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OCR for page 137
17
Assessing Health-Related
Quality of Life Outcomes
Donald L. Patrick
The hope and promise of the Effectiveness Initiative to curtail escalating
health care costs remind me of the time an airline pilot made an urgent
announcement during a transatlantic flight. His voice suddenly came over
the public address system, and he said, "Ladies and gentlemen, I have two
pieces of news for you. One of them is good, and one of them is not so
good. First I'll tell you the bad news. The bad news is that we are lost. We
don't have any idea of where we are. But, as I told you, there is good news,
too. The good news is that we have a 200-mile-an-hour tail wind. In other
words, we don't know where we're going, but we're getting there awfully
fast." ~ think this story nicely describes our current situation. Rapidly
rising costs are hastening our attempts to use whatever means possible to
find solutions. The Effectiveness Initiative is one means of turning bad
news into good news.
I wish to address four methodological issues involved in the assessment
of health status outcomes: (a) selection of relevant outcomes; (b) use of
generic and disease-specific measures; (c) progress toward short, reliable,
valid, and responsive measures; and (d) methods for interpreting observed
changes in measures.
Before reviewing these issues, however, I would like to identify two
challenges to our reliance on outcomes assessment for controlling health
care costs. First, I would remind us that health services are only one
determinant of health status (1~. When we talk about effectiveness of health
care in terms of health status outcomes, we cannot forget that socioeconomic,
political, and cultural systems have diverse and powerful influences on outcomes
(2~. Effectiveness of medical care is our focus, but the larger sociocultural
context influences both provider and patient reports of outcomes. Effectiveness
is often in the eye of the beholder; patient expectations range from efficacious
137
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138
EFFECTIVENESS AND O UTCOMES IN HEALTH CARE
TABLE 1 Combinations of Cost and Effectiveness Outcomes
Quality of Life Outcomes
+
Cost
of
Treatment
+
Worse quality of life
Higher cost
Better quality of life
Higher cost
Worse quality of life
Lower cost
Better quality of life
Lower cost
treatments that "cure" to "hugs from the doctor." Patient expectations, in
fact, may well exceed our ability to provide the services that produce expected
outcomes.
A second cautionary note is that the increase in health technologies makes
cost containment extremely difficult. Our decisions concerning cost and
effectiveness outcomes can be described in Table 1.
There are four different combinations of cost and effectiveness outcomes.
Ideally, new technologies such as pharmaceuticals will produce better quality
of life outcomes at reduced cost (lower right quadrant). Medical treatment
for back pain and new drugs for benign prostatic hypertrophy might produce
similar results. Rationing, capping reimbursement, and other methods of
cost containment may produce outcomes in the lower left quadrant, that is,
worse quality of life and lower costs. The upper left quadrant (higher cost,
worse quality of life) is obviously to be avoided, although life-extending
treatments might well fall into this category. Most technological innovations
probably fall in the upper right quadrant, that is, better quality of life outcomes
at higher cost. Technological advance clearly challenges our initiatives to
maintain or lower health care costs.
QUANTITY AND QUALITY OF LIFE
Quantity and quality of life are distinct but related concepts used to
evaluate the present and future state of a person or group of people (3~.
Taken together, quantity and quality should represent a complete picture of
the person or group. Quantity of life is assessed in terms of length of
survival. For example, survival time is the number of days a patient lives
after undergoing heart transplantation or while receiving drugs such as
azidothymidine (AZT, a treatment for AIDS). Although such drugs may
prolong the life of patients, they may produce concurrent toxic effects. It is
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DEVELOPMENT AND USE OF OUTCOMES MEASURES
139
easy to assess quantity of life accurately in retrospective studies, but prog-
nosis or duration of survival can only be estimated, often with considerable
uncertainty. Furthermore, the value attached to a day of life differs from
one person to another (4~. For some persons, death is preferable to the
lowest states of functioning, such as coma or profound pain or depression.
