The political polarization of COVID-19 treatments among physicians and laypeople in the United States.

In the United States, liberals and conservatives disagree about facts. To what extent does expertise attenuate these disagreements? To study this question, we compare the polarization of beliefs about COVID-19 treatments among laypeople and critical care physicians. We find that political ideology predicts both groups' beliefs about a range of COVID-19 treatments. These associations persist after controlling for a rich set of covariates, including local politics. We study two potential explanations: a) that partisans are exposed to different information and b) that they interpret the same information in different ways, finding evidence for both. Polarization is driven by preferences for partisan cable news but not by exposure to scientific research. Using a set of embedded experiments, we demonstrate that partisans perceive scientific evidence differently when it pertains to a politicized treatment (ivermectin), relative to when the treatment is not identified. These results highlight the extent to which political ideology is increasingly relevant for understanding beliefs, even among expert decision makers such as physicians.

Decisional Conflict Among Patients Newly Diagnosed With Clinical T1 Renal Masses: A Prospective Study.

PURPOSE: Because multiple management options exist for clinical T1 renal masses, patients may experience a state of uncertainty about the course of action to pursue (ie, decisional conflict). To better support patients, we examined patient, clinical, and decision-making factors associated with decisional conflict among patients newly diagnosed with clinical T1 renal masses suspicious for kidney cancer. MATERIALS AND METHODS: From a prospective clinical trial, participants completed the Decisional Conflict Scale (DCS), scored 0 to 100 with < 25 associated with implementing decisions, at 2 time points during the initial decision-making period. The trial further characterized patient demographics, health status, tumor burden, and patient-centered communication, while a subcohort completed additional questionnaires on decision-making. Associations of patient, clinical, and decision-making factors with DCS scores were evaluated using generalized estimating equations to account for repeated measures per patient. RESULTS: Of 274 enrollees, 250 completed a DCS survey; 74% had masses ≤ 4 cm in size, while 11% had high-complexity tumors. Model-based estimated mean DCS score across both time points was 17.6 (95% CI 16.0-19.3), though 50% reported a DCS score ≥ 25 at least once. On multivariable analysis, DCS scores increased with age (+2.64, 95% CI 1.04-4.23), high- vs low-complexity tumors (+6.50, 95% CI 0.35-12.65), and cystic vs solid masses (+9.78, 95% CI 5.27-14.28). Among decision-making factors, DCS scores decreased with higher self-efficacy (-3.31, 95% CI -5.77 to -0.86]) and information-seeking behavior (-4.44, 95% CI -7.32 to -1.56). DCS scores decreased with higher patient-centered communication scores (-8.89, 95% CI -11.85 to -5.94). CONCLUSIONS: In addition to patient and clinical factors, decision-making factors and patient-centered communication relate with decisional conflict, highlighting potential avenues to better support patient decision-making for clinical T1 renal masses.

What Clinicians and Researchers Should Know About the Evolving Field of Advance Care Planning: a Narrative Review.

Advance care planning (ACP) has been recognized as crucial by patients, families, and clinicians; however, different definitions and measurements have led to inconsistencies in practice and mixed evidence in the literature. This narrative review explores ACP's evolution, innovations, and outcomes using thematic analysis to synthesize data from randomized controlled trials, reviews, and editorials. Key findings include (1) ACP has evolved over the past several decades from a sole focus on code status and advance directive (AD) forms to a continuum of care planning over the life course focused on tailored preparation for patients and surrogate decision-makers and (2) ACP measurement has evolved from traditional outcome metrics, such as AD completion, to a comprehensive outcomes framework that includes behavior change theory, systems, implementation science, and a focus on surrogate outcomes. Since the recent development of an ACP consensus definition and outcomes framework, high-quality trials have reported mainly positive outcomes for interventions, especially for surrogates, which aligns with the patient desire to relieve decision-making burden for loved ones. Additionally, measurement of "clinically meaningful" ACP information, including documented goals of care discussions, is increasingly being integrated into electronic health records (EHR), and emerging, real-time assessments and natural language processing are enhancing ACP evaluation. To make things easier for patients, families, and care teams, clinicians and researchers can use and disseminate these evolved definitions; provide patients validated, easy-to-use tools that prime patients for conversations and decrease health disparities; use easy-to-access clinician training and simple scripts for interdisciplinary team members; and document patients' values and preferences in the medical record to capture clinically meaningful ACP so this information is available at the point of care. Future efforts should focus on efficient implementation, expanded reimbursement options, and seamless integration of EHR documentation to ensure ACP's continued evolution to better serve patients and their care partners.

