Prudence in Shared Decision-Making: The Missing Link between the “Technically Correct” and the “Morally Good” in Medical Decision-Making

Author(s):  
Paul Muleli Kioko ◽  
Pablo Requena Meana

Abstract Shared Decision-Making is a widely accepted model of the physician–patient relationship providing an ethical environment in which physician beneficence and patient autonomy are respected. It acknowledges the moral responsibility of physician and patient by promoting a deliberative collaboration in which their individual expertise—complementary in nature, equal in importance—is emphasized, and personal values and preferences respected. Its goal coincides with Pellegrino and Thomasma’s proximate end of medicine, that is, a technically correct and morally good healing decision for and with a particular patient. We argue that by perfecting the intellectual ability to apprehend the complexity of clinical situations, and through a perfection of the application of the first principles of practical reason, prudence is able to point toward the right and good shared medical decision. A prudent shared medical decision is therefore always in keeping with the kind of person the physician and the patient have chosen to be.

2016 ◽  
Vol 27 (7) ◽  
pp. 1035-1048 ◽  
Author(s):  
Katherine D. Lippa ◽  
Markus A. Feufel ◽  
F. Eric Robinson ◽  
Valerie L. Shalin

Despite increasing prominence, little is known about the cognitive processes underlying shared decision making. To investigate these processes, we conceptualize shared decision making as a form of distributed cognition. We introduce a Decision Space Model to identify physical and social influences on decision making. Using field observations and interviews, we demonstrate that patients and physicians in both acute and chronic care consider these influences when identifying the need for a decision, searching for decision parameters, making actionable decisions Based on the distribution of access to information and actions, we then identify four related patterns: physician dominated; physician-defined, patient-made; patient-defined, physician-made; and patient-dominated decisions. Results suggests that (a) decision making is necessarily distributed between physicians and patients, (b) differential access to information and action over time requires participants to transform a distributed task into a shared decision, and (c) adverse outcomes may result from failures to integrate physician and patient reasoning. Our analysis unifies disparate findings in the medical decision-making literature and has implications for improving care and medical training.


2021 ◽  
Author(s):  
Alysha Taxter ◽  
Lisa Johnson ◽  
Doreen Tabussi ◽  
Yukiko Kimura ◽  
Brittany Donaldson ◽  
...  

BACKGROUND Coproduction of care involves patients and families partnering with their clinicians and care teams, with the premise that each brings their own perspective, knowledge, and expertise, as well as their own values, goals, and preferences to the partnership. Dashboards can display meaningful patient and clinical data to assess how a patient is doing and inform shared decision making. Increasing communication between patients and care teams is particularly important for children with chronic conditions, such as juvenile idiopathic arthritis (JIA), which is the most common, chronic rheumatic condition of childhood, and is associated with increased pain, decreased function, and decreased quality of life. OBJECTIVE We aimed to design a dashboard prototype for use in coproducing care for JIA patients. We evaluated the context use and needs of end users, obtained consensus on the necessary dashboard data elements, and constructed display prototypes to inform meaningful discussions for coproduction. METHODS A human-centered design approach involving parents, patients, clinicians, and care team members was used to develop a dashboard to support coproduction of care in four diverse ambulatory pediatric rheumatology clinics across the United States. We engaged a multidisciplinary team (n=18) of patients/parents, clinicians, nurses, and staff during an in-person kick-off meeting, followed by bi-weekly meetings. We also leveraged advisory panels. Teams mapped workflows and patient journeys, created personas, and developed dashboard sketches. Final necessary dashboard components were determined using Delphi consensus voting. Low-tech dashboard testing was completed during clinic visits, and visual display prototypes were iterated using PDSA methodology. Patients and providers were surveyed about their experiences. RESULTS Teams achieved consensus on what data matters most at point-of-care to support JIA patients, families, and clinicians partnering together to make the best possible decisions for better health. Notable themes included: the right data, in the right place, at the right time; data in once for multiple purposes; patient and family self-management components; and opportunity for education and increased transparency. A final set of 11 dashboard data elements were identified which include patient-reported outcomes, clinical data, and medications. Important design considerations include incorporation of real-time data, clearly labeled graphs, and vertical orientation to facilitate review and discussion. Prototype paper testing with 36 patients/families yielded positive feedback about the dashboard’s usefulness during clinic discussions, helped to talk about what mattered most, and informed healthcare decision making. CONCLUSIONS Our study developed a dashboard prototype that displays patient-reported and clinical data over time, along with medications, that can be used during a clinic visit to support meaningful conversations and shared decision making between JIA patients/families and their clinicians and care teams. CLINICALTRIAL N/A