Quality of life has been assessed in a variety of different ways, including
beauty in the landscape, close family life, environmental purity, and a spiritual
understanding of existence. Health-related quality of life is more limited; it
can be defined as the value assigned to the duration of life as modified by
the social opportunities, perceptions, functional states, and impairments
that are influenced by disease, injuries, treatments, or policy (5~. This
definition covers five broad concepts on a continuum of health-related qual-
ity of life, which is anchored at the top by an optimal value of 1.0 and at the
bottom by a minimal value of 0. Specific dimensions of opportunity, perception,
functional status, impairment, and survival fall along this continuum. See
Table 2 for a more comprehensive description of the concepts and dimen-
sions of health-related quality of life.
Dimensions of the five concepts may be negatively or positively valued
in relation to one another. The value assigned to the particular state of
individuals or groups defines health-related quality of life. The time spent
in that state or the probability of moving from one state to another (that is,
prognosis) defines quantity of life. Thus, a complete representation of
health-related quality of life involves specification of relevant states or
combinations of dimensions, the values or preferences assigned to these
states, and the duration or probability of duration in different states. This
definition of health-related quality of life is similar to the health-state utilities
approach developed over the last two decades (6~.
SELECTION OF OUTCOMES
The question arises whether there is a core set of outcomes that must be
included in a quality of life assessment on theoretical, empirical, or judgmental
criteria. Sol Levine has provided theoretical guidance in this area by focusing
attention on two very important aspects of quality of life (74. The first is
performance of the physical, psychological, and social functions and activities
that people do in their everyday lives. The second is the satisfaction derived
from performing these usual activities. Functional status and satisfaction
with health are the core domains of health-related quality of life.
There are many measures currently available to assess these health-re-
lated quality of life dimensions. When we select these measures, we are
attempting, in advance, to identify the potential effects of treatments as well
as the potential side effects or unanticipated consequences of treatments.
Table 3 contains a taxonomy of health-related quality of life measures.
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140
EFFECTIVENESS AND OUTCOMES IN HEALTH CARE
TABLE 2 Concepts and Domains of Health-Related Quality of Life
Concept and Domain
Opportunity
Social or cultural handicap
Individual resilience
Health perceptions
Satisfaction with health function
General health perceptions
Functional status
Social
Limitations in usual roles
Integration
Contact
Intimacy
Psychological
Affective
Cognitive
Physical
Activity restrictions
Fitness
Impairment
Subjective complaints
S.
1gns
Self-reported disease
Psychological measures
Tissue alterations
Diagnoses
Death and duration of life
Definition/Indic ator
Disadvantage because of health
Capacity for health; ability to withstand
stress; reserve
Physical, psychological, social
Self-rating of health; health concern, worry
Acute or chronic limitations in social roles
of student, worker, parent, household
member
Participation in the community
Interaction with others
Perceived feelings of closeness; sexual
Psychological attitudes and behaviors,
including distress and general well-
being or happiness
Alertness, disorientation; problems in
reasoning
Acute or chronic limitation in physical
activity, mobility, self-care, sleep,
communication
Performance of activity with vigor and
without excessive fatigue
Reports of physical and psychological
symptoms, sensations, pain, health
problems, or feelings not directly
observable
Physical examination: observable evidence
of defect or abnormality
Patient listing of medical conditions or
impairments
Laboratory data, records, and their clinical
interpretation
Pathological evidence
Clinical judgments after "all the evidence"
Mortality; survival; longevity
SOURCE: Patrick and Erickson (5~.
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DEVELOPMENT AND USE OF OUTCOMES MEASURES
TABLE 3 A Taxonomy of Health-Related Quality of Life Measures
Approach
Scores for analysis
Single index number
Useful for cost-
effectiveness
Profile of interrelated
scores
Battery of
independent scores
Wide range of outcomes
Objective of application
Generic: across
conditions and
populations
Specific: disease,
population, function,
. .
or cone Ton
Weighting System
Utility: preference
weights from patients,
. .