Disease-modifying therapies for sickle cell disease: Decisional needs and supports among adolescents and young adults.

BACKGROUND: Shared decision-making is one promising solution to addressing barriers in use of disease-modifying therapies for adolescents and young adults (AYAs) with sickle cell disease (SCD). A thorough understanding of decisional needs can guide the development of decisional supports and promote shared decision-making. PROCEDURE: Informed by the Ottawa Decision Support Framework (ODSF), we conducted a qualitative analysis to assess decisional needs and supports reported by AYAs with SCD, their caregivers, and healthcare providers. Semi-structured qualitative interviews were conducted with AYAs and their caregivers, and online crowdsourcing was used with SCD providers. Thematic and descriptive content analyses were used to summarize perspectives on decisional needs and supports regarding disease-modifying therapies. RESULTS: Fourteen AYAs (Mage  = 21 years, 57% male, 93% non-Hispanic Black, 79% HbSS), 11 caregivers (80% female, 100% non-Hispanic Black), and 40 healthcare providers (65% female, 65% non-Hispanic White, Myears in practice  = 14.8 years, 75% physicians) participated. Thematic analysis revealed needs related to: decisional conflict, inadequate knowledge, unclear expectations, and inadequate supports and resources. Six forms of support emerged as important for decision-making: establishing an open and trusting patient/family-provider relationship, providing information, accepting ambivalence and unreadiness, supporting implementation of a decision, addressing inadequate health and social services, and promoting adequate social, emotional, and instrumental help. CONCLUSIONS: This is the first study to assess decisional needs and supports for AYAs with SCD considering disease-modifying therapies. Additional research is needed to examine which decision supports are the most impactful to promote effective shared decision-making in this population.

Surgical prioritization based on decision model outcomes is not sensitive to differences between the health-related quality of life values estimates of physicians and citizens.

PURPOSE: Decision models can be used to support allocation of scarce surgical resources. These models incorporate health-related quality of life (HRQoL) values that can be determined using physician panels. The predominant opinion is that one should use values obtained from citizens. We investigated whether physicians give different HRQoL values to citizens and evaluate whether such differences impact decision model outcomes. METHODS: A two-round Delphi study was conducted. Citizens estimated HRQoL of pre- and post-operative health states for ten surgeries using a visual analogue scale. These values were compared using Bland-Altman analysis with HRQoL values previously obtained from physicians. Impact on decision model outcomes was evaluated by calculating the correlation between the rankings of surgeries established using the physicians' and the citizens' values. RESULTS: A total of 71 citizens estimated HRQoL. Citizens' values on the VAS scale were - 0.07 points (95% CI - 0.12 to - 0.01) lower than the physicians' values. The correlation between the rankings of surgeries based on citizens' and physicians' values was 0.96 (p < 0.001). CONCLUSION: Physicians put higher values on health states than citizens. However, these differences only result in switches between adjacent entries in the ranking. It would seem that HRQoL values obtained from physicians are adequate to inform decision models during crises.

When facts become feelings.

I have long maintained that equipoise between empathy and the rational, decisive nature of obstetric care is central to good doctoring. I had exacting standards for how to communicate facts with feeling while shielding my own. Then, after experiencing my own obstetric emergency and preterm birth, this changed. In this reflection, I explore how recognizing the intersections between facts and feelings has made me a better physician.

Attitudes toward and preparedness for lung transplantation among individuals with cystic fibrosis in the era of highly effective modulators.

BACKGROUND: Outcomes for individuals with cystic fibrosis (CF) have improved due to highly effective modulator therapy (HEMT). However, lung transplant (LTx) remains an important treatment for people with advanced lung disease. This study assessed attitudes and knowledge about LTx in the HEMT era. METHODS: All patients from the University of Washington CF clinic were surveyed March 25-May 30, 2020. Questions addressed self-rated LTx preparedness and knowledge, as well as barriers and facilitators to discussing LTx. Demographic and clinical data were extracted from the electronic health record. RESULTS: There were 159/224 (71%) responses. Respondents had a median forced expiratory volume in one second (FEV1) of 70%, and 142 (89%) were on modulatory therapy. One hundred thirteen (71%) respondents felt that it was moderately or very important to be prepared to make decisions about LTx, though only 56 (35%) felt moderately or very prepared. Only 83 (30%) and 47 (52%) participants correctly answered questions about life expectancy and improved quality of life after LTx, respectively. Respondents with Medicaid insurance less frequently answered questions correctly. The most common barriers to discussing LTx were fear of being a burden on loved ones for 58 respondents (36%) and cost of LTx for 46 (29%). Most participants (94%) trusted their CF doctor, and 75% of participants selected trust as a facilitator for LTx discussions. CONCLUSIONS: Many individuals with CF, especially those with lower socioeconomic status, lacked knowledge and did not feel very prepared for decisions about LTx. Earlier education and discussions about LTx represent an area for improvement in CF care.

