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As nurses, we all make clinical decisions. Each shift, we are required to make judgements about the needs of our patients and decisions about what interventions will assist in their recovery. As our knowledge and experience grow, so does our ability to recognize intuitive feelings and to interpret and analyse patient situations to improve our decision-making.

Regardless of the level of expertise, nurses need to recognize that the decisions they make have a significant impact on healthcare outcomes and the experiences of their patients (Dowding & Thompson 2003). From the beginning of our education we are taught and encouraged to base our professional practice on sound evidence and to be transparent about our clinical judgements and decisions. However, the ability to synthesize and prioritize information from various sources into appropriate and meaningful interventions for the patient is akin to ‘juggling jelly’ (Thompson & Dowding 2002). In fact, every part of a nursing assessment including clinical history and examination can be viewed as a diagnostic test (Gill et al. 2005). Furthermore, learning to reason and think critically in professional practice is as much a competency as knowing the facts about a disease or a particular technique for delivering care (Mullally 2002).

In addition to measuring the outcomes of decision-making, there is increasing interest in understanding how nurses actually make decisions in clinical practice. The literature identifies many different decision-making models which can be categorized under three different theories. Table 1 presents three examples of decision-making theories and models: decision analysis, hypotheticodeductive reasoning and Bayes’ theorem.

Table 1.   Decision-making theories and models
TheoryExample model
NormativeDecision analysis
Theories that are concerned with how good a judgement or decision is. What people should do (in theory)A model of the problem is constructed, showing the available options which are to be considered and the consequences of following each. An attempt is then made to assign a probability to possible outcomes (Harbison 1991)
DescriptiveHypotheticodeductive reasoning
Theories that try to describe how individuals reach their judgements or decisions. What people actually do or have doneThe procedure of testing hypotheses and then modifying them as a result of the outcome of the test (Evans 1983)
PrescriptiveBayes’ theorem
Theories that try to improve the judgements and decisions of individuals. Draws on normative and descriptive theories. What people – should and can doA statistical model that describes the way in which judgements are revised in the light of new information (Taylor 2000)

Many different methods have been used to investigate decision-making. Observation, interviewing and surveys may be appropriate techniques if the outcome of decision-making is under investigation. However, these methods of data collection may be problematic if the research is examining the actual thought processes which an individual uses to reach a decision. Many would argue that researching what individuals think they do compared to how they actually behave is challenging and introduces concerns with accuracy and validity (Lamond et al. 1996). The ‘think aloud’ technique, used in this study, is therefore often used to examine thought processes utilized by subjects.

The ‘think aloud’ technique has a long history in psychological research and is accepted as a valid means of accessing concurrent human reasoning for the purpose of understanding , reasoning and information processing (Newall & Simon 1972, Evans 1983). Whilst solving a problem, subjects are asked to verbalize everything they are thinking. Lamond et al. (1996) highlight that the main assumption in the ‘think aloud’ approach is that the scenarios used in the research adequately represent reality and, therefore, the output should be valid illustrations of an individual subject's thought processes. Twycross and Powls (2006) used real-life medical cases and experts to formulate their scenarios; however, they were not explicit with the form of presentation of the information given to the subjects in the study. Were the scenarios delivered to the participants verbally or in a written or video format? Does the delivery of the scenario, apart from the actual patients themselves, alter the decision-making process? Lamond et al. (1996) hypothesized that information presented in an unfamiliar format will not allow subjects to process information as they would normally and, therefore, the output from that scenario would not be valid. Taylor (2000) also summarized some of the shortcomings of the ‘think aloud’ technique and points out that simply instructing the participants to describe the cognitive process may affect their performance.

The results of this study found that their participant nurses used hypotheticodeductive decision-making with backward reasoning strategies (Twycross & Powls 2006). This means that the nurses assumed their conclusion was true and then reasoned back to the evidence. In contrast, forward reasoning is a chain of inferences from data towards an incremental refinement of hypotheses resulting in a solution. This is claimed as one of the hallmarks of expert clinical decision-making (Anderson 1995). Of particular interest was that nurses with all levels of experience used backward reasoning strategies, challenging the old notion that experienced nurses make better decisions. What this suggests is that experience is a necessary but not sufficient condition for expertise.