prove .ers, or community
Statistical: items
weighted equally or
from frequency of
response
141
Strength
Represents net impact
May not be responsive
Single instrument
Effects on different
outcomes possible
Can select relevant
outcomes
Multiple comparisons
possible
Broadly applicable
Summarize range of
concepts
May detect unanticipated
effects
More acceptable to
respondents
May be more responsive
Interval scale
Patient view
incorporated
Self-weighting
samples
More familiar techniques
Appears easier to use
Weakness
Effects on different
outcomes not possible
May not be responsive
Length often problem
Cannot relate different
outcomes to common
scale
Need to identify major
outcome
May not be responsive
enough
May not have focus of
patient interest
Length often problem
Effects may be difficult
to interpret
Comparisons across
conditions and
populations not
possible
Difficulty obtaining
weights
May not differ from
statistical weights that
are easier to obtain
May be influenced by
prevalence
SOURCE: Guyatt et al. (8~.
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42
EFFECTIVENESS AND OUTCOMES IN HEALTH CARE
Measures can be classified according to the scores they produce for analy-
sis, their objective in application, and the weighting system used in scoring
(8~.
SOURCES FOR ANALYSIS
Indexes
Measures such as the Quality of Well-being Scale (9), the Health Utilities
Classification (6), and the Disability/Distress Scale (10) combine duration
of life with specific dimensions of impairment, as well as physical, psychological,
and social function. These measures yield a single index value, quality-
adjusted life years (QALYs), that can be used to compare the cost per
quality-adjusted life year gained from different health interventions. For
example, the cost per QALY gained in 1986 U.S. dollars for coronary artery
bypass surgery for left main coronary artery disease is $4,796, compared
with $36,316 for neonatal intensive care for infants weighing 500 to 900
grams (6~. The effects of a particular treatment on a single index, such as
QALYs, however, remain hidden. There is considerable controversy over
whether such an index can represent health in a sufficient manner to detect
changes and, indeed, interpret where those changes have taken place. Nev-
ertheless, QALYs, or years of healthy life, are gaining acceptance, as exemplified
by their inclusion in the Year 2000 Objectives for the Nation (11~.
Profiles
Other measures provide a profile of scores for different components of
health-related quality of life. The Sickness Impact Profile (SIP) assesses
sickness-related dysfunction in 12 different categories, producing a score
for each category (12~. Various categories may be aggregated into a physical
dimension score, a psychosocial dimension score, and an overall score with
independent categories of work, eating, sleep and rest, home management,
and recreation and pastimes. Similarly, Part I of the Nottingham Health
Profile (NHP) contains 38 items that cover six domains of experience, yielding
individual scores for each; Part II contains perceived problems in seven
areas of daily life (13~. Unlike the SIP, however, the NHP does not yield an
overall index score. The 59-item McMaster Health Questionnaire yields
separate indexes for physical, emotional, and social function (14~. Measures
developed originally at The RAND Corporation the 108-item Health Insurance
Study battery and the 20- to 40-item Medical Outcomes Study short-form
generic measures cover a wide spectrum of health concepts for use in
general populations (15~. All these generic measures have been tested ex-
tensively with different patient populations.
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DEVELOPMENT AND USE OF OUTCOMES MEASURES
Batteries
143
It is important to make a distinction between health profiles and batteries.
Batteries are collections of health status measures with independent scores
for each outcome. Specific measures of different health outcome domains
are selected to make up an assessment battery. The recent evaluation of
antihypertensive medications, sponsored by the Squibb Pharmaceutical Company,
is an example of the battery approach (16~. These investigators selected,
among others, the latest "best available" specific measures of general well-
being, physical symptoms, and sexual dysfunction. Improvement in quality
of life was assessed for three different anti-hypertensive agents on each of
these independent measures. Luckily, all measures chosen for this study
showed some improvement for the new drug under consideration. Often,
our results are more mixed.
The battery approach is an appealing assessment strategy because of the
wide range and type of outcomes that can be assessed. A major outcome
needs to be identified as the primary endpoint, however, to avoid conflicting
findings and multiple comparisons of outcomes on different measurement
scales.
GENERIC AND SPECIFIC MEASURES
Generic measures of health status are those that purport to be broadly
applicable across types and severities of disease, across different medical
treatments or health interventions, and across demographic and cultural subgroups.
