scholarly journals How Human Decision-making Biases Influence Health Outcomes in Patient Care

2021 ◽  
Vol 29 (2) ◽  
pp. 64-72
Author(s):  
Rainer Sibbel ◽  
Angelina Huber
Keyword(s):  
Decision Making ◽  
Healthcare Professionals ◽  
Cognitive Biases ◽  
Meta Analysis ◽  
Delayed Diagnosis ◽  
Medical Decision ◽  
Future Research ◽  
Literature Study ◽  
Human Decision ◽  
The Impact

Purpose: Medical treatments and medical decision making are mostly human based and therefore in risk of being influenced by cognitive biases. The potential impact could lead to bad medical outcome, unnecessary harm or even death. The aim of this comprehensive literature study is to analyse the evidence whether healthcare professionals are biased, which biases are most relevant in medicine and how these biases may be reduced. Approach/Findings: The results of the comprehensive literature based meta-analysis confirm on the one hand that several biases are relevant in the medical decision and treatment process. On the other hand, the study shows that the empirical evidence on the impact of cognitive biases on clinical outcome is scarce for most biases and that further research is necessary in this field. Value/Practical Implications: Nevertheless, it is important to determine the extent to which biases in healthcare professionals translate into negative clinical outcomes such as misdiagnosis, delayed diagnosis, or mistreatment. Only this way, the importance of incorporating debiasing strategies into the clinical setting, and which biases to focus on, can be properly assessed. Research Limitations/Future Research: Though recent literature puts great emphasis on cognitive debiasing strategies, there are still very few approaches that have proven to be efficient. Due to the increasing degree of specialization in medicine, the relevance of the different biases varies. Paper type: Theoretical.

scholarly journals The Influence of Cognitive Biases in Production Planning and Control: Considering the Human Factor for the Design of Decision Support Systems

2021 ◽  
Author(s):  
Julia Bendul ◽  
Melanie Zahner
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Production Planning ◽  
Cognitive Biases ◽  
Production Planning And Control ◽  
Due Date ◽  
Planning And Control ◽  
Human Decision ◽  
And Control ◽  
The Impact

Production planning and control (PPC) requires human decision-making in several process steps like production program planning, production data management, and performance measurement. Thereby, human decisions are often biased leading to an aggravation of logistic performance. Exemplary, the lead time syndrome (LTS) shows this connection. While production planners aim to improve due date reliability by updating planned lead times, the result is actually a decreasing due date reliability. In current research in the field of production logistics, the impact of cognitive biases on the decision-making process in production planning and control remains at a silent place. We aim to close this research gap by combining a systematic literature review on behavioral operation management and cognitive biases with a case study from the steel industry to show the influence of cognitive biases on human decision-making in production planning and the impact on logistic performance. The result is the definition of guidelines considering human behavior for the design of decision support systems to improve logistic performance.

Systems Simulation of Design for End-of-Life Recovery Under Uncertainty

2013 ◽  
Author(s):  
Sara Behdad ◽  
Aaron T. Joseph ◽  
Deborah Thurston
Keyword(s):  
Decision Making ◽  
Product Design ◽  
End Of Life ◽  
Reverse Logistics ◽  
Cognitive Biases ◽  
Design Features ◽  
Product Life ◽  
Return Flows ◽  
Human Decision ◽  
The Impact

Design for End of Life (DfEOL) recovery is a complex process that requires consideration of various design aspects including design for product life extension, design for reliability, design for disassembly, design for components reuse, and design for recyclability. There is a need for an analytical tool that helps designers integrate all these design aspects together and moreover investigate the impact of design features on the recovery network. The designer needs to predict the variability that design features bring into the reverse logistics network, including the variability in the amount, quality and timing of return flows and uncertainty in the remanufacturing operations such as disassembly time. In addition to the product design, the EOL recovery system performance is also affected by human decision making. The willingness of customers to keep used products in storage, the qualitative criteria used by remanufacturing companies to sort and categorize the returned used products and the manual disassembly operations influenced by the operator’s cognitive biases are examples of human decision making processes that impact product recovery. The nonlinear character of reverse logistics system along with the dynamic complexity as a result of uncertainties and cognitive biases are particularly troublesome. This paper establishes a simulation-based System Dynamics (SD) model of product life cycle to check interrelationship among product design features and their impacts on the amount, quality and timing of the return flows to the waste stream. The complex product take back process and recovery operations are modeled. Designers could use the results of the model to compare different design scenarios and to receive information about what design features bring problems or create opportunities for EOL recovery.

