Medical Epistemology

2018 ◽  
pp. 45-55
Author(s):  
Erwin B. Montgomery
Keyword(s):  
Decision Making ◽  
Medical Decision Making ◽  
Medical Decision ◽  
Modus Tollens ◽  
Medical Epistemology ◽  
Medical Decisions ◽  
Cause And Effect ◽  
Practical Syllogism ◽  
New Knowledge ◽  
Cutoff Threshold

Deductive approaches in medical decision-making have an air of certainty borrowed from philosophical deduction, as for example, in the hypothetico-deductive approach. However, deduction, although certain, is limited because it cannot contribute to new knowledge other than proving some claims to knowledge as false (using modus tollens). Syllogistic deduction requires modification to gain utility, such as the partial and practical syllogisms. However, these forms are logically invalid in that they do not ensure certainty in the conclusions. The partial syllogism can be rendered more certain by the use of probability. However, the necessity of a medical decision requires dichotomization of the continuous probability variable. A cutoff threshold applied to the probability is necessary to enable a dichotomous decision, such as whether to treat or not treat a patient. The practical syllogism introduces the notion of cause and effect, which also may influence medical decisions, although often in a counterproductive manner.

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.

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.

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.

scholarly journals Use of Tablets and Smartphones to Support Medical Decision Making in US Adults: Cross-Sectional Study (Preprint)

2020 ◽  
Author(s):  
Aisha Langford ◽  
Kerli Orellana ◽  
Jolaade Kalinowski ◽  
Carolyn Aird ◽  
Nancy Buderer
Keyword(s):  
Decision Making ◽  
Health Information ◽  
Medical Decision Making ◽  
Electronic Devices ◽  
Sociodemographic Factors ◽  
Medical Decision ◽  
Health And Wellness ◽  
Medical Decisions ◽  
Cross Sectional ◽  
Lower Odds

BACKGROUND Tablet and smartphone ownership have increased among US adults over the past decade. However, the degree to which people use mobile devices to help them make medical decisions remains unclear. OBJECTIVE The objective of this study is to explore factors associated with self-reported use of tablets or smartphones to support medical decision making in a nationally representative sample of US adults. METHODS Cross-sectional data from participants in the 2018 Health Information National Trends Survey (HINTS 5, Cycle 2) were evaluated. There were 3504 responses in the full HINTS 5 Cycle 2 data set; 2321 remained after eliminating respondents who did not have complete data for all the variables of interest. The primary outcome was use of a tablet or smartphone to help make a decision about how to treat an illness or condition. Sociodemographic factors including gender, race/ethnicity, and education were evaluated. Additionally, mobile health (mHealth)- and electronic health (eHealth)-related factors were evaluated including (1) the presence of health and wellness apps on a tablet or smartphone, (2) use of electronic devices other than tablets and smartphones to monitor health (eg, Fitbit, blood glucose monitor, and blood pressure monitor), and (3) whether people shared health information from an electronic monitoring device or smartphone with a health professional within the last 12 months. Descriptive and inferential statistics were conducted using SAS version 9.4. Weighted population estimates and standard errors, univariate odds ratios, and 95% CIs were calculated, comparing respondents who used tablets or smartphones to help make medical decisions (n=944) with those who did not (n=1377), separately for each factor. Factors of interest with a <i>P</i> value of &lt;.10 were included in a subsequent multivariable logistic regression model. RESULTS Compared with women, men had lower odds of reporting that a tablet or smartphone helped them make a medical decision. Respondents aged 75 and older also had lower odds of using a tablet or smartphone compared with younger respondents aged 18-34. By contrast, those who had health and wellness apps on tablets or smartphones, used other electronic devices to monitor health, and shared information from devices or smartphones with health care professionals had higher odds of reporting that tablets or smartphones helped them make a medical decision, compared with those who did not. CONCLUSIONS A limitation of this research is that information was not available regarding the specific health condition for which a tablet or smartphone helped people make a decision or the type of decision made (eg, surgery, medication changes). In US adults, mHealth and eHealth use, and also certain sociodemographic factors are associated with using tablets or smartphones to support medical decision making. Findings from this study may inform future mHealth and other digital health interventions designed to support medical decision making.