Also evident in this study is that less experienced nurses tend to collect numerical data (e.g. patient-controlled analgesia, fluid balance and medication data) in preference to physiological observations and non-verbal cues in making their assessment. Previous studies report that, in observing and teaching developing clinicians to collect patient data, the beginner often places high value on knowing how to use patient-related technology and associated numerical data in preference to mastering simple observational skills in the assessment of the physical condition of the patient (Ramsbotham 2004). Nurses spending an inordinate amount of time in the quest for technological mastery may do so to the detriment of acquiring clinical knowledge and skills with which to inform clinical judgement (Benner 1984). To reverse this phenomenon, Ramsbotham (2004) has proposed, and is currently testing, a practice model based on three phases, namely information seeking, critical thinking and clinical judgement to mimic expert nurses’ behaviour in paediatric assessment. This practice model seeks to assist nurses to collect observed and subjective data first and then uses the numerical data and available technology to confirm developed hypotheses of patient condition rather than in the reverse order.

Some people might argue that it should not matter what decision-making model or strategy is used, as long as the outcome is appropriate. Although Twycross and Powls (2006) used real-life clinical scenarios to describe the process of clinical decision-making in their study, they did not measure the quality of the outcome. Does the method or strategy for decision-making influence the outcome in these patients? Given that nurses mostly operate in environments that are characterized by uncertainty, some authors suggest that defining decisions as good or bad may be difficult (Buckingham & Adams 2000, Dowding & Thompson 2003). Baron (2000) suggests that the best decisions are those yielding the best outcomes for achieving patient's goals; although this measure of ‘best’ may be difficult to operationalize in a paediatric setting where many children are not able to articulate needs or goals. The alternative to measuring the outcome (good or bad) is to examine the process by which the clinician has made the decision. Dowding and Thompson (2003) add to this debate by suggesting that this also, is, challenging, ‘as it ignores the outcome of the decision and raises the issue of what makes a ‘‘good’’ decision process’ (p. 54). Considering these comments, perhaps future research in this area should evaluate not only the decision-making process but also the outcome within the same context. Additionally, do researchers need to consider a gold standard to which the process and outcome will be compared?

Nursing education has attempted to teach decision-making using problem-based learning. Descriptive theories have been more influential in curriculum design and thus problem-based learning was developed from a hypotheticodeductive approach. Unfortunately, educational institutions have not always recognized the need to teach the decision-making theories and their strategies. Round (2001) argues that it is difficult to teach students (novices) to think like experts, as they do not have the experience or knowledge structure to do this. Furthermore, if nurses are only exposed to one model of decision-making, they will have limited opportunity to develop the ability to make decisions via alternative means. The ability to use various models of decision-making in different scenarios may be important. Some literature suggests that no one decision-making theory can be applied universally and that different theories are appropriate depending on their context and the experience of the clinicians. Moreover, theories often overlap in different situations (Round 2001, Elstein & Szhwarz 2002). This raises the question of whether decision-making can be taught or whether it can only be learned experientially; and, are clinical decision-making skills specific or subject specific? It is recognized by some that decision-making, along with other important attributes such as critical thinking, is both domain specific and idiosyncratic. Teaching general skills to enhance someone's critical thinking or decision-making ability may therefore be inappropriate as general critical thinking or decision-making ability does not exist. Voss et al. (1991) share this view and reviewed the research on the solving of ill-structured problems by novices and experts. They report that the ability to use problem-solving or decision-making strategies was greater when the individual had developed stronger intellectual ability or more formal education in subject-matter content rather than a content-free reasoning course. Schuwirth (2002) comments that learning programmes on clinical reasoning may be more effective than didactic teaching programmes and suggests that educational interventions should be based on providing the learner with feedback and should emphasize critical reflection by the teacher on the thought processes of the student.

It appears that it would also be important for nurses to be critical thinkers if they are to be effective clinical decision-makers; however, research demonstrates that the ability to think critically may not necessarily improve one's clinical decision-making ability (Girot 2000, Hicks et al. 2004). If nurses are expected to be competent decision-makers, the nursing profession has a responsibility to enhance the clinical decision-making abilities of its members. One means of doing this has been to identify the factors that might affect problem-solving and decision-making. These factors may include individual variables, such as experience and knowledge, creative thinking ability, education, personality and self-concept, as well as environmental and situational stressors (O'Reilly 1993, Hoffman et al. 2004). These factors may serve to enhance or impede clinical decision-making and, by recognising the nature and existence of certain barriers, strategies may be developed to overcome them.

Twycross and Powls’ (2006) study on paediatric nurses’ decision-making contributes to the literature by providing us with information related to the processes and information sources used to make clinical decisions. Whilst the nursing profession has not fully investigated what constitutes quality in decision-making, this study contributes to the cognitive theories in thinking and reasoning. It also provides us with ideas towards establishing what counts as quality in the way we decide on the care that we provide.

References

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