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.

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 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).

Clinical decision-making and its place in paramedic practice

2019 ◽  
Vol 11 (5) ◽  
pp. 1-5
Author(s):  
Samantha Murdoch
Keyword(s):  
Decision Making ◽  
Clinical Outcome ◽  
Clinical Decision Making ◽  
Clinical Decision ◽  
Hospital Environment ◽  
Decision Making Process ◽  
Clinical Decisions ◽  
Correct Treatment ◽  
Health And Wellbeing

In the pre-hospital environment, paramedics are required to make clinical decisions, often rapidly to ensure correct treatment and care is provided. Decisions made by paramedics majorly impacts on the life, clinical outcome, safety, health and wellbeing of their patients. With the introduction of the Newly Qualified Paramedic Framework, it potentially has never been more pertinent to examine the decision-making process-an integral part of paramedicine. The implementation of the NQP framework has prompted an exploration into clinical decision making and its place in an ever-evolving profession. Through examination of theories and frameworks, this article aims to identify the underpinning evidence that enables a paramedic to reach a competent decision and the barriers experienced in the process.

Annals Clinical Decision Making: Weighing Evidence to Inform Clinical Decisions

2020 ◽  
Vol 172 (9) ◽  
pp. 599-603 ◽  
Author(s):  
Joshua P. Metlay ◽  
Katrina A. Armstrong
Keyword(s):  
Decision Making ◽  
Clinical Decision Making ◽  
Clinical Decision ◽  
Clinical Decisions

scholarly journals Culture, Self, and Medical Decision Making in Australia and China: A Structural Model Analysis

2019 ◽  
Vol 4 (2) ◽  
pp. 238146831987101 ◽  
Author(s):  
Hankiz Dolan ◽  
Dana L. Alden ◽  
John M. Friend ◽  
Ping Yein Lee ◽  
Yew Kong Lee ◽  
...  
Keyword(s):  
Decision Making ◽  
Medical Decision Making ◽  
Medical Information ◽  
Personal Values ◽  
Total Variance ◽  
Medical Decision ◽  
Equation Modeling ◽  
Individual Level ◽  
Study Results ◽  
Variance Explained

Objective. To explore and compare the influences of individual-level cultural values and personal attitudinal values on the desire for medical information and self-involvement in decision making in Australia and China. Methods. A total of 288 and 291 middle-aged adults from Australia and China, respectively, completed an online survey examining cultural and personal values, and their desired level of self-influence on medical decision making. Structural equation modeling was used to test 15 hypotheses relating to the effects of cultural and personal antecedents on the individual desire for influence over medical decision making. Results. Similar factors in both Australia and China (total variance explained: Australia 29%; China 35%) predicted desire for medical information, with interdependence (unstandardized path coefficient βAustralia = 0.102, P = 0.014; βChina = 0.215, P = 0.001), independence (βAustralia = 0.244, P < 0.001; βChina = 0.123, P = 0.037), and health locus of control (βAustralia = −0.140, P = 0.018; βChina = −0.138, P = 0.007) being significant and positive predictors. A desire for involvement in decisions was only predicted by power distance, which had an opposite effect of being negative for Australia and positive for China (total variance explained: Australia 11%; China 5%; βAustralia = 0.294, P < 0.001; China: βChina = −0.190, P = 0.043). National culture moderated the effect of independence on desire for medical information, which was stronger in Australia than China ( Z score = 1.687, P < 0.05). Conclusions. Study results demonstrate that in both countries, desire for medical information can be influenced by individual-level cultural and personal values, suggesting potential benefits of tailoring health communication to personal mindsets to foster informed decision making. The desired level of self-involvement in decision making was relatively independent of other cultural and personal values in both countries, suggesting caution against cultural stereotypes. Study findings also suggest that involvement preferences in decision making should be considered separately from information needs at the clinical encounter.

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