Visual analogue measures are designed to summarize a spectrum of the
concepts of health or quality of life that apply to many different impair-
ments, illnesses, patients, and populations.
Disease-specific measures are those designed to assess specific diagnos-
tic groups or patient populations, often with the goal of measuring responsiveness
or "clinically important" changes. These are changes that clinicians and
patients think are discernible and important, have been detected with an
intervention of known efficacy, or are related to well-established physiological
measures (such as grip strength for arthritis patients or spirometry for those
with chronic obstructive lung disease) (17~. The term "disease-specific,"
here, refers to different adult patient populations with specific conditions or
diagnoses.
Not all specific measures are disease-related. They may be specific to
conditions (for example, back pain or dyspnea), functions (for example,
sexual or emotional function), or populations (for example, older adults or
developmentally disabled children). Specific measures of single concepts
or conditions are the most numerous of all within the health status field.
These single-concept measures range from the assessment of specific symptoms
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144
EFFECTIVENESS AND OUTCOMES IN HEALTH CARE
such as nausea and vomiting to more global concepts of life satisfaction.
Mental health measures of depression, anxiety, and other emotional states,
for example, are frequently used in clinical research for assessing individual
concepts of psychological status. Numerical estimates of subjective pain,
such as visual analogue scales, have gained a wide following, partly because
of their high correlation with verbal rating scales and their simplicity (184.
Visual analogue scales are also gaining popularity in the measurement of
symptoms and functional status.
Disease-specific measures, such as the Karnofsky Performance Status
Scale for cancer (19), the American Rheumatism Association (ARA) functional
classification for arthritis (20), and the New York Heart Association functional
classification (21), have been used extensively over several decades. These
measures were developed to meet the need for rapid classification of patients,
and their sensitivity to small but clinically important change is limited. The
ARA classification, for example, may detect large changes, such as those
following hip replacement, but not smaller changes following drug therapy
judged successful by other criteria. The popularity of disease-specific measures
arises primarily from the need of clinical trials and practitioners to use
scales that are most responsive to clinical changes that occur over time.
Both discriminating improved from unimproved patients and accurately
quantifying minimally important changes are particularly important measurement
objectives for clinical research and clinical practice.
Generic and disease-specific assessments alike are useful for clinical
research, clinical practice, and policy analysis. Selection of different mea-
sures depends on the objectives of measurement and the environment of the
application. No single general-purpose measure is likely to meet all the
needs of investigators and specific populations. Patients with different medical
conditions have different concerns or place different emphasis on more
generic concepts of health. Rather than develop disease-specific measures
that incorporate generic concepts of health-related quality of life, the preferred
strategy is to use standardized, generic instruments with disease-specific
supplements.
Generic measures permit the comparison of different populations and
different programs, a most important objective for policy analysis and decision
making. Use of generic measures is necessary for comparing benefits of
different health interventions and allocating resources. Cumulative knowl-
edge of health and quality of life outcomes using generic measures will
establish the relative burden of different diseases and the relative merit of
different interventions.
By contrast, instruments specific to different diseases, conditions, and
populations are critical for identifying important concerns of patients with
particular conditions and for measuring small, clinically important changes
from specific treatments. Experience with disease-specific measures to date
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DEVELOPMENT AND USE OF OUTCOMES MEASURES
145
indicates their usefulness in discriminating among different conditions and
in assessing changes. Rapid development of such instruments is to be
expected for conditions and populations where few specific measures now
exist, notably certain cardiovascular conditions, diabetes, gastrointestinal
disorders, and sexually transmitted diseases including AIDS.
SHORT, RESPONSIVE MEASURES
The development of short-form generic measures for use in clinical practice
is a welcome advance (22,23~. Undoubtedly these measures will be tested
against more comprehensive and detailed generic instruments to identify
information that may be lost using brief assessments. The need to measure
an increasing array of physiological, physical, psychological, social, and
general outcomes within a single investigation cannot be met unless measures
are short, efficient to administer, and highly acceptable to investigators and
respondents. Both generic and disease-specific measures will be assessed
against these practical constraints.
