scholarly journals The role of non-medical factors in physicians’ decision-making process in a pediatric telemedicine service

2019 ◽  
Vol 26 (2) ◽  
pp. 1152-1176 ◽  
Author(s):  
Motti Haimi ◽  
Shuli Brammli-Greenberg ◽  
Yehezkel Waisman ◽  
Nili Stein ◽  
Orna Baron-Epel
Keyword(s):  
Decision Making ◽  
Medical Decision Making ◽  
Medical Decision ◽  
Decision Making Process ◽  
Medical Decisions ◽  
Telemedicine Service ◽  
Medical Factors ◽  
Complex Process ◽  
Clinical Scenarios

The complex process of medical decision-making is prone also to medically extraneous influences or “non-medical” factors. We aimed to investigate the possible role of non-medical factors in doctors’ decision-making process in a telemedicine setting. Interviews with 15 physicians who work in a pediatric telemedicine service were conducted. Those included a qualitative section, in which the physicians were asked about the role of non-medical factors in their decisions. Their responses to three clinical scenarios were also analyzed. In an additional quantitative section, a random sample of 339 parent -physician consultations, held during 2014–2017, was analyzed retrospectively. Various non-medical factors were identified with respect to their possible effect on primary and secondary decisions, the accuracy of diagnosis, and “reasonability” of the decisions. Various non-medical factors were found to influence physicians’ decisions. Those factors were related to the child, the applying parent, the physician, the interaction between the doctor and parents, the shift, and to demographic considerations, and were also found to influence the ability to make an accurate diagnosis and “reasonable” decisions. Our conclusion was that non-medical factors have an impact on doctor’s decisions, even in the setting of telemedicine, and should be considered for improving medical decisions in this milieu.

Emotions and Medical Decision-Making

2020 ◽  
Vol 83 (2) ◽  
pp. 174-194
Author(s):  
Amanda M. Gengler
Keyword(s):  
Health Care ◽  
Decision Making ◽  
Medical Decision Making ◽  
Medical Decision ◽  
Decision Making Process ◽  
Medical Decisions ◽  
Interactive Process ◽  
The Social ◽  
Life Threatening ◽  
Ethnographic Data

Sociologists have written surprisingly little about the role emotions play in medical decision-making, largely ceding this terrain to psychologists who conceptualize emotional influences on decision-making in primarily cognitive and individualistic terms. In this article, I use ethnographic data gathered from parents and physicians caring for children with life-threatening conditions to illustrate how emotions enter the medical decision-making process in fundamentally interactional ways. Because families and physicians alike often defined emotions as useful information to guide the decision-making process, both parties could leverage them in health care interactions by eliciting or demonstrating emotional investment, strategically deploying emotionally charged symbols, and using emotions as tiebreakers to help themselves and one another make choices in the midst of uncertainty. Constructing emotions as valuable in the decision-making process and effectively marshalling them in these ways offered a number of advantages. It could make decisions easier to arrive at, help people feel more confident in the decisions they made, and reduce interpersonal conflict. By connecting the dynamic role emotions can play in the interactive process through which medical decisions are made to the social advantages they can produce, I point to an underappreciated avenue through which inequalities in health care are perpetuated.

Augmenting Medical Diagnosis Decisions? An Investigation into Physicians’ Decision-Making Process with Artificial Intelligence

2021 ◽  
Author(s):  
Ekaterina Jussupow ◽  
Kai Spohrer ◽  
Armin Heinzl ◽  
Joshua Gawlitza
Keyword(s):  
Artificial Intelligence ◽  
Decision Making ◽  
Medical Errors ◽  
Decision Makers ◽  
Medical Decision ◽  
Decision Making Process ◽  
Self Monitoring ◽  
Rule Based ◽  
Human Actors

Systems based on artificial intelligence (AI) increasingly support physicians in diagnostic decisions, but they are not without errors and biases. Failure to detect those may result in wrong diagnoses and medical errors. Compared with rule-based systems, however, these systems are less transparent and their errors less predictable. Thus, it is difficult, yet critical, for physicians to carefully evaluate AI advice. This study uncovers the cognitive challenges that medical decision makers face when they receive potentially incorrect advice from AI-based diagnosis systems and must decide whether to follow or reject it. In experiments with 68 novice and 12 experienced physicians, novice physicians with and without clinical experience as well as experienced radiologists made more inaccurate diagnosis decisions when provided with incorrect AI advice than without advice at all. We elicit five decision-making patterns and show that wrong diagnostic decisions often result from shortcomings in utilizing metacognitions related to decision makers’ own reasoning (self-monitoring) and metacognitions related to the AI-based system (system monitoring). As a result, physicians fall for decisions based on beliefs rather than actual data or engage in unsuitably superficial evaluation of the AI advice. Our study has implications for the training of physicians and spotlights the crucial role of human actors in compensating for AI errors.