Predictive models for delay in medical decision-making among older patients with acute ischemic stroke: a comparative study using logistic regression analysis and lightGBM algorithm.

OBJECTIVE: To explore the factors affecting delayed medical decision-making in older patients with acute ischemic stroke (AIS) using logistic regression analysis and the Light Gradient Boosting Machine (LightGBM) algorithm, and compare the two predictive models. METHODS: A cross-sectional study was conducted among 309 older patients aged ≥ 60 who underwent AIS. Demographic characteristics, stroke onset characteristics, previous stroke knowledge level, health literacy, and social network were recorded. These data were separately inputted into logistic regression analysis and the LightGBM algorithm to build the predictive models for delay in medical decision-making among older patients with AIS. Five parameters of Accuracy, Recall, F1 Score, AUC and Precision were compared between the two models. RESULTS: The medical decision-making delay rate in older patients with AIS was 74.76%. The factors affecting medical decision-making delay, identified through logistic regression and LightGBM algorithm, were as follows: stroke severity, stroke recognition, previous stroke knowledge, health literacy, social network (common factors), mode of onset (logistic regression model only), and reaction from others (LightGBM algorithm only). The LightGBM model demonstrated the more superior performance, achieving the higher AUC of 0.909. CONCLUSIONS: This study used advanced LightGBM algorithm to enable early identification of delay in medical decision-making groups in the older patients with AIS. The identified influencing factors can provide critical insights for the development of early prevention and intervention strategies to reduce delay in medical decisions-making among older patients with AIS and promote patients' health. The LightGBM algorithm is the optimal model for predicting the delay in medical decision-making among older patients with AIS.

Do Reasons Matter? Navigating Parents' Reasons in Healthcare Decisions for Children.

Bioethics has dedicated itself to exploring and defending both reasons for and against certain aspects of clinical care, biomedical research and health policy, including what decisions must be made, who should make them, and how they should be made. In pediatrics, it's widely acknowledged that parents' reasons may matter pragmatically; attending to parents' reasons is important if we want to work with families. Yet the conventional view in pediatric ethics is that parents' reasons are irrelevant to whether a decision is permissible or impermissible according to accepted ethical standards. In this paper, we explore whether parents' reasons matter ethically and, if so, in what way and for whom. First, we clarify what we mean by 'reasons.' Second, we provide an overview of how reasons are typically treated in medical decision-making and pediatric ethics. Third, we analyze a hypothetical pediatric case to illustrate how changing reasons can transform ethical analyses, including by contributing to where and how clinicians and ethicists draw the boundaries intrinsic to common pediatric ethical frameworks. We push back against the conventional view and argue that parents' reasons matter ethically in several ways. We call for further research on the role of parents' reasons in clinical ethics deliberation.

Is Suffering a Useless Concept?

"Suffering" is a central concept within bioethics and often a crucial consideration in medical decision making. As used in practice, however, the concept risks being uninformative, ambiguous, or even misleading. In this paper, we consider a series of cases in which "suffering" is invoked and analyze them in light of prominent theories of suffering. We then outline ethical hazards that arise as a result of imprecise usage of the concept and offer practical recommendations for avoiding them. Appeals to suffering are often getting at something ethically important. But this is where the work of ethics begins, not where it ends.

Transformative medical ethics: A framework for changing practice according to normative-ethical requirements.

We propose a step-by-step methodological framework of translational bioethics that aims at changing medical practice according to normative-ethical requirements, which we will thus call "transformative medical ethics." The framework becomes especially important when there is a gap between widely acknowledged, ethically justified normative claims and their realization in the practice of biomedicine and technology (ought-is gap). Building on prior work on translational bioethics, the framework maps a process with six different phases and 12 distinct translational steps. The steps involve various research activities including conceptual philosophical inquiry and (socio-)empirical research. On the one hand, the framework can be used as a heuristic tool to identify barriers to the transformation process. On the other hand, it can provide guidance for researchers and practitioners to develop appropriate (conceptual action and practice) models, which are then implemented and evaluated in specific practice contexts. We use the example of realizing the norm of respect for autonomy in the practice of medical decision-making to illustrate the framework. Further research is required, for example, to theoretically underpin the framework, to apply it to other ought-is gaps, and to evaluate its feasibility and effectiveness in various practice areas. Overall, the framework of transformative medical ethics suggests a strategic process to investigate and promote practice change that is ethically informed in all phases.