2018 ◽  
Vol 45 (3) ◽  
pp. 156-160 ◽  
Author(s):  
Rosalind J McDougall

Artificial intelligence (AI) is increasingly being developed for use in medicine, including for diagnosis and in treatment decision making. The use of AI in medical treatment raises many ethical issues that are yet to be explored in depth by bioethicists. In this paper, I focus specifically on the relationship between the ethical ideal of shared decision making and AI systems that generate treatment recommendations, using the example of IBM’s Watson for Oncology. I argue that use of this type of system creates both important risks and significant opportunities for promoting shared decision making. If value judgements are fixed and covert in AI systems, then we risk a shift back to more paternalistic medical care. However, if designed and used in an ethically informed way, AI could offer a potentially powerful way of supporting shared decision making. It could be used to incorporate explicit value reflection, promoting patient autonomy. In the context of medical treatment, we need value-flexible AI that can both respond to the values and treatment goals of individual patients and support clinicians to engage in shared decision making.


2020 ◽  
pp. 0272989X2097787
Author(s):  
K. D. Valentine ◽  
Ha Vo ◽  
Floyd J. Fowler ◽  
Suzanne Brodney ◽  
Michael J. Barry ◽  
...  

Background The Shared Decision Making (SDM) Process scale is a short patient-reported measure of the amount of SDM that occurs around a medical decision. SDM Process items have been used previously in studies of surgical decision making and exhibited discriminant and construct validity. Method Secondary data analysis was conducted across 8 studies of 11 surgical conditions with 3965 responses. Each study contained SDM Process items that assessed the discussion of options, pros and cons, and preferences. Item wording, content, and number of items varied, as did inclusion of measures assessing decision quality, decisional conflict (SURE scale), and regret. Several approaches for scoring, weighting, and the number of items were compared to identify an optimal approach. Optimal SDM Process scores were compared with measures of decision quality, conflict, and regret to examine construct validity; meta-analysis generated summary results. Results Although all versions of the scale were highly correlated, a short, partial credit, equally weighted version of the scale showed favorable properties. Overall, higher SDM Process scores were related to higher decision quality ( d = 0.18, P = 0.029), higher SURE scale scores ( d = 0.57, P < 0.001), and lower decision regret ( d = −0.34, P < 0.001). Significant heterogeneity was present in all validity analyses. Limitations Included studies all focused on surgical decisions, several had small sample sizes, and many were retrospective. Conclusion SDM Process scores showed resilience to coding changes, and a scheme using the short, partial credit, with equal weights was adopted. The SDM Process scores demonstrated a small, positive relationship with decision quality and were consistently related to lower decision conflict and less regret, providing evidence of validity across several surgical decisions.


2019 ◽  
Vol 56 (9) ◽  
pp. 1220-1229
Author(s):  
Francesca Wogden ◽  
Alyson Norman ◽  
Louise Dibben

Objective: Limited research has studied the involvement of children in medical decision-making. The aim of the study was to understand the involvement of adolescents with cleft lip and/or palate (CL/P) in decisions about elective surgeries and treatments. Design: Parents and professionals completed mixed-methods questionnaires about the degree to which children had been involved in choices about elective treatments. Data were analyzed using content analysis. Young people aged 12 to 25 years were asked to take part in semistructured interviews. The data were analyzed using inductive thematic analysis. Setting: Questionnaire data collection took place online, and interview data were collected via messenger or telephone-based interviews. Participants: The study employed 30 participants; 11 young people (3 male, 8 female), 17 parents (13 mothers, 4 fathers), and 5 professionals (2 surgeons, 2 speech and language therapists, and 1 pediatric dentist). Results: Five main themes were identified. These reflected participants feeling that with increasing age should come increased involvement in decision-making and that it was important for adolescents to “have a voice” during decision-making. Parents, peers, and health professionals were identified as influencing decisions. Most adolescents reported overall satisfaction with their involvement in decision-making but sometimes felt “left in the dark” by professionals or under pressure from parents. A desire to improve speech and/or appearance was as an area where adolescents wanted to be more involved in decision-making. Conclusions: Shared decision-making is an important factor for psychological well-being by promoting autonomy and self-esteem among adolescents with CL/P.


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