scholarly journals Decision Aiding to Overcome Biases in Object Identification

2012 ◽  
Vol 2012 ◽  
pp. 1-7 ◽  
Author(s):  
Mary Fendley ◽  
S. Narayanan
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Cognitive Biases ◽  
Target Identification ◽  
Object Identification ◽  
Identification Accuracy ◽  
Human Decision ◽  
The Impact

Human decision makers typically use heuristics under time-pressured situations. These heuristics can potentially degrade task performance through the impact of their associated biases. Using object identification in image analysis as the context, this paper identifies cognitive biases that play a role in decision making. We propose a decision support system to help overcome these biases in this context. Results show that the decision support system improved human decision making in object identification, including metrics such as time taken to identify targets in an image set, accuracy of target identification, accuracy of target classification, and quantity of false positive identification.

Cognitive biases and decision-making strategies in times of change: a systematic literature review

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Chiara Acciarini ◽  
Federica Brunetta ◽  
Paolo Boccardelli
Keyword(s):  
Decision Making ◽  
Literature Review ◽  
Systematic Literature Review ◽  
Cognitive Biases ◽  
Future Research ◽  
Strategic Decisions ◽  
Data Set ◽  
Content Type ◽  
The Impact

PurposeIn a work environment marked by unprecedented complexity, volatility and ambiguity, managers must accomplish their objectives while navigating many challenges. This paper aims to investigate potential interrelations among environmental transformations, cognitive biases and strategic decisions. In particular, the purpose of the study is to crystallize the state of art on the impact of cognitive biases on strategic decisions, in the context of environmental transformations.Design/methodology/approachThe authors have conducted a systematic literature review to identify existing relevant work on this topic and to detect potential avenues for future research.FindingsThe findings highlight how decision-making is influenced and enabled by internal (e.g. perception) and external factors (e.g. digitalization). Specifically, the strategic role of cognitive biases appears to be crucial when investigating the related impact on strategic decisions in times of environmental transformation.Practical implicationsImplications are drawn for scholars and practitioners interested in evaluating the role of specific decision-making determinants for the formation and implementation of strategic decisions. In this sense, we stress that decision-makers need to manage their cognitive biases and select the right information out of a wide data set in order to adapt to environmental transformations.Originality/valueBy systematizing the literature review, potential interrelations among environmental transformations, cognitive biases and strategic decisions are identified. Furthermore, the primary phases that drive the decision-making process are proposed (analysis, decision, onboarding and control).

De-Biasing Legal Factfinders

2021 ◽  
pp. 395-410
Author(s):  
Frank Zenker
Keyword(s):  
Decision Making ◽  
Special Reference ◽  
Cognitive Biases ◽  
Confirmation Bias ◽  
Future Research ◽  
Research Needs ◽  
Base Rate Neglect ◽  
Human Decision ◽  
Social Biases ◽  
Evidential Basis

This chapter examines the psychological studies of biases and de-biasing measures in human decision-making with special reference to adjudicative factfinding. Research shows that factfinders are prone to cognitive biases (such as anchoring, framing, base-rate neglect, and confirmation bias) as well as social biases. Driven by this research, multiple studies have examined the extent to which those biases can be mitigated by de-biasing measures like “consider the opposite” and “give reasons.” After a brief overview of the research, the author points to the problematic evidential basis and identifies future research needs, and concludes that empirical research on de-biasing measures has so far delivered less than one would hope for.

scholarly journals Spontaneous intracerebral hemorrhage and the challenge of surgical decision making: a review