Support for management medical decisions and the nature of uncertainty in them

2021 ◽  
Author(s):  
S.Yu. Zhuleva ◽  
A.V. Kroshilin ◽  
S.V. Kroshilina
Keyword(s):  
Decision Making ◽  
Medical Decision Making ◽  
Medical Information ◽  
General Scheme ◽  
The Body ◽  
Medical Decision ◽  
Problem Situation ◽  
Medical Decisions ◽  
Inaccurate Information ◽  
Individual Decisions

The process of making a medical decision is characterized by a lack of knowledge and inconsistency of the available information, the lack of the possibility of attracting competent medical experts, limited time resources, incomplete or inaccurate information about the patient's condition. These aspects may be the causes of medical errors, which lead to further aggravation of the problem situation. Purpose – it is necessary to define and justify managerial medical decisions and types of medical information in conditions of uncertainty, when each variant of the sets of outcomes of the situation (recommendations) has its own unique set of values. The fundamental difference between this process for medical use is the concept of the "best medical solution", in which the key role is given to the patient's state of health in obtaining and evaluating alternatives, as well as the need to take into account the time, adverse reactions of the body and the costs of implementing this solution. In the medical field, support for medical decision-making can be classified as organizational-managerial and therapeutic-diagnostic, but both are determined by the position of the person making the medical decision and are aimed at effective management of the medical institution as a whole. The article describes the causes and factors of the nature of uncertainty in the tasks of supporting medical decision-making in medical-diagnostic and organizational-managerial areas. The analysis of the features of supporting medical decision-making in conditions of uncertainty is carried out. Approaches and directions in this area, as well as the concept of “solution”, are considered. The essence of the management medical decision is reflected. The classification of management medical decisions is given, the requirements that are imposed on them are highlighted. The features of the development of management medical solutions in the conditions of incompleteness and uncertainty, the problems that arise when they are implemented in information systems are presented. The general scheme of the process of creating a management medical solution is shown. The features of making group and individual decisions are reflected. The algorithm of actions of the person making the medical decision in the conditions of uncertainty, incompleteness and risk in medical subject areas is presented.

Reducing overuse by recognising the unintended harms of good intentions

2019 ◽  
pp. bmjebm-2019-111247
Author(s):  
David Slawson ◽  
Allen F Shaughnessy
Keyword(s):  
Decision Making ◽  
Medical Decision Making ◽  
Clinical Care ◽  
Critical Role ◽  
Medical Decision ◽  
Wide Acceptance ◽  
Hierarchy Of Evidence ◽  
Healthcare Interventions

Overdiagnosis and overtreatment—overuse—is gaining wide acceptance as a leading nosocomial intervention in medicine. Not only does overuse create anxiety and diminish patients’ quality of life, in some cases it causes harm to both patients and others not directly involved in clinical care. Reducing overuse begins with the recognition and acceptance of the potential for unintended harm of our best intentions. In this paper, we introduce five cases to illustrate where harm can occur as the result of well-intended healthcare interventions. With this insight, clinicians can learn to appreciate the critical role of probability-based, evidence-informed decision-making in medicine and the need to consider the outcomes for all who may be affected by their actions. Likewise, educators need to evolve medical education and medical decision-making so that it focuses on the hierarchy of evidence and that what ‘ought to work’, based on traditional pathophysiological, disease-focused reasoning, should be subordinate to what ‘does work’.

scholarly journals The Gray Zone: Adolescent and Young Adult Decision Support Needs for Ulcerative Colitis

2020 ◽  
Vol 5 (2) ◽  
pp. 238146832094070
Author(s):  
Andrea Meisman ◽  
Nancy M. Daraiseh ◽  
Phil Minar ◽  
Marlee Saxe ◽  
Ellen A. Lipstein
Keyword(s):  
Ulcerative Colitis ◽  
Decision Making ◽  
Decision Support ◽  
Focus Groups ◽  
Medical Decision Making ◽  
Medical Decision ◽  
Support Needs ◽  
Final Decision ◽  
Care Providers ◽  
Medical Decisions

Purpose. To understand the medical decision support needs specific to adolescents and young adults (AYAs) with ulcerative colitis (UC) and inform development of a decision support tool addressing AYAs’ preferences. Methods. We conducted focus groups with AYAs with UC and mentors from a pediatric inflammatory bowel disease clinic’s peer mentoring program. Focus groups were led by a single trained facilitator using a semistructured guide aimed at eliciting AYAs’ roles in medical decision making and perceived decision support needs. All focus groups were audio recorded, transcribed, and coded by the research team. Data were analyzed using content analysis and the immersion crystallization method. Results. The facilitator led six focus groups: one group with peer mentors aged 18 to 24 years, three groups with patients aged 14 to 17 years, and two groups with patients aged 18 to 24 years. Decision timing and those involved in decision making were identified as interacting components of treatment decision making. Treatment decisions by AYAs were further based on timing, location (inpatient v. outpatient), and family preference for making decisions during or outside of clinic. AYAs involved parents and health care providers in medical decisions, with older participants describing themselves as “final decision makers.” Knowledge and experience were facilitators identified to participating in medical decision making. Conclusions. AYAs with UC experience changes to their roles in medical decisions over time. The support needs identified will inform the development of strategies, such as decision support tools, to help AYAs with chronic conditions develop and use skills needed for participating in medical decision making.

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