International Journal of Nursing Studies 38 (2001) 609–615
Responding to uncertainty in nursing practice
Carl Thompsona,*, Dawn Dowdingb
a
Department of Health Studies, Centre for Evidence Based Nursing, Genesis 6, University of York, York, YO10 5DQ, UK
b
Department of Nursing and Midwifery, University of Stirling, Stirling, Scotland, UK
Abstract
Uncertainty is a fact of life for practising clinicians and cannot be avoided. This paper outlines the model of
uncertainty presented by Katz (1988, Cambridge University Press, Cambridge, UK. pp. 544–565) and examines the
descriptive and normative power of three broad theoretical and strategic approaches to dealing with uncertainty:
rationality, bounded rationality and intuition. It concludes that nursing research and development (R&D) must
acknowledge uncertainty more fully in its R&D agenda and that good-quality evaluation studies which directly
compare intuitive with rational–analytical approaches for given clinical problems should be a dominant feature of
future R&D. # 2001 Elsevier Science Ltd. All rights reserved.
Keywords: Clinical decision making; Uncertainty; Rationality; Bounded rationality; Intuition
1. Introduction
This paper discusses the issue of uncertainty in
nursing, and how nurses attempt to gain control over
clinical uncertainty in order to make judgements and
decisions. Specifically it highlights different forms of
uncertainty, and examines how rational and intuitive
approaches to judgement and decision making might
prove useful in making sense of, and therefore coping
with, uncertainty in clinical practice. It is suggested that
the entire issue of uncertainty within nursing practice
needs to be discussed in more detail as a cornerstone of
efforts to ensure that research and development (R&D)
aimed at improving nursing practice reflects and
addresses the clinical reality of the choices nurses face.
2. Uncertainty: the one variable in healthcare which is
certain
Uncertainty is an inescapable and omnipresent fact of
decision making in societies. Pitz and Sachs (1984)
*Corresponding author. Tel.: +44-1904-434101; fax: +441904-434102.
suggest that:
a judgement or decision making (JDM) task is
characterized either by uncertainty of information
or outcome, or by a concern for a person’s
preferences, or both. Unlike other tasks, there may
exist no criterion for determining whether a single
choice or judgement is correct, since the response is
based in part on personal opinions or preferences.
(p. 140).
Human beings however, have difficulty in both
accepting this uncertainty within their daily lives, and
integrating it into their judgement and decision making
processes (Katz, 1988). In health care, as in other areas
of human activity, judgement and decision tasks are
uncertain. Characteristically, a patient’s diagnosis is
probably accurate, the treatment and interventions they
receive will probably work and the patient will probably
get better.
Baumann et al. (1991) suggest that this uncertainty
occurs at more than one level, employing the terms
micro and macro (un)certainty to refer to the bidimensional nature of the concept. For them micro
(un)certainty refers to the level of confidence expressed
by an individual about his or her decision, reflecting
0020-7489/01/$ - see front matter # 2001 Elsevier Science Ltd. All rights reserved.
PII: S 0 0 2 0 - 7 4 8 9 ( 0 0 ) 0 0 1 0 3 - 6
610
C. Thompson, D. Dowding / International Journal of Nursing Studies 38 (2001) 609–615
individual variation. Macro (un)certainty is the extent to
which these decisions vary across individuals, reflecting
variations in practice.
In contrast, Katz (1988), following on from Fox
(1957), highlights three different types of uncertainty
which, it is suggested, affect how clinicians make
judgements and decisions. The first type of uncertainty
results from an individual having incomplete or
imperfect knowledge of the area; the second from
limitations in current empirical knowledge; and the
third is a derivative of the first two: there is difficulty in
distinguishing between personal ignorance and the
limitations of current knowledge.
These two different approaches to uncertainty can be
combined. For instance, a nurse may have incomplete
knowledge with which to make a judgement or decision
but a high level of confidence in the decision taken } the
first type of uncertainty highlighted by Katz (1988),
together with micro (un)certainty defined by Baumann
et al. (1991). This can often lead to a practitioner having
over (or under) confidence in their judgmental abilities.
