes about risk, cognitive approaches result in different yet related and

complexity of the measurement task, perception complementary assessments of health outcomes.and attention, beliefs about health and emotional Investigators need to be aware of the differencesreactions. 12'18'2°'31'32'-_1The addition of duration of between utility/preference and health statusthe health state into the assessment process will measures. Patient assessments of health outcomesalso affect preference scores, n'2_ are important for the evaluation of medical treat-

Some of the differences between health utility ment, and multiple methods for assessing healthand health status measures are due to actual outcomes are needed to help clinicians, patients

preferences for health conditions. These prefer- and their families in selecting among alternativeences may only be partially related to assessment medical treatments. A greater understanding ofof current health status and well-being, which the relationship between utilities and preferences

explains the moderate correlation between health and health status measures is needed. Futurestatus and SG or TTO scores. Preferences for research needs to focus on explaining measure-current health are likely influenced by current ment and individual variation in utilities, and tofunctional status and well-being, adaptation to better identify the cognitive processes people useillness, and other factors, such as risk aversion, to make preference judgements related to healthbeliefs about health, characteristics of the measure- outcomes. Combining health status and prefer-ment task, emotional factors, previous experience ence measures with traditional indicators of safety"

QualityofL(feResearch. Vol2 . 1993 485


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