Reducing decisional conflict in decisions about prenatal genetic testing: the impact of a dyadic intervention at the start of prenatal care.

OBJECTIVES: Decisional conflict and regret about prenatal genetic screening and diagnostic tests may have important consequences in the current pregnancy and for future reproductive decisions. Identifying mechanisms that reduce conflict associated with the decision to use or decline these options is necessary for optimal patient counseling. METHODS: We conducted a cluster-randomized controlled trial of a shared decision-making tool (NEST) at the beginning of prenatal care. Enrolled patients completed follow-up surveys at the time of testing (QTT) and in the second-third trimester (QFF), including the Decision Conflict Scale (DCS). Total DCS scores were analyzed using a multivariate linear mixed-effect model. RESULTS: Of the total number of participants (n=502) enrolled, 449 completed the QTT and QFF surveys. The mean age of participants was 31.6±3.8, with most parous at the time of study participation (n=321; 71.7 %). Both the NEST (the intervention) and control groups had lower median total DCS scores at QFF (NEST 13.3 [1.7, 25.0] vs. control 16.7 [1.7, 25.0]; p=0.24) compared to QTT (NEST 20.8 [5.0, 25.0] vs. control 18.3 [3.3, 26.7]; p=0.89). Participants exposed to NEST had lower decisional conflict at QFF compared to control (ß -3.889; [CI -7.341, -0.437]; p=0.027). CONCLUSIONS: Using a shared decision-making tool at the start of prenatal care decreased decisional conflict regarding prenatal genetic testing. Such interventions have the potential to provide an important form of decision-making support for patients facing the unique type of complex and preference-based choices about the use of prenatal genetic tests.

Second opinion machine learning for fast-track pathway assignment in hip and knee replacement surgery: the use of patient-reported outcome measures.

BACKGROUND: The frequency of hip and knee arthroplasty surgeries has been rising steadily in recent decades. This trend is attributed to an aging population, leading to increased demands on healthcare systems. Fast Track (FT) surgical protocols, perioperative procedures designed to expedite patient recovery and early mobilization, have demonstrated efficacy in reducing hospital stays, convalescence periods, and associated costs. However, the criteria for selecting patients for FT procedures have not fully capitalized on the available patient data, including patient-reported outcome measures (PROMs). METHODS: Our study focused on developing machine learning (ML) models to support decision making in assigning patients to FT procedures, utilizing data from patients' self-reported health status. These models are specifically designed to predict the potential health status improvement in patients initially selected for FT. Our approach focused on techniques inspired by the concept of controllable AI. This includes eXplainable AI (XAI), which aims to make the model's recommendations comprehensible to clinicians, and cautious prediction, a method used to alert clinicians about potential control losses, thereby enhancing the models' trustworthiness and reliability. RESULTS: Our models were trained and tested using a dataset comprising 899 records from individual patients admitted to the FT program at IRCCS Ospedale Galeazzi-Sant'Ambrogio. After training and selecting hyper-parameters, the models were assessed using a separate internal test set. The interpretable models demonstrated performance on par or even better than the most effective 'black-box' model (Random Forest). These models achieved sensitivity, specificity, and positive predictive value (PPV) exceeding 70%, with an area under the curve (AUC) greater than 80%. The cautious prediction models exhibited enhanced performance while maintaining satisfactory coverage (over 50%). Further, when externally validated on a separate cohort from the same hospital-comprising patients from a subsequent time period-the models showed no pragmatically notable decline in performance. CONCLUSIONS: Our results demonstrate the effectiveness of utilizing PROMs as basis to develop ML models for planning assignments to FT procedures. Notably, the application of controllable AI techniques, particularly those based on XAI and cautious prediction, emerges as a promising approach. These techniques provide reliable and interpretable support, essential for informed decision-making in clinical processes.

Patient Experience and Decision-Making Process for Laser Photocoagulation for Monochorionic Twin Pregnancy: A Qualitative Exploration.