Self-administered, comprehensive measures that are sensitive to varia-
tions in health care organization and medical practice are also needed. Short,
generic health status measures (1 to 60 items) have been developed from
longer versions based on minimal psychometric criteria for internal consis-
tency reliability and content and construct validity (22,24~. The Short-Form
Health Survey, derived from measures used in the Medical Outcomes Study,
is currently being tested for its responsiveness, or ability to detect minimal
changes of importance to interested parties. In the next decade, short-form
generic measures need to be tested rigorously for their content validity,
responsiveness, convergent and discriminant validity, and generalizability.
"Short" and "comprehensive" can be conflicting goals for some applica-
tions and populations. The full domain of health-related quality of life
outcomes of interest to patients, providers, and payers simply cannot be
represented in short measures. Some concepts, for example, cognitive function,
sleep and rest behaviors, recreation, and satisfaction with health, are seldom
represented in short, generic measures. These omissions may not seriously
compromise the usefulness of short-form measures in relatively well popu-
lations, but outcomes assessment in specific populations such as older per-
sons, mentally ill persons, and institutionalized persons may require long-
form assessments.
Responsiveness, how well short-form measures detect subtle changes in
behavioral and subjective health status, also requires testing and comparison
with clinical measures. We can be encouraged by the data from the Medical
Outcomes Study indicating that generic measures are very strong in detect-
ing stable scores among a clinically stable group. Greater emphasis needs
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146
EFFECTIVENESS AND OUTCOMES IN HEALTH CARE
to be placed on the assessment of responsiveness in comparing generic and
disease-specific outcomes.
Responsiveness is an important consideration in all serial applications of
health status measures. Including items sensitive to change is critical to
such assessments. Responsiveness of health status measures has been assessed
using the relative efficiency statistic (a ratio of paired t statistics) (25),
correlation of scale changes with other measures (26), receiver-operating
characteristic curves (26), and a responsiveness statistic (ratio of minimal
clinically important differences to variability in stable subjects) (171.
Disease-specific measures with items selected to assess particular concerns
or worded to attribute change to the condition of interest, for example, back
pain in the modified SIP, may be particularly sensitive to within-subject
changes and thus more responsive than generic measures, which contain
items unrelated to change.
CHANGES IN MEASURES
Analyzing and interpreting changes in health status measures are problems
in all longitudinal studies. These may be observational case studies, cohort
studies, clinical trials, or health services evaluations. Changes in physiological
measures such as blood pressure or cholesterol level may be interpreted in
terms of prognostic implications and well-established or agreed cutoff points.
Changes in generic health measures are more difficult to interpret, although
even small changes in portions of such measures may be quite useful (for
example, changes in physical mobility or self-care are meaningful in disabled
populations). Changes in scores on the most general measures, such as
health perceptions or global physical and psychosocial dimension scores,
can be even more difficult to interpret.
The net changes observed may reflect a large number of different transi-
tions or combinations of transitions within the population. Single-score or
aggregated measures can make it difficult to identify which items or components
are responsible for the change. Net changes must also be distinguished
from random or systematic changes (learning effects, rumination) that may
occur independently of an intervention. Although changes in these scores
may reflect sensitive effects, the relative magnitude of the change may be
difficult to assess. For example, is a S-point difference more meaningful
than a 3-point difference?
Changes in disease-specific measures may be easier to interpret because
they are more specific or more closely associated with changes in clinical
measures of disease activity such as blood pressure or joint inflammation.
Clinician or patient assessments of improvement, which are common measures
of change or effects, may be more closely associated with changes in disease-
specific measures than with those in generic health status measures (27~.
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DEVELOPMENT AND USE OF OUTCOMES MEASURES
A THEORETICAL MODEL FOR HEALTH STATUS AND
QUALITY OF LIFE
147
A major challenge facing developers and users of health and quality of
life measures is to establish a testable theory of the expected relationships
among the different concepts and domains of health-related quality of life.
