Clinical Decision Making in Familiar Cases: A Model of the Process and Implications for Practice

1996 ◽  
Vol 59 (5) ◽  
pp. 217-222 ◽  
Author(s):  
Rosemary Hagedorn
Keyword(s):  
Decision Making ◽  
Medical Decision Making ◽  
Clinical Decision Making ◽  
Occupational Therapists ◽  
Clinical Decision ◽  
Medical Decision ◽  
Physical Practice ◽  
Problem Space ◽  
Schematic Processing ◽  
Decision Making Processes

This qualitative study describes the clinical reasoning and decision-making processes used by experienced occupational therapists in physical practice when deciding on the first intervention in a familiar type of case. The main finding was that therapists use schematic processing to speed the identification of problems and to indicate potential solutions and actions. Such processing is rapid and automated. Theory appears to become embedded in practice to the point where the therapist is no longer conscious of using it. A model of the mental problem space generated by therapists during decision making is proposed and the implications for practice are discussed. This model may help to explain some of the differences observed in the reasoning of novice and experienced practitioners. The sample is too small to permit generalisation, but the findings are compatible with theories of cognition and problem solving and also with the results of studies into medical decision making.

scholarly journals Value-impregnated factual claims may undermine medical decision-making

2018 ◽  
Vol 13 (3) ◽  
pp. 151-158 ◽  
Author(s):  
Niels Lynøe ◽  
Gert Helgesson ◽  
Niklas Juth
Keyword(s):  
Decision Making ◽  
Medical Decision Making ◽  
Clinical Decision Making ◽  
Negative Impact ◽  
Personal Values ◽  
Healthcare Providers ◽  
Clinical Decision ◽  
Medical Decision ◽  
Clinical Decisions ◽  
Soft Laws

Clinical decisions are expected to be based on factual evidence and official values derived from healthcare law and soft laws such as regulations and guidelines. But sometimes personal values instead influence clinical decisions. One way in which personal values may influence medical decision-making is by their affecting factual claims or assumptions made by healthcare providers. Such influence, which we call ‘value-impregnation,’ may be concealed to all concerned stakeholders. We suggest as a hypothesis that healthcare providers’ decision making is sometimes affected by value-impregnated factual claims or assumptions. If such claims influence e.g. doctor–patient encounters, this will likely have a negative impact on the provision of correct information to patients and on patients’ influence on decision making regarding their own care. In this paper, we explore the idea that value-impregnated factual claims influence healthcare decisions through a series of medical examples. We suggest that more research is needed to further examine whether healthcare staff’s personal values influence clinical decision-making.

DISCUSSION AGENDA FOR THE SESSION ON MEDICAL DECISION MAKING and MINUTES OF A GROUP DISCUSSION ON CLINICAL DECISION MAKING

1988 ◽  
pp. 599-612
Author(s):  
Milton C. Weinstein ◽  
Harvey V. Fineberg ◽  
Barbara J. McNeil ◽  
Stephen G. Pauker ◽  
Robert J. Quinn
Keyword(s):  
Decision Making ◽  
Medical Decision Making ◽  
Clinical Decision Making ◽  
Group Discussion ◽  
Clinical Decision ◽  
Medical Decision

scholarly journals Development and Evaluation of a Crowdsourcing Platform for Education and Evidence-Based Medical Decision-Making

2019 ◽  
Vol 43 (1 suppl 1) ◽  
pp. 513-524
Author(s):  
Álisson Oliveira dos Santos ◽  
Alexandre Sztajnberg ◽  
Tales Mota Machado ◽  
Daniel Magalhães Nobre ◽  
Adriano Neves de Paula e Souza ◽  
...  
Keyword(s):  
Decision Making ◽  
Clinical Practice ◽  
Medical Decision Making ◽  
Clinical Decision Making ◽  
Real Life ◽  
Evaluation Process ◽  
Clinical Decision ◽  
Medical Decision ◽  
Alternative Form ◽  
Evidence Based

ABSTRACT The medical education for clinical decision-making has undergone changes in recent years. Previously supported by printed material, problem solving in clinical practice has recently been aided by digital tools known as summaries platforms. Doctors and medical students have been using such tools from questions found in practice scenarios. These platforms have the advantage of high-quality, evidence-based and always up-to-date content. Its popularization was mainly due to the rise of the internet use and, more recently, of mobile devices such as tablets and smartphones, facilitating their use in clinical practice. Despite this platform is widely available, the most of them actually present several access barriers as costs, foreign language and not be able to Brazilian epidemiology. A free national platform of evidence-based medical summaries was proposed, using the crowdsourcing concept to resolve those barriers. Furthermore, concepts of gamification and content evaluation were implemented. Also, there is the possibility of evaluation by the users, who assigns note for each content created. The platform was built with modern technological tools and made available for web and mobile application. After development, an evaluation process was conducted by researchers to attest to the valid of content, usability, and user satisfying. Consolidated questionnaires and evaluation tools by the literature were applied. The process of developing the digital platform fostered interdisciplinarity, from the involvement of medical and information technology professionals. The work also allowed the reflection on the innovative educational processes, in which the learning from real life problems and the construction of knowledge in a collaborative way are integrated. The assessment results suggest that platform can be real alternative form the evidence-based medical decision-making.