2013 ◽  
Vol 34 (5) ◽  
pp. E1 ◽  
Author(s):  
Michael L. Kelly ◽  
Daniel P. Sulmasy ◽  
Robert J. Weil
Keyword(s):  
Decision Making ◽  
Intracerebral Hemorrhage ◽  
Medical Care ◽  
Cognitive Biases ◽  
Treatment Strategies ◽  
Medical Decision ◽  
Future Research ◽  
Spontaneous Intracerebral Hemorrhage ◽  
Surgical Decision ◽  
Surgical Decision Making

Decision making for patients with spontaneous intracerebral hemorrhage (ICH) poses several challenges. Outcomes in this patient population are generally poor, prognostication is often uncertain, and treatment strategies offer limited benefits. Studies demonstrate variability in the type and intensity of treatment offered, which is attributed to clinical uncertainty and habits of training. Research has focused on new techniques and more stringent evidence-based selection criteria to improve outcomes and produce consensus around treatment strategies for patients with ICH. Such focus, however, offers little description of how ICH treatment decisions are made and how such decisions reflect patient preferences regarding medical care. A growing body of literature suggests that the process of decision making in ICH is laden with bias, value assumptions, and subjective impressions. Factors such as geography, cognitive biases, patient perceptions, and physician characteristics can all shape decision making and the selection of treatment. Such factors often serve as a barrier to providing patient-centered medical care. In this article, the authors review how surgical decision making for patients with ICH is shaped by these decisional factors and suggest future research pathways to study decision making in ICH. Such research efforts are important for establishing quality guidelines and pay-for-performance measures that reflect the preferences of individual patients and the contextual nature of medical decision making.

A Study on Outcome Framing and Risk Attitude in Engineering Decisions Under Uncertainty

2015 ◽  
Vol 137 (8) ◽  
Author(s):  
Sean D. Vermillion ◽  
Richard J. Malak ◽  
Rachel Smallman ◽  
Julie Linsey
Keyword(s):  
Decision Making ◽  
Cognitive Biases ◽  
Risk Attitude ◽  
Future Research ◽  
Project Outcomes ◽  
Positive Gain ◽  
Central Activity ◽  
The Difference ◽  
The Impact ◽  
Risky Option

Decision making is a central activity in the design of an engineered system and has a significant impact on project outcomes. Although much research exists on engineering decision making, relatively little addresses behavioral aspects of how engineers make decisions. This is a potentially significant gap, as factors such as the way in which information is communicated and presented to engineers can matter greatly. For example, cognitive psychology has demonstrated that the choices people make can be strongly influenced by how the options are framed even when the different framings are mathematically equivalent. This paper explores the impact of framing on the types of decisions engineers face. Given engineers' intense mathematical training, it is possible that they are less susceptible to framing effects. Thus, there is motivation to determine whether relevant findings can be replicated in an engineering context. This paper presents a set of positively and negatively framed design scenarios. Consistent with prior experiments, engineers in the positive (gain) framed scenarios were more likely to choose the less risky option for three of the four scenarios. One of the scenarios did not show this bias but did include a longer time horizon which likely explains the difference. Engineers were risk neutral when the scenarios were presented negatively (loss) framed, which is in contrast to prior experiments on nonengineering populations. These results motivate the future research into the impact of framing on engineering decision making and effective guidelines on how to create engineering processes and tools that leverage or avoid inducing cognitive biases.

The impact of patient narratives on medical students’ perceptions of shared decision making: A randomized controlled trial

2020 ◽  
Author(s):  
Martina Bientzle ◽  
Marie Eggeling ◽  
Simone Korger ◽  
Joachim Kimmerle
Keyword(s):  
Decision Making ◽  
Medical Students ◽  
Shared Decision Making ◽  
Medical Training ◽  
Controlled Trial ◽  
Future Research ◽  
Shared Decision ◽  
Randomized Controlled ◽  
Information Text ◽  
The Impact