The problem is not confined only to the relationship between physiological
measures and behaviors or perceptions, for example, blood pressure and
functional status. Measures of various dimensions, such as symptoms, psy-
chological function, and satisfaction with health have been shown to be
only loosely associated or entirely dissociated within the same sample (2~.
Figure 1 depicts hypothesized relationships among different health-related
quality of life concepts in a simple linear progression. The concepts are
bounded by environmental determinants that influence disease and its con-
sequences and by prognoses for improvement, maintenance, or decline in
health-related quality of life.
The simple causal model suggested in Figure 1 does not represent the
complexity or strength of the expected relationships among health-related
quality of life dimensions. For example, persons can have an asymptomatic
disease that affects prognosis without affecting functional status, perceptions,
or opportunity. A person with hypertension or hypercholesterolemia may
not have restrictions in activity but may be disadvantaged by fear of a
stroke or death. Similarly, not all persons with impaired physiological
capacity experience psychological dysfunction. Persons with rheumatoid
arthritis and congestive heart failure may have high satisfaction with their
health and positive well-being.
Figure 1 also indicates that the causal relationships among concepts can
be reversed; for example, functional limitations and perceived health can be
viewed as influencing impairment or physiological measures of chronic disease
(29~. Reversing the causal chain permits testing of the variable course of
chronic disease, whereby impairments may become permanent and lead to
changes in behavior and perceptions that, in turn, influence symptoms or
level of impairment. The notion of an interplay between the psyche and the
body is as old as medicine itself. Models of psychophysiological processes
such as disruption in the regulation of blood volume and control of blood
pressure by the kidneys can be invoked to explain sociobehavioral influ-
ences on disease processes. This evidence may not be sufficient to convince
the most skeptical biomedical researcher, but the hypothesis has moved
well beyond mere speculation.
At present, researchers tend to approach the relationship among end points
inductively, by collecting data and examining the correlation among measures.
Little hypothetical or deductive reasoning is involved in either the selection
of measures or analysis of results. Head-to-head comparisons of different
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48
EFFECTIVENESS AND OUTCOMES IN HEALTH CARE
Duration of Life
!
Disease and Injury
l
1
Impairments
Environment
Genetic
Personal
Social
Economic
Cultural
Physical
Physical, Psychological,
& Social Function
1
Health Perceptions
Opportunity for Health
Prognosis
Improvement
Maintenance
Decline
Variable
FIGURE 1 Relationships Among Health-Related Quality of Life Concepts
SOURCE: Adapted from Patrick and Bergner (28~.
dimensions will be important for determining the association between spe-
cific disease states or disorders and their behavioral, perceptual, and social
consequences. Increasing our understanding of these relationships will help
us realize the potential of health-related quality of life measures for identi-
fying the intervention strategies that address the most important concerns of
patients, their families, clinicians, and society in general.
CONCLUSIONS
The use of health-related quality of life measures, especially those based
on function, is likely to increase during the next decade. This increase,
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DEVELOPMENT AND USE OF OUTCOMES MEASURES
149
however, is most likely to occur in clinical research and clinical practice
(301. Unless the necessary political will, resources, data, and policy researchers
coexist, there will be relatively little advance in the use of health status
measures for decision making and policymaking.
Policy research tends to rely on available national data, and currently
these data provide limited information about health status. The Effectiveness
Initiative will be successful only if it motivates data collection and methods
that incorporate a broad spectrum of health outcomes (such as death, impairment,
functional status, and perceptions) into a single assessment. Health and
quality of life outcomes are what count, and these outcomes cannot be
determined without appropriate and inclusive measures of health-related
quality of life.
I hope that motivation and resources will be found to help resolve meth-
odological issues in the measurement of health status and quality of life. I
also hope that government agencies, employers, and private providers will
begin to collect health-related quality of life data on the constituents and
populations they serve. Even if these data are imperfect or primitive, the
effects of improving accessibility and quality of health care can only be
assessed adequately in terms of the health-related quality of life of the
nation.
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Representative terms from entire chapter:
generic measures