Alternatively, there may be incomplete empirical
evidence to support a particular treatment intervention,
and variations in whether that treatment is used
according to the hospital a patient attends } the second
type of uncertainty identified by Katz (1988) together
with macro (un)certainty defined by Baumann et al.
(1991). In some instances the patient may receive a
treatment, which the practitioner has little knowledge of,
and for which there is little supporting empirical
evidence. In this instance it is unclear where the
uncertainty regarding the treatment arises: it may not
work because of the practitioner’s limited knowledge (a
situation easily rectified by asking a knowledgeable nurse
to deliver it); equally, it may not matter who delivers the
intervention as its lack of effectiveness may be masked by
the limited empirical evidence to support its use.
Uncertainty therefore is an unavoidable characteristic
of clinical practice. However, the key dilemma for
practitioners, policy makers and } most importantly }
healthcare recipients, is how practitioners make judgements and decisions when faced with the reality of these
uncertain clinical situations. In this paper broadly
rational and intuitive strategies to judgement and
decision making are examined utilising the framework
of uncertainty proposed by Katz (1988). The relative
utility of the different approaches in helping practitioners cope with the uncertainty inherent in clinical
situations is examined and proposals for future research
suggested.
3. Rationality in dealing with uncertainty
Dahl and Lindblom (1992) suggest that an action is
rational to the extent that it is ‘correctly designed to
maximise goal achievement, given the goal in question
and the real world as it exists’ (pp. 38,39). Where more
than one goal exists, which is often the case in clinical
environments, then responses will be rational to the
extent that they are correctly designed to maximise net
goal achievement.
For simple clinical decisions rational responses are
relatively easy to isolate. The following critical care
scenario can be used as an example: a nurse observes a
patient collapse, establishes he has no pulse and is not
breathing. Having diagnosed (correctly) a cardiac arrest
she begins cardiopulmonary resuscitation (CPR).
In this instance the nurse’s actions can be regarded as
entirely rational. The intervention being chosen as the
means of achieving the goal of restarting the patient’s
heart and re-establishing circulation. However, if the
nurse’s first action had been to administer antibiotics
following the identification of cardiac arrest, then the
action would be less rational. Antibiotics have little
discernible effect on the electrical activity of the heart
and the circulatory system and are therefore a poor way
of achieving the goals previously mentioned.
In more complex clinical situations, with multiple
dimensions of uncertainty, the implications of Dahl and
Lindblom’s approach are that all parties involved must
agree on the goals to be achieved, match their
assumptions about the nature of the reality involved,
and appreciate the consequences of their actions given
this shared reality. Where the decision involves multiple
stakeholders then the process is necessarily complex.
The professional and patient may differ fundamentally
on the value (utility) of desired outcomes and the means
to arrive at them. This is obviously problematic in real
life clinical situations and is a major limitation on the
descriptive and normative power of a wholly rational
theoretical position. Although it should be noted that
efforts are being made to build multiple stakeholders’
values and utilities into the rational frameworks of
computerised healthcare decision support models. For
example the decision analysis in routine treatments
(DARTS) study at the University of Newcastle Upon
Tyne, UK (Robinson and Thomson, 1999).
In the nurse decision making literature there are a
number of studies which have sought to test, operationalise, or extend rational approaches to dealing with
uncertainty (Hammond et al., 1967; Aspinall, 1979;
Panniers and Kellogg Walker, 1994). What each of these
studies proposes is a narrow, ‘purist’ and normative
conceptualisation of rationality in decision making.
