Abstract
BackgroundThe validity of studies describing clinicians’ judgements based on their responses to paper cases is questionable, because - commonly used - paper case simulations only partly reflect real clinical environments. In this study we test whether paper case simulations evoke similar risk assessment judgements to the more realistic simulated patients used in high fidelity physical simulations.Methods97 nurses (34 experienced nurses and 63 student nurses) made dichotomous assessments of risk of acute deterioration on the same 25 simulated scenarios in both paper case and physical simulation settings. Scenarios were generated from real patient cases. Measures of judgement ‘ecology’ were derived from the same case records. The relationship between nurses’ judgements, actual patient outcomes (i.e. ecological criteria), and patient characteristics were described using the methodology of judgement analysis. Logistic regression models were constructed to calculate Lens Model Equation parameters. Parameters were then compared between the modeled paper-case and physical-simulation judgements.ResultsParticipants had significantly less achievement (ra) judging physical simulations than when judging paper cases. They used less modelable knowledge (G) with physical simulations than with paper cases, while retaining similar cognitive control and consistency on repeated patients. Respiration rate, the most important cue for predicting patient risk in the ecological model, was weighted most heavily by participants.ConclusionsTo the extent that accuracy in judgement analysis studies is a function of task representativeness, improving task representativeness via high fidelity physical simulations resulted in lower judgement performance in risk assessments amongst nurses when compared to paper case simulations. Lens Model statistics could prove useful when comparing different options for the design of simulations used in clinical judgement analysis. The approach outlined may be of value to those designing and evaluating clinical simulations as part of education and training strategies aimed at improving clinical judgement and reasoning.
Highlights
The validity of studies describing clinicians’ judgements based on their responses to paper cases is questionable, because - commonly used - paper case simulations only partly reflect real clinical environments
Participants Ninety-seven (34 experienced and 63 student) UK nurses participated in both the paper case and high fidelity physical simulation arms of the experiment
All the students had been in the simulation facilities numerous times for learning activities in the previous study periods and they have completed a range of learning activities, using the simulation facilities, on the topic of “managing the deteriorating patient” – these include, monitoring a patient’s vital signs, clinical risk assessment and cardiopulmonary resuscitation
Summary
The validity of studies describing clinicians’ judgements based on their responses to paper cases is questionable, because - commonly used - paper case simulations only partly reflect real clinical environments. A clinician’s predictions of that criterion are based on the same clinical features. The Lens Model Equation describes the reliability and the accuracy of the clinician’s judgement via five decompositional concepts [6]: predictability (Re); cognitive control (Rs); achievement (ra); policy matching (G); and unmodeled knowledge (C). Predictability (Re) reflects the degree to which a model predicts the value of the ecological criterion from the clinical features. Cognitive control (Rs) reflects how well a similar model predicts the clinician’s judgements based on the same features; Rs examines the consistency with which the clinician applies a policy to their judgments. Unmodeled knowledge (C) measures the degree to which the residuals from the model of the clinician’s judgements reflect the unmodeled (residual) components of the ecology
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