Evaluating Patient-Based Outcome Measures - NIHR Health ...

cases questionnaire items may ask for reports
of very specific behaviours, for example, ability to
walk a certain distance, or use of physical aids, that
observers such as carers or therapists can in principle
readily verify from observation. Even with such
behavioural items, the questionnaire still largely
elicits perceptual information. It is this reporting of
the personal and the subjective by the patient that
uniquely identifies patient-based outcome measures
from other health information used as outcomes,
such as laboratory data. Clinical scores and scales are
a different kind of subjective perceptual evidence;
they are the perceptual judgement of doctors or
of other health professionals. It is the inherently
subjective source of patient-based material that
leaves grounds for anxiety in some minds about the
‘hardness’, robustness and ultimately scientific value
of such evidence (Fries, 1983; Deyo, 1991). Such
concerns are addressed when we consider desirable
measurement properties of patient-based measures
in chapter 3.
Dimensions such as ‘QoL’ and ‘subjective health
status’ can be assessed by what may be considered a
continuum of methods. At one extreme, health
professionals or others make judgements with
minimal input from the patient, and, at the other
extreme, assessments are largely determined by the
patient with minimal influence from other observers.
This review is largely concerned with instruments
of the latter kind because there is a prima facie
case that such measures more directly elicit the
respondent’s perspective rather than the observer’s
(O’Brien and Francis, 1988; Rothman et al., 1991;
Berkanovic et al., 1995). However there is a continuum
of approaches and much of what is discussed
in this review may be relevant to assessments such as
disability scales or standardised psychiatric assessments
which are completed by observers on the
basis of evidence from a patient, but without the
patient himself or herself literally selecting the
items or description that most fit their view.
There are circumstances where patients are unable
to provide their unique report of their perceptions,
due to ill-health, physical or cognitive problems, or
some other incapacity. In these cases, proxy reports
may be necessary because of the need for some
assessment to inform a clinical trial. Because there
is consistent evidence of lack of agreement with
patients’ judgements of their QoL by observers
such as health professionals, informal carers, and
other so-called ‘proxy’ judges, this is increasingly
considered a second-best solution to be used only
when the patient cannot contribute (Mosteller et
al., 1989; Clarke and Fries, 1992; Sprangers and
Aaronson, 1992). However, there
Health Technology Assessment 1998; Vol. 2: No. 14
is also substantial evidence that patients with
poorer health are less likely to complete patientbased
outcome measures (Bleehen et al., 1993).
Since such patients are an important group in
relation to assessment of outcomes in trials and
their omission may result in bias, effort is required
to examine the extent to which proxy ratings of
outcome are valid. Whilst there is clear evidence
of discrepancies in judgements between patients’
and proxy reports from others, it is important to
examine closely the scope for obtaining proxy
reports when patients’ are unable to contribute.
Sneeuw and colleagues (1997) used a simple QoL
instrument with relatively few distinctions between
levels of QoL with patients with a range of cancer
diagnoses, and their informal carers and physicians
also rated the sample of patients on the same
instrument. For five out of six dimensions, there
was broad agreement between patient and physician
or carer in 85% of patients, and 75% agreement
on a sixth dimension (‘social activities’).
Agreement also increased for some dimensions
at a follow-up assessment. Thus there is some
support for using evidence from proxies at least
when relatively simple judgements are required.
Theories and concepts
It is sometimes argued that this field lacks a
rigorous underpinning theory and clear and
precise definitions that flow from theory (Schipper
and Clinch, 1988; Ventegodt, 1996). There is some
basis for this criticism; much of the work stems
from very applied and pragmatic problem solving,
rather than deriving from an explicit theoretical
framework. However it is not entirely true that the
field of patient-based outcome measures lacks
theories of the phenomena that investigators wish
to measure. Psychometric theory provides a well
established foundation for most patient-based
outcome measures (Nunnally and Bernstein, 1994).
This scientifically rigorous field is concerned with
the science of assessing the measurement characteristics
of scales and involves such properties as
validity, reliability and responsiveness (Hays et al.,
1993). More recently developed is the field of
‘clinimetrics’ (Feinstein, 1987; Feinstein, 1992;
Wright and Feinstein, 1992). Closely associated
with psychometric theory, this field focuses on the
clinical challenges of constructing scales that
clinicians use for measuring health status of
patients (Fava, 1990). Similarly, economic contributions
to this field have also a broad range of
theoretical literature on which to draw from
evidence such as decision-theory (Torrance, 1986).
Thus strictly speaking, a far greater difficulty
than the dearth of theory is that there are a large
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