They derive from formal probability theory and
expected utility (EU) theory (Pitz and Sachs, 1984),
and assume a rational choice of the process and outcome
which maximises benefit and minimises costs to the
decision maker (Le Breck, 1989). Typically the probability of each possible outcome occurring is assessed
quantitatively, together with the value or utility of each
C. Thompson, D. Dowding / International Journal of Nursing Studies 38 (2001) 609–615
outcome for the decision maker. These values are then
combined to provide a value for the expected utility of
each outcome, with the rational choice being the
alternative that has the highest expected utility (Le
Breck, 1989). These normative approaches, often in the
form of decision analysis and decision support systems
are becoming more popular with the advent of evidence
based health care and increases in computing power,
portability, and accessibility (Lilford et al., 1998).
The rational approach has benefits when considering
the different types of uncertainty highlighted earlier.
Decision models based on decision analysis (utilising
decision trees) explicitly highlight the probability of a
certain intervention or treatment leading to a specific
outcome. Ideally, these probabilities should be derived
from existing empirical evidence regarding the effectiveness (or not) of the intervention in question. If this
evidence does not exist, then it is apparent in the
decision model, and other forms of probability estimation have to take place. This often involves an
estimation of the probability of a particular treatment
or intervention having an effect based on practitioner
knowledge of the situation. In both cases, not only are
the estimates of the uncertainty in the situation explicit
(in the form of given probabilities), but also the source
of the uncertainty is explicit (either from empirical
evidence, professional knowledge or both). If, at a later
date it is apparent that the estimation of probability is
inaccurate, it is possible in this model to identify where
the error lay, dealing with the third (combined) type of
uncertainty highlighted by Katz (1988).
Decision models, therefore, can be a very effective way
for practitioners to deal with the uncertainty in clinical
situations. They explicitly integrate this uncertainty into
a decision problem, and highlight the source from which
the uncertainty is derived. However, this normative
approach to decision theory fails to capture the reality of
most decision situations in nursing and health care.
Decisions in health care, and nursing in particular,
are characterised by incomplete knowledge of all
available alternatives, a lack of reliable probabilistic
data of the consequences of these alternatives and few
readily applicable techniques for reliably gauging patient
utility.
One might also argue that in the continuum of health
care delivery the majority of nurses’ work is not yet
amenable to the technical rationality of quantitativeresearch-based theory, an issue which is highlighted by
Schon (1988).
In the varied topography of professional practice,
there is high, hard ground where practitioners can
make effective use of research-based theory and
technique, and there is a swampy lowland where
situations are confusing ‘messes’ incapable of technical solution. The difficulty is that the problems of
611
the high ground are often relatively unimportant to
clients or larger society, while in the swamp are the
problems of greatest human concern. Shall the
practitioner stay on the high, hard ground where he
can practice rigorously, as he understands rigor, but
where he is constrained to deal with problems of
relatively little social importance? Or shall he descend
to the swamp where he can engage the most
important and challenging problems if he is willing
to forsake rigour (p. 67).
Even though it may not constitute the bulk of practice
it can be argued that the ‘high ground’ in nursing is of
enormous social importance. Those technical procedures
which constitute the ‘hard ground’ in clinical practice (as
opposed to the manifest functions of ‘care’) cost society
huge sums of money. For instance, the NHS bill for
deciding which leg ulcer treatment regimen is most
effective alone is around £230–400 million (NHS Centre
for Reviews and Dissemination, 1997), a large proportion of which is allocated by nurses. It is easy to
appreciate that for these particular types of decisions, a
‘technical–rational’ approach such as decision analysis
could be appropriate.
4. Bounded rationality
As implied, it will be abundantly clear to most readers
that the requirements of pure rationality do not permit
accurate description of the behaviour of individual
agents in healthcare settings. In response to this
(although speaking about society generally rather than
healthcare specifically) a number of commentators
propose that rationality can be imperfect yet still remain
rational by recognition that it is ‘bounded’ (Simon,
1982; Cherniak, 1986).