INTRODUCTION: The aim of the study was to explore patients' perspectives on diagnosis and treatment options for complicated monochorionic multiple gestations, and experiences with fetoscopic laser photocoagulation. METHODS: This is a prospective cohort study of patients undergoing laser photocoagulation. Participants were interviewed during pregnancy and the postpartum period. Qualitative analysis was performed. RESULT: Twenty-seven patients who were candidates for laser photocoagulation were included. All elected to have laser photocoagulation. Patients chose surgery with goals of improving survival, decreasing the risk of preterm delivery, and improving the long-term health of their fetuses. They demonstrated accurate knowledge of the risks and benefits of treatment. Most (74%) felt that laser photocoagulation represented their only viable clinical option. Few seriously considered pregnancy termination or selective reduction (7% and 11% respectively). Postpartum, patients expressed no regrets about their decisions for surgery, but many felt unprepared for the challenges of preterm delivery. CONCLUSION: Participants weighed treatment options similarly to fetal specialists. They acknowledged but did not seriously consider treatments other than fetoscopic laser photocoagulation and were highly motivated to do whatever they could to improve outcomes for their fetuses.

Machine learning decision support model for discharge planning in stroke patients.

BACKGROUND/AIM: Efficient discharge for stroke patients is crucial but challenging. The study aimed to develop early predictive models to explore which patient characteristics and variables significantly influence the discharge planning of patients, based on the data available within 24 h of admission. DESIGN: Prospective observational study. METHODS: A prospective cohort was conducted at a university hospital with 523 patients hospitalised for stroke. We built and trained six different machine learning (ML) models, followed by testing and tuning those models to find the best-suited predictor for discharge disposition, dichotomized into home and non-home. To evaluate the accuracy, reliability and interpretability of the best-performing models, we identified and analysed the features that had the greatest impact on the predictions. RESULTS: In total, 523 patients met the inclusion criteria, with a mean age of 61 years. Of the patients with stroke, 30.01% had non-home discharge. Our model predicting non-home discharge achieved an area under the receiver operating characteristic curve of 0.95 and a precision of 0.776. After threshold was moved, the model had a recall of 0.809. Top 10 variables by importance were National Institutes of Health Stroke Scale (NIHSS) score, family income, Barthel index (BI) score, FRAIL score, fall risk, pressure injury risk, feeding method, depression, age and dysphagia. CONCLUSION: The ML model identified higher NIHSS, BI, and FRAIL, family income, higher fall risk, pressure injury risk, older age, tube feeding, depression and dysphagia as the top 10 strongest risk predictors in identifying patients who required non-home discharge to higher levels of care. Modern ML techniques can support timely and appropriate clinical decision-making. RELEVANCE TO CLINICAL PRACTICE: This study illustrates the characteristics and risk factors of non-home discharge in patients with stroke, potentially contributing to the improvement of the discharge process. REPORTING METHOD: STROBE guidelines.

The voices of breast cancer survivors with chronic pain: A qualitative thematic analysis of patients' challenges to pain management.

OBJECTIVES: Recognizing the limitations of the current pain therapies, the study aimed to explore the unique needs and obstacles related to pain management in Breast Cancer Survivors (BCs) with Chronic Pain (CP). METHODS: 4 focus groups were conducted involving 17 BCs with CP (Mage = 51, SD = 7.99) with varying pain intensities. Thematic analysis was applied to transcribed discussions. FINDINGS: Three key themes emerged: (1) Challenges to pain management, including "Doctor-patients communications barriers" and "Contextual and societal barriers"; (2) Self-management needs, encompassing "Psycho-social support," "Care-related needs," and "Shared decision-making"; (3) Treatment preferences and perceptions of pain management, with subthemes like "Treatment preferences," "Institution preference," and "Decision role perception." CONCLUSIONS: This study emphasizes tailored support systems targeting patient hesitancy, countering pain normalization, and addressing healthcare providers' attitudes. It underscores the importance of integrating caregiver and peer support. Findings advocate refining healthcare provider education, adopting a comprehensive multidisciplinary approach, and strategically incorporating eHealth tools into such care.

Frequency of vaccine hesitancy among patients with advanced cancer.