Diagnosing, fast and slow

2020 ◽  
pp. postgradmedj-2019-137412
Author(s):  
JJ Coughlan ◽  
Cormac Francis Mullins ◽  
Thomas J Kiernan
Keyword(s):  
Decision Making ◽  
Cognitive Bias ◽  
Medical Decision Making ◽  
Clinical Decision Making ◽  
Clinical Decision ◽  
Diagnostic Error ◽  
Medical Decision ◽  
Content Type ◽  
Clinical Paradigm ◽  
Improving Patient Care

Diagnostic error is increasingly recognised as a source of significant morbidity and mortality in medicine. In this article, we will attempt to address several questions relating to clinical decision making; How do we decide on a diagnosis? Why do we so often get it wrong? Can we improve our critical faculties?We begin by describing a clinical vignette in which a medical error occurred and resulted in an adverse outcome for a patient. This case leads us to the concepts of heuristic thinking and cognitive bias. We then discuss how this is relevant to our current clinical paradigm, examples of heuristic thinking and potential mechanisms to mitigate bias.The aim of this article is to increase awareness of the role that cognitive bias and heuristic thinking play in medical decision making. We hope to motivate clinicians to reflect on their own patterns of thinking with an overall aim of improving patient care.

Benner’s Framework and Clinical Decision-Making in the Critical Care Environment

2016 ◽  
Vol 30 (1) ◽  
pp. 52-57 ◽  
Author(s):  
Kristi J. Stinson
Keyword(s):  
Decision Making ◽  
Critical Care ◽  
Clinical Experience ◽  
Strong Correlation ◽  
Clinical Decision Making ◽  
Clinical Decision ◽  
Decision Making Process ◽  
Clinical Experiences ◽  
Care Environment ◽  
Decision Making Processes

Completed as part of a larger dissertational study, the purpose of this portion of this descriptive correlational study was to examine the relationships among registered nurses’ clinical experiences and clinical decision-making processes in the critical care environment. The results indicated that there is no strong correlation between clinical experience in general and clinical experience in critical care and clinical decision-making. There were no differences found in any of the Benner stages of clinical experience in relation to the overall clinical decision-making process.

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.

scholarly journals Physician-Specific Maximum Acceptable Risk in Personalized Medicine: Implications for Medical Decision Making

2018 ◽  
Vol 38 (5) ◽  
pp. 593-600
Author(s):  
Marco Boeri ◽  
Alan J. McMichael ◽  
Joseph P. M. Kane ◽  
Francis A. O’Neill ◽  
Frank Kee
Keyword(s):  
Decision Making ◽  
Clinical Decision Making ◽  
Clinical Decision ◽  
Discrete Choice Experiments ◽  
Medical Decision ◽  
Random Parameters ◽  
Acceptable Risk ◽  
Syndrome Scale ◽  
Unit Increase ◽  
Negative Syndrome

Background. In discrete-choice experiments (DCEs), respondents are presented with a series of scenarios and asked to select their preferred choice. In clinical decision making, DCEs allow one to calculate the maximum acceptable risk (MAR) that a respondent is willing to accept for a one-unit increase in treatment efficacy. Most published studies report the average MAR for the whole sample, without conveying any information about heterogeneity. For a sample of psychiatrists prescribing drugs for a series of hypothetical patients with schizophrenia, this article demonstrates how heterogeneity accounted for in the DCE modeling can be incorporated in the derivation of the MAR. Methods. Psychiatrists were given information about a group of patients’ responses to treatment on the Positive and Negative Syndrome Scale (PANSS) and the weight gain associated with the treatment observed in a series of 26 vignettes. We estimated a random parameters logit (RPL) model with treatment choice as the dependent variable. Results. Results from the RPL were used to compute the MAR for the overall sample. This was found to be equal to 4%, implying that, overall, psychiatrists were willing to accept a 4% increase in the risk of an adverse event to obtain a one-unit improvement of symptoms – measured on the PANSS. Heterogeneity was then incorporated in the MAR calculation, finding that MARs ranged between 0.5 and 9.5 across the sample of psychiatrists. Limitations. We provided psychiatrists with hypothetical scenarios, and their MAR may change when making decisions for actual patients. Conclusions. This analysis aimed to show how it is possible to calculate physician-specific MARs and to discuss how MAR heterogeneity could have implications for medical practice.

Clinical Decision Making by Emergency Room Physicians and Residents

2008 ◽  
pp. 217-223
Author(s):  
Ken J. Farion ◽  
Michael J. Hine ◽  
Wojtek Michalowski ◽  
Szymon Wilk
Keyword(s):  
Decision Making ◽  
Information Technology ◽  
Decision Support ◽  
Clinical Decision Making ◽  
Clinical Decision Support Systems ◽  
Clinical Decision ◽  
Medical Community ◽  
Medical Decision ◽  
Best Interest ◽  
Complex Process

Clinical decision-making is a complex process that is reliant on accurate and timely information. Clinicians are dependent (or should be dependent) on massive amounts of information and knowledge to make decisions that are in the best interest of the patient. Increasingly, information technology (IT) solutions are being used as a knowledge transfer mechanism to ensure that clinicians have access to appropriate knowledge sources to support and facilitate medical decision making. One particular class of IT that the medical community is showing increased interest in is clinical decision support systems (CDSSs).

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