Surrogate’s Personal Sense of Duty as a Crucial Element in Medical Decision Making

2021 ◽  
pp. 7-26
Author(s):  
Chris Feudtner ◽  
Theodore E. Schall ◽  
Douglas L. Hill
Keyword(s):  
Decision Making ◽  
Medical Decision Making ◽  
Adult Child ◽  
Decision Makers ◽  
Medical Decision ◽  
Single Event ◽  
Medical Decisions ◽  
The Social ◽  
Surrogate Decision Makers ◽  
Surrogate Decision

Surrogates who must make medical decisions for other people—most often, loved ones—face difficult challenges not acknowledged in current models of medical decision making. Furthermore, medical decisions are typically not a single event, but an ongoing event that evolves over time. This chapter presents a broader conceptualization of medical decision making, highlighting that (1) surrogate decision makers often face multiple problems, not a single clear problem; (2) the path to the decision maker’s desired goal is often unclear and often constrained by past decisions; (3) the social relationships between the surrogate and the patient (parent, adult child, spouse) influence the decision making as surrogates try to fulfill their role as a good parent, good son/daughter, or good spouse; and (4) surrogate decision makers often judge themselves negatively in ways that influence their decisions and the outcome. Clinicians who recognize these complex influences on surrogate decision making may be better able to support surrogates through this difficult process.

scholarly journals Influence of response shift and disposition on patient-reported outcomes may lead to suboptimal medical decisions: a medical ethics perspective

2019 ◽  
Vol 20 (1) ◽  
Author(s):  
Iris D. Hartog ◽  
Dick L. Willems ◽  
Wilbert B. van den Hout ◽  
Michael Scherer-Rath ◽  
Tom H. Oreel ◽  
...  
Keyword(s):  
Decision Making ◽  
Patient Care ◽  
Patient Reported Outcomes ◽  
Medical Decision Making ◽  
Response Shift ◽  
Cost Effective ◽  
Medical Decision ◽  
Medical Decisions ◽  
Patient Reports ◽  
Patient Reported

Abstract Background Patient-reported outcomes (PROs) are frequently used for medical decision making, at the levels of both individual patient care and healthcare policy. Evidence increasingly shows that PROs may be influenced by patients’ response shifts (changes in interpretation) and dispositions (stable characteristics). Main text We identify how response shifts and dispositions may influence medical decisions on both the levels of individual patient care and health policy. We provide examples of these influences and analyse the consequences from the perspectives of ethical principles and theories of just distribution. Conclusion If influences of response shift and disposition on PROs and consequently medical decision making are not considered, patients may not receive optimal treatment and health insurance packages may include treatments that are not the most effective or cost-effective. We call on healthcare practitioners, researchers, policy makers, health insurers, and other stakeholders to critically reflect on why and how such patient reports are used.

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.

scholarly journals Design and implementation of the system to support making medical decisions aid to the population

2021 ◽  
Vol 244 ◽  
pp. 11015
Author(s):  
Ekaterina Stodelova ◽  
Galina Korableva
Keyword(s):  
Decision Making ◽  
Medical Care ◽  
Medical Decision Making ◽  
Database Management System ◽  
Automated System ◽  
Medical Decision ◽  
City Hospital ◽  
Medical Decisions ◽  
Software Product ◽  
Rabies Prevention