BACKGROUND: Successful shared decision making (SDM) in clinical practice requires that future clinicians learn to appreciate the value of patient participation as early as in their medical training. Narratives, such as patient testimonials, have been successfully used to support patients’ decision-making process. Previous research suggests that narratives may also be used for increasing clinicians’ empathy and responsiveness in medical consultations. However, so far, no studies have investigated the benefits of narratives for conveying the relevance of SDM to medical students.METHODS: In this randomized controlled experiment, N = 167 medical students were put into a scenario where they prepared for medical consultation with a patient having Parkinson disease. After receiving general information, participants read either a narrative patient testimonial or a fact-based information text. We measured their perceptions of SDM, their control preferences (i.e., their priorities as to who should make the decision), and the time they intended to spend for the consultation.RESULTS: Participants in the narrative patient testimonial condition referred more strongly to the patient as the one who should make decisions than participants who read the information text. Participants who read the patient narrative also considered SDM in situations with more than one treatment option to be more important than participants in the information text condition. There were no group differences regarding their control preferences. Participants who read the patient testimonial indicated that they would schedule more time for the consultation.CONCLUSIONS: These findings show that narratives can potentially be useful for imparting the relevance of SDM and patient-centered values to medical students. We discuss possible causes of this effect and implications for training and future research.

Focal Concerns and Police Decision Making in Sexual Assault Cases: A Systematic Review and Meta-Analysis

2021 ◽  
pp. 152483802199128
Author(s):  
David S. Lapsey ◽  
Bradley A. Campbell ◽  
Bryant T. Plumlee
Keyword(s):  
Systematic Review ◽  
Decision Making ◽  
Sexual Assault ◽  
Meta Analysis ◽  
The United States ◽  
Empirical Literature ◽  
Campbell Collaboration ◽  
Focal Concerns ◽  
Police Decision Making ◽  
The Impact

Sexual assault and case attrition at the arrest stage are serious problems in the United States. Focal concerns have increasingly been used to explain police decision making in sexual assault cases. Because of the popularity of the focal concerns perspective and potential to inform evidence-based training, a systematic review and meta-analysis are needed to condense the literature. In this study, we assess the overall strength of the relationship between focal concerns variables and police decisions to arrest in cases of sexual assault. Our assessment of the effects of focal concerns variables on arrest decision making in sexual assault cases followed the systematic review protocols provided by the Campbell Collaboration of Systematic Reviews. Specifically, we used the Campbell Collaboration recommendations to search empirical literature and used meta-analysis to evaluate the size, direction, and strength of the impact of focal concerns variables on arrest decisions. Our search strategy detected 14 eligible studies and 79 effect sizes. The meta-analysis found several robust and statistically significant correlates of arrest. In fact, each focal concerns concept produced at least one robust arrest correlate. Overall, focal concerns offers a strong approach for explaining police decisions in sexual assault cases. Although practical concerns and resource constraints produced the strongest arrest correlates, results show the importance of additional case characteristics in officers’ decision to arrest.

Errors in Surgical Neuropathology and the Influence of Cognitive Biases: The Psychology of Intelligence Analysis

2006 ◽  
Vol 130 (5) ◽  
pp. 613-616 ◽  
Author(s):  
Roger E. McLendon
Keyword(s):  
Decision Making ◽  
Cognitive Psychology ◽  
Medical Decision Making ◽  
Cognitive Biases ◽  
Correct Diagnosis ◽  
Data Sources ◽  
Medical Decision ◽  
Intelligence Analysis ◽  
First Impression ◽  
Decision Making Processes

Abstract Context.—A significant difficulty that pathologists encounter in arriving at a correct diagnosis is related to the way information from various sources is processed and assimilated in context. Objective.—These issues are addressed by the science of cognitive psychology. Although cognitive biases are the focus of a number of studies on medical decision making, few if any focus on the visual sciences. Data Sources.—A recent publication authored by Richards Heuer, Jr, The Psychology of Intelligence Analysis, directly addresses many of the cognitive biases faced by neuropathologists and anatomic pathologists in general. These biases include visual anticipation, first impression, and established mindsets and subconsciously influence our critical decision-making processes. Conclusions.—The book points out that while biases are an inherent property of cognition, the influence of such biases can be recognized and the effects blunted.

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