Proponents argue that individual agents are limited in
their ability to process information rationally. Individuals seeking rational solutions are expected to engage
with and develop future scenarios, and consider all
alternative actions. However they tend to consider only
a few future scenarios and often neglect obvious
alternatives, lacking awareness of the importance of
these omissions (Fischoff et al., 1978). Appraisal of
alternatives is also often seriously limited and further
compromised by hindsight bias: the phenomenon
whereby individuals claim to ‘have known it all along’
or use hindsight to exaggerate what was known about
the decision prior to having to choose a course of action
(Fischoff, 1975). All of these limitations mean that
individuals (and social groups) will make judgements
which are more often than not simply satisfactory
rather than optimal, a process known as satisficing.
Individuals’ judgements can still be considered rational
but within the limits of those cognitive parameters which
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C. Thompson, D. Dowding / International Journal of Nursing Studies 38 (2001) 609–615
act as boundaries for that rationality. This view of
rationality as bounded has been applied to such diverse
areas as computing and artificial intelligence (Russell
and Norvig, 1995), philosophy (Cherniak, 1986) and
economics (Simon, 1982).
With the recognition that rationality will always be
bounded comes a higher degree of descriptive validity
for rational approaches to dealing with the three types of
uncertainty outlined previously. If nurses consider only
a few future scenarios and appraise a limited number of
possible alternative actions, this could be explained as
being due to a lack of individual knowledge regarding
other possible courses of action and possible scenarios
}Katz’s (1988) first type of uncertainty. Alternatively,
they may be utilising all the available empirical knowledge that exists to construct scenarios and alternative
actions, but that knowledge is limited and therefore only
contributes to greater uncertainty. As before, the
uncertainty of appropriateness of actions could be due
to a combination of lack of individual knowledge and
gaps in wider empirical evidence upon which to base
actions.
In contrast to the normative approach which pervades
discussions of rationality, theories of bounded rationality attempt to describe how individuals may make
judgements and decisions in a rational way, with
reference to the ‘real world’ of social actions, of which
clinical practice is a part. However, sources of
uncertainty may not be completely acknowledged, as
individuals may not be aware of the cognitive boundaries and limiting strategies (heuristics) they are subject
to and which act to frame decision tasks and the rational
consideration of uncertainty and options. With this in
mind, and given the ‘swampy’ (Schon, 1988) nature of
much nursing practice, many nurses draw on intuitive
approaches to dealing with uncertainty and gut instinct
as a guiding force.
5. The role of intuition
Intuition, as a process of reasoning, has been defined
in various ways:
*
*
*
*
‘understanding without rationale’ (Benner and Tanner, 1987),
‘a perception of possibilities, meanings and relationships by way of insight’ (Gerrity, 1987),
‘knowledge of a fact or truth, as a whole; immediate
possession of knowledge; and knowledge independent of the linear reasoning process’ (Rew and
Barron, 1987),
‘immediate knowing of something without the
conscious use of reason’ (Schrader and Fischer,
1987),
*
*
*
‘[a] .... process whereby the nurse knows something
about a patient that cannot be verbalized, that is
verbalized with difficulty or for which the source of
knowledge cannot be determined’ (Young, 1987),
‘the decision to act on a sudden awareness of
knowledge that is related to previous experience,
perceived as a whole, and difficult to articulate’ (Rew,
2000),
‘deliberate application of knowledge or understanding that is independently distinct from the usual,
linear, and analytical reasoning process (Rew, 2000).