BACKGROUND: Vaccine hesitancy has become prevalent in society. Vulnerable populations, such as those with cancer, are susceptible to increased morbidity and mortality from diseases that may have been prevented through vaccination. OBJECTIVES: Our objective was to determine patient perception of vaccine efficacy and safety and sources of information that influence decisions. METHODS: This study was a prospective cross-sectional survey trial conducted from March 10, 2022, to November 1, 2022, at a Supportive Care Clinic. Patients completed the survey with a research assistant or from a survey link. Vaccine hesitancy was defined as a response of 2 or more on the Parent Attitudes About Childhood Vaccines (PACV-4). Perception on vaccine safety and efficacy along with the importance of sources of information were determined by a questionnaire. RESULTS: Of the 72 patients who completed the PACV-4, 30 were considered vaccine-hesitant (42%). Of those who completed the survey alone (35), 23 (66%) were vaccine-hesitant; and of those who completed the survey with the help of a study coordinator (37), 7 (19%) were vaccine-hesitant. The most important source for decision-making was their doctor (82%, 95% CI 73-89), followed by family (42%, 95% CI 32-52), news/media (31%, 95% CI 22-41), and social media (9%, 95% CI 4-16). Clinical and demographic factors including age, gender, race/ethnicity, education level, and location of residence were not associated with vaccine hesitancy. SIGNIFICANCE OF RESULTS: Vaccine hesitancy is present among patients with advanced cancer. The high value given to the doctor's recommendation suggests that universal precautions regarding vaccine recommendation may be an effective intervention.

Capacity Reconceptualized: From Assessment Tool to Clinical Intervention.

Capacity evaluation has become a widely used assessment device in clinical practice to determine whether patients have the cognitive ability to render their own medical decisions. Such evaluations, which might be better thought of as "capacity challenges," are generally thought of as benign tools used to facilitate care. This paper proposes that such challenges should be reconceptualized as significant medical interventions with their own set of risks, side effects, and potentially deleterious consequences. As a result, a cost-benefit analysis should be implemented prior to imposing such capacity challenges, and efforts should be made to minimize such challenges in situations where they are unlikely to alter the course of treatment.

Catholic Teaching: A Middle Ground and Guide for End-of-Life Care and Decision-Making and an Antidote for Dying Badly in America.

Dying in the United States is characterized as: medicalized, depersonalized, high technology, fragmented with frequent transitions among care settings, burdensome to patients and families, driven by efficiency and effectiveness, and lacking in key areas, for example, access to palliative care and adequate pain and symptom treatment. Patients and families are often left with a choice of two extremes: vitalism or utilitarian pessimism (utilitarianism). The Catholic Church, however, rejects both of these extremes, and Catholic social teaching (CST) at end of life focuses on ordinary-extraordinary treatments/means, a culture of life and human dignity, accompaniment and community, and caring for whole persons through the end of life. The Catholic tradition of ordinary-extraordinary means is helpful to guide complex end-of-life decisions, regardless of one's religious beliefs, and offers a middle ground between vitalism and utilitarianism that can inform end-of-life care and decision-making for all patients in Catholic health care. While it does not provide answers, it offers guidance and enables conversations that are crucial for the dying and their families to make autonomous, informed decisions about end-of-life care. It provides an opportunity for the dying to let the care team, loved ones, and decision-makers know what a life with meaning, purpose, and passion is for them-and how they want to live and die. This article will summarize the problem, describe end-of-life Catholic teaching, and discuss how it offers a middle-ground. Arguments for and against vitalism and utilitarianism will be explored, including a discussion of CST's response to those receiving care in Catholic health care facilities who are outside the Catholic tradition and do not believe in the teaching. The last section describes a model of collaborative partnership where local parishes and Catholic health care come together to tackle the challenges of caring for and ministering to the seriously ill and those facing death.

Beyond Autonomy: Ethics of Decision Making About Treatments for Kidney Failure at the Extremes of Age.

Decisions around initiating and forgoing treatments for kidney failure are complex, and contemporary approaches to medical decision making are designed to uphold patients' own preferences and values when there are multiple clinically reasonable treatment options. When patients do not have cognitive capacity to make their own decisions, these models can be adapted to support the previously expressed preferences of older adults and to promote open futures as autonomous persons for young children. Nonetheless, an autonomy-focused approach to decision making may not align with other overlapping values and needs of these groups. Dialysis profoundly shapes life experience. Values framing decisions about this treatment extend beyond independence and self-determination and vary between life stages. Patients at the extremes of age may place a strong emphasis on dignity, caring, nurturing, and joy. Models of decision making tailored to support an autonomous individual may also discount the role of family as not only surrogate decision makers but stakeholders whose lives and experience are interwoven with a patient's and will be shaped by their treatment decisions. These considerations underline a need to more flexibly incorporate a diversity of ethical frameworks to support medical decisions, especially for the very young and old, when facing complex medical decisions such as initiating or forgoing treatments for kidney failure.