Masterarbeit, 2023
74 Seiten, Note: A
1. Introduction
1.2 Goals
1.3 Rationale
1.4 Description
1.5 Summary
2. Review of the Literature
2.1 The Concept of Bounded Rationality
2.2 Total Error and Unwanted Variability in Judgement
2.3 Kahneman’s view of Total Error: identifying ‘Noise’ in the real world
2.4 The Role of Mood, Personality and Emotions in Decision-making
2.5 Decisions under critical Conditions: The Case for Emergency Medicine
2.6 Research Questions and Hypotheses
3. Method
3.1 Study Design
3.2 Sampling
3.3 Drafting and development of hypothetical vignettes
3.5 Measuring the Effect of Mood and Personality
3.6 Procedure
4. Results
4.1 Population description
4.2 Professional nurses’ differences in their judgement of emergency case scenarios
4.3 Qualitative Data Analysis
4.4 Consistency in Justifying Judgements
4.5 Observations outside the main research scope
4.6 Summary
5. Discussion
5.1. Interpretation of Key Findings
5.2 Opportunities and Implications for Future Research
5.3 Contribution to Knowledge, Theory and Practice
5.4 Conclusion
This study explores the prevalence and impact of judgemental error and 'noise' in professional clinical decision-making within emergency medical settings. The research aims to evaluate how time pressure, distractions, and individual personality traits influence the consistency of triage judgements made by emergency nurses, ultimately seeking to understand the variance in these critical decisions and how management might mitigate such errors through simulation-based research.
2.3 Kahneman’s view of Total Error: identifying ‘Noise’ in the real world
“Most of the time professionals have confidence in their own judgement. They expect that colleagues would agree with them, and they never find out whether they actually do. In most fields in the real world, a judgement may never be evaluated against a true value and at most will be subjected to vetting by another professional who is considered a respect-expert. Only occasionally will professionals be faced with a surprising disagreement, and when it happens, they will generally find reasons to view it as an isolated case. The authors acknowledge that true experts exist in domains where their skills can be verified and compared with the results; such as Chess Masters” (p. 369).
Popularised in 2016, the publication amply illustrates the scale of the problem of inconsistent judgements, backing their case on the presence of system noise, a phenomenon often overlooked (Harvard Business Review, 2016). The authors view bias as “systematic errors of judgement” and that “bias is error we can often see and even explain” (Kahneman et al., 2021, p. 229), they point out that ‘judgement’ should be understood as “a form or measurement in which the instrument is a human mind”. Like physical measurements, it is the process of assigning a score to an object, but unlike physical measurements, the score does not have to be a number - it is the process of assigning a score that results in noise. To help readers conceptualise this distinction better, a visual and an equation (the mean squared error is equal to bias squared plus noise squared) are portrayed, and their argument is sustained by a number of real-world scenarios and studies, where the variability in judgements of all kinds is explored - from court sentencing to insurance underwriting, to medical diagnosis.
1. Introduction: Outlines the importance of identifying errors in decision-making and establishes the research purpose of exploring ‘noise’ in clinical judgements through simulation.
2. Review of the Literature: Examines theories of bounded rationality, the distinction between bias and noise, and how personality and mood influence professional decision-making.
3. Method: Describes the experimental design, including how a web-based simulator was used to measure nurses' judgemental responses under varied stressors.
4. Results: Details the demographic findings and presents quantitative and qualitative data regarding variables affecting triage accuracy and justification consistency.
5. Discussion: Contextualizes the findings within existing theory, discusses research limitations, and identifies implications for future study and clinical practice.
Bounded Rationality, Judgemental Error, Variance Analysis, System Noise, Healthcare Management, Triage, Simulation-based Research, Cognitive Bias, Clinical Decision-making, Emergency Medicine, Intrasubjective Variability, Personality Traits, Decision Hygiene, Diagnostic Error, Total Analytic Error
The study investigates the unwanted variability, or 'noise', in professional clinical judgements made by emergency nurses when assessing fictitious patient cases under conditions of varying stress.
The work covers behavioral science, specifically decision theory, the psychology of judgment, emergency medicine triage practices, and the application of simulation-based research in management.
The primary goal is to deploy a 'noise audit' to capture decision outcomes, analyze variance resulting from judgemental errors, and help hospital management understand how to minimize such inaccuracies in clinical settings.
The research employed an experimental, blinded, randomized controlled trial using simulation-based methods, comparing a control group against two groups challenged by time pressure and cognitive distractions.
The main part of the document reviews existing literature on 'noise' and bias, outlines the experimental design and data collection processes, presents results on judgemental consistency, and analyzes the role of individual personality traits.
Key terms include Bounded Rationality, Judgemental Error, System Noise, Variance Analysis, Triage, and Simulation-based Research.
The study suggests that participants under time pressure and distraction performed better than the control group, potentially linked to the Yerkes-Dodson Law, which posits that performance increases with mental arousal up to a certain point.
The noise audit allows organizations to objectively measure the inconsistency in decisions made by professionals, providing a practical tool to improve systemic decision-making processes rather than focusing only on individual performance metrics.
Triage systems are essential for assessing patient urgency and prioritizing care; inconsistent applications of these systems can lead to increased mortality rates and operational inefficiencies in emergency departments.
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