Intuition is characterised by a lack of ability to
explain or understand how or why judgements and
decisions have been arrived at. This makes it difficult to
communicate the basis of intuitive decisions. Theorists
claim that intuitive reasoning is indicative of a recognition of the complexity of clinical challenges. However,
because of the opaque nature of intuitive thought there
is no way of knowing if the sophisticated conceptualisations implied by this argument are actually being used in
the cognitive methods individuals deploy. Indeed,
evidence suggests that sophisticated constructs and
messages derived from ‘scientific’ enquiry may not
actually find their way into nurses’ thought processes
as nurses often fail to recognise the distinction between
scientific and experiential knowledge (Luker and Kenrick, 1992). Intuition is also context specific, leaving little
possibility that anyone other than nurses grounded in a
single clinical context can ever translate their skills to
other areas of clinical work. This is highlighted in a
study by Fischer and Fonteyn (1995) where even the
domain specific skills of intensive care unit (ICU) nurses
vary depending on the specific context in which they
work (specifically, uncertainty was heightened even
when placed in a different form of ICU). If, as some
nursing theorists imply, nursing can lay claims to being a
high-order body of knowledge that transcends clinical
boundaries, then such specificity should play less of a
role in shaping decisions. All of the above points
represent important objections to the role of an intuitive
‘reaction’ to clinical challenges as the sole basis for
professional action.
Despite these objections it is intuitive thought carried
out in ‘real time’ (within the immediate context of the
decision situation) which dominates nursing judgement
and decision making. A process referred to by Benner
as ‘thinking in action’ (Benner et al., 1998). From
observations and interviews with nurses making decisions carried out by researchers at the University of
York, it was clear that time is a very real factor in the
decision making process, with decision types fitting into
a ‘continuum’ ranging from a short time scale with little
control over the process (the level at which intuitive
response dominates) to longer time scales and greater
control over the decision process (lending itself to more
C. Thompson, D. Dowding / International Journal of Nursing Studies 38 (2001) 609–615
rational or analytical modes of thought), a finding
supported by other research into decision making (Kim,
1983; Joseph et al., 1988). Moreover, this pattern
reinforces the idea of the cognitive continuum framework proposed by Hamm (1984). As many of the
decisions made in practice are of the rapid operational
type (cf. Benner et al., 1998), one has to yield to the
possibility that intuition may be a better mode of
cognition for decision making in clinical areas than more
rational or analytical approaches } if only by virtue of
its popularity.
Intuition has been seen as a useful way of dealing with
the inherent uncertainty within clinical practice (Rew,
2000). Nursing, as an occupational group, has not yet
learned to work with the kinds of research data and
findings which help in the calculation of objective
probabilities, which, as has been shown, are a necessary
condition for rational approaches to decision making.
Indeed there is considerable evidence that nursing
practice seldom makes use of research findings at all
and that the quality of much of our research knowledge
base is poor (Hicks, 1995; Luker and Kenrick, 1995;
MacGuire, 1990; Mulhall, 1995; Pearcey, 1995; Bostrum
and Suter, 1993). If nurses did suddenly decide en masse
to utilise more analytical approaches, the probabilities
and subjective utilities used would be based on
significantly flawed, or even absent, assessments. Moreover, the kinds of research results the nursing research
industry produces are not amenable to this form of
cognition, with the majority of evidence published in
nursing journals being qualitative and descriptive in
nature (Thompson, 1999).
A further benefit of intuitive cognition arises as a
result of the complex and hands-on nature of nursing
itself. When faced with complex practical tasks,
individuals are often able to develop competence far in
advance of the ability to articulate the cues or patterns
associated with the task } they act intuitively before
being able to act rationally (Berry and Broadbent, 1984;
Lewicki et al., 1992; Reber, 1993). This runs counter to
the dominant arguments of proponents of intuitive
expertise, a vision which posits intuition as the zenith of
professional achievement achieved only after years of
systematic training and experience and when you have
‘worked through’ the confines of rational systematic
responses. However, several authors suggest that
sophisticated agents (experts) are well able to articulate
intuitive judgements post hoc often under the guise of
validation (Young, 1987; Dreyfus and Dreyfus, 1986;
Rew, 2000). This involves nurses essentially rationalising
their judgements against experience, knowledge or some
other cognitive waymark. Nurses often work in highly
stressful environments, where patients present with very
complex clinical problems and challenges. Masters
(1992) has shown that under such conditions of stress
and high uncertainty individuals who try to utilise
613
conscious rationality perform worse than those who
continue to operate intuitively.