The publication discusses the issues and results of designing an automated system for supporting medical decision-making on issues of antirabic prevention and aid to the population. The need to provide medical care in the framework of preventing deaths from rabies infection and carrying out preventive measures to prevent such infections is relevant not only in the Russian Federation, but also in many countries of the world. Algorithms for providing medical care and carrying out rabies vaccination are complex, requiring certain professional skills from medical professionals, as well as care and accuracy from patients. Therefore, in manual mode, they are time-consuming both in terms of registering information about the treatment performed, and in terms of the speed of forming medical decisions when providing medical care or when correcting violations of previously defined algorithms. For computer support of these processes, an automated system for supporting medical decision-making has been developed using the tools of the Clarion 10 relational database management system. For various categories of patients and citizens undergoing rabies prevention, experts have developed and entered into the database templates of treatment courses, which are assigned by the system after analyzing the clinical data of patients and the initial or repeated fact of their request for help. These templates and algorithms for analyzing the possibilities of their application are similar to products that allow you to link assumptions and conclusions when making decisions. The automated medical decision support system allows you to register patients and persons undergoing rabies prevention, assign them treatment courses and vaccination schemes, adjust treatment and prevention methods in case of violations of previously prescribed ones, and generate statistical reports. The developed software product received the author’s certificate no. 2018663452 dated 26.10.2018 from the Federal service for intellectual property (Rospatent). The software product has been tested in first aid rooms in Moscow, in the practice of the polyclinic department of the First City hospital named after N. I. Pirogov.

scholarly journals Use of Tablets and Smartphones to Support Medical Decision Making in US Adults: Cross-Sectional Study

10.2196/19531 ◽  
2020 ◽  
Vol 8 (8) ◽  
pp. e19531 ◽  
Author(s):  
Aisha Langford ◽  
Kerli Orellana ◽  
Jolaade Kalinowski ◽  
Carolyn Aird ◽  
Nancy Buderer
Keyword(s):  
Decision Making ◽  
Health Information ◽  
Medical Decision Making ◽  
Electronic Devices ◽  
Sociodemographic Factors ◽  
Medical Decision ◽  
Health And Wellness ◽  
Medical Decisions ◽  
Cross Sectional ◽  
Lower Odds

Background Tablet and smartphone ownership have increased among US adults over the past decade. However, the degree to which people use mobile devices to help them make medical decisions remains unclear. Objective The objective of this study is to explore factors associated with self-reported use of tablets or smartphones to support medical decision making in a nationally representative sample of US adults. Methods Cross-sectional data from participants in the 2018 Health Information National Trends Survey (HINTS 5, Cycle 2) were evaluated. There were 3504 responses in the full HINTS 5 Cycle 2 data set; 2321 remained after eliminating respondents who did not have complete data for all the variables of interest. The primary outcome was use of a tablet or smartphone to help make a decision about how to treat an illness or condition. Sociodemographic factors including gender, race/ethnicity, and education were evaluated. Additionally, mobile health (mHealth)- and electronic health (eHealth)-related factors were evaluated including (1) the presence of health and wellness apps on a tablet or smartphone, (2) use of electronic devices other than tablets and smartphones to monitor health (eg, Fitbit, blood glucose monitor, and blood pressure monitor), and (3) whether people shared health information from an electronic monitoring device or smartphone with a health professional within the last 12 months. Descriptive and inferential statistics were conducted using SAS version 9.4. Weighted population estimates and standard errors, univariate odds ratios, and 95% CIs were calculated, comparing respondents who used tablets or smartphones to help make medical decisions (n=944) with those who did not (n=1377), separately for each factor. Factors of interest with a P value of <.10 were included in a subsequent multivariable logistic regression model. Results Compared with women, men had lower odds of reporting that a tablet or smartphone helped them make a medical decision. Respondents aged 75 and older also had lower odds of using a tablet or smartphone compared with younger respondents aged 18-34. By contrast, those who had health and wellness apps on tablets or smartphones, used other electronic devices to monitor health, and shared information from devices or smartphones with health care professionals had higher odds of reporting that tablets or smartphones helped them make a medical decision, compared with those who did not. Conclusions A limitation of this research is that information was not available regarding the specific health condition for which a tablet or smartphone helped people make a decision or the type of decision made (eg, surgery, medication changes). In US adults, mHealth and eHealth use, and also certain sociodemographic factors are associated with using tablets or smartphones to support medical decision making. Findings from this study may inform future mHealth and other digital health interventions designed to support medical decision making.

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