It has been suggested that intuitive thought is an
effective way for experts to make decisions (Benner
et al., 1998) and in so doing they are assumed to
automatically utilise a large amount of personal knowledge and experience to inform such decisions. They may
also be integrating large amounts of empirical data into
the processes which inform their decisions. However, an
inherent difficulty with individuals using intuitive
thought is their inability in most cases to actually
explain how they arrived at a particular judgement or
decision (by default, often an explanation of intuition).
It is therefore difficult to ascertain whether and where
the uncertainty in such decision situations arises from.
Very recent work by Rew (2000) does little to reassure
us. Rew recognises that intuition involves synthesising
empirical, ethical, aesthetic and personal knowledge.
Moreover, she vehemently supports for the idea that
intuition constitutes ‘a cognitive skill useful to nursing’.
However, her work } whilst undoubtedly capturing the
concept of intuition } fails to reveal whether intuitive
modes of thought are more accurate or effective when
compared to rational decision styles, or again, at which
point uncertainty is addressed. Her scale items (aimed at
measuring the role of intuition in decision making)
include such statements as
I am inclined to make decisions based on a sudden flash
of insight. There are times when I feel that I know what
will happen to a patient, but I don’t know why
There are some things I suddenly know to be true about
some of my patients, but I am unable to support this
with concrete data. (Rew, 2000 p. 103).
It seems to us that these statements are ideal
representations of the sorts of expressions delivered
from practitioners just prior to demonstrating the
overconfidence, hindsight and anchoring biases or
heuristics so common to us all.
6. Conclusion
This paper has highlighted the rational and intuitive
schools of thought in dealing with the inherent
uncertainty which is a component of the complex
clinical decisions faced by nurses and other health care
workers. It is generally assumed that perhaps the best
way to deal with such uncertainty is to recognise it and
to build it into rational models, such as those
represented by formal decision analysis. By recognising
the inherent variability in decision situations (through
the use of probability assessment), uncertainty can be
‘controlled’ and therefore the decision which is subsequently made can be seen to be the most rational.
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C. Thompson, D. Dowding / International Journal of Nursing Studies 38 (2001) 609–615
However, this paper has also highlighted that this may
not be appropriate for much of nursing practice, where
clinical situations need rapid responses, and much of the
data needed for a more ‘rational’ approach do not exist.
Intuitive judgement can offer much in terms of enabling
nurses to deal with the uncertainty of the situations they
face, and provide a coping mechanism for dealing with
the contextual factors over which nurses have little
control (stress, limited time to make decisions, and a
relative lack of requirement to explain their choices). As
is suggested by Hamm (1984) the context of the decision
situation needs to be taken into account, so that the
cognitive processes used by individuals match the tasks
set them. In this instance, perhaps intuitive judgement is
the most practical way for nurses to deal with uncertain
clinical situations.
However, whilst there is some evidence to suggest that
at the cognitive level and in laboratory tests individuals
perform better when drawing on intuition, this level of
confidence is missing from pragmatic or real life studies.
Few studies address the essential research question, ‘‘is
intuition versus rational decision support more effective
for a given clinical challenge?’’ They also fail to address
where uncertainty in clinical situations may arise, and if
it exists how clinical practitioners identify issues which
can be sources of such uncertainty, such as their own
lack of knowledge, or an adequate empirical basis for
their decisions. If nursing is to truly control the quality
of its contribution to healthcare then the characteristics
of uncertainty in practice must be described and good
quality evaluation of cognitive and practical strategies
must be designed, carried out and, equally importantly,
published } no matter how uncomfortable the results
might be for the profession.
Acknowledgements
We wish to thank Dr Nicky Cullum, Professor David
Thompson, Dorothy McCaughan and the research team
at the Centre for Evidence Based Nursing, York and the
participants of the Universities of Stirling, York and
Newcastle, Nurse Decision Making Symposium in June
1999 for the debates which informed the development of
this paper.
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