Patient preference predictors (PPPs) promise to provide medical professionals with a new solution to the problem of making treatment decisions on behalf of incapacitated patients. I show that the use of PPPs faces a version of a normative problem familiar from legal scholarship: the problem of naked statistical evidence. I sketch two sorts of possible reply, vindicating and debunking, and suggest that our reply to the problem in the one domain ought to mirror our reply in the other. The (...) conclusion is thus conditional: if we think the problem of naked statistical evidence is a serious problem in the legal domain, then we should be concerned about the symmetrical problem for PPPs. (shrink)

Background: Current practice frequently fails to provide care consistent with the preferences of decisionally-incapacitated patients. It also imposes significant emotional burden on their surrogates. Algorithmic-based patient preference predictors (PPPs) have been proposed as a possible way to address these two concerns. While previous research found that patients strongly support the use of PPPs, the views of surrogates are unknown. The present study thus assessed the views of experienced surrogates regarding the possible use of PPPs as a means to (...) help make treatment decisions for decisionally-incapacitated patients. -/- Methods: This qualitative study used semi-structured interviews to determine the views of experienced surrogates [n=26] who were identified from two academic medical centers and two community hospitals. The primary outcomes were respondents’ overall level of support for the idea of using PPPs and the themes related to their views on how a PPP should be used, if at all, in practice. -/- Results: Overall, 21 participants supported the idea of using PPPs. The remaining five indicated that they would not use a PPP because they made decisions based on the patient’s best interests, not based on substituted judgment. Major themes which emerged were that surrogates, not the patient’s preferences, should determine how treatment decisions are made, and concern that PPPs might be used to deny expensive care or be biased against minority groups. -/- Conclusions: Surrogates, like patients, strongly support the idea of using PPPs to help make treatment decisions for decisionally-incapacitated patients. These findings provide support for developing a PPP and assessing it in practice. At the same time, patients and surrogates disagree over whose preferences should determine how treatment decisions are made, including whether to use a PPP. These findings reveal a fundamental disagreement regarding the guiding principles for surrogate decision-making. Future research is needed to assess this disagreement and consider ways to address it. (shrink)

Recently, Jardas _et al_ have convincingly defended the patient preference predictor (PPP) against a range of autonomy-based objections. In this response, I propose a new autonomy-based objection to the PPP that is not explicitly discussed by Jardas _et al_. I call it the ‘objection from higher-order preferences’. Even if this objection is not sufficient reason to reject the PPP, the objection constitutes a pro tanto reason that is at least as powerful as the ones discussed by Jardas _et (...) al._. (shrink)

When making substituted judgments for incapacitated patients, surrogates often struggle to guess what the patient would want if they had capacity. Surrogates may also agonize over having the (sole) responsibility of making such a determination. To address such concerns, a Patient Preference Predictor (PPP) has been proposed that would use an algorithm to infer the treatment preferences of individual patients from population-level data about the known preferences of people with similar demographic characteristics. However, critics have suggested (...) that even if such a PPP were more accurate, on average, than human surrogates in identifying patient preferences, the proposed algorithm would nevertheless fail to respect the patient’s (former) autonomy since it draws on the ‘wrong’ kind of data: namely, data that are not specific to the individual patient and which therefore may not reflect their actual values, or their reasons for having the preferences they do. Taking such criticisms on board, we here propose a new approach: the Personalized Patient Preference Predictor (P4). The P4 is based on recent advances in machine learning, which allow technologies including large language models to be more cheaply and efficiently ‘fine-tuned’ on person-specific data. The P4, unlike the PPP, would be able to infer an individual patient’s preferences from material (e.g., prior treatment decisions) that is in fact specific to them. Thus, we argue, in addition to being potentially more accurate at the individual level than the previously proposed PPP, the predictions of a P4 would also more directly reflect each patient’s own reasons and values. In this article, we review recent discoveries in artificial intelligence research that suggest a P4 is technically feasible, and argue that, if it is developed and appropriately deployed, it should assuage some of the main autonomy-based concerns of critics of the original PPP. We then consider various objections to our proposal and offer some tentative replies. (shrink)

In this paper, I set out two ethical complications for Rid and Wendler’s proposal that a “Patient Preference Predictor” (PPP) should be used to aid decision making about incapacitated patients’ care. Both of these worries concern how a PPP might categorize patients. In the first section of the paper, I set out some general considerations about the “ethics of apt categorization” within stratified medicine and show how these challenge certain PPPs. In the second section, I argue for a more (...) specific—but more contentious—claim that proper respect for the autonomy of incapacitated patients might require us to act on reasons which they could endorse and show how this claim places important limits on the categories employed by an ethically acceptable PPP. The conclusion shows how these concerns about apt categorization relate to more familiar worries about Rid and Wendler’s proposals. (shrink)

Introduction: This study, the first of its kind in Iran, was to assess Iranian patients’ preferences for receiving information and participating in decision-making and to evaluate their satisfaction with how medical information is given to them and with their participation in decision-making at present. Method and materials: 299 of 312 eligible patients admitted to general internal medicine or surgery wards from May to December 2006 were interviewed according to a structured questionnaire. The questionnaire contained questions about patients’ preferences (...) regarding four domains of information and their participation in decision-making. Patients’ responses were measured on a visual analogue scale graded from 1 to 10. Results: The mean (SD) score for desire to receive information was 8.88 out of 10 (1.5) and for participation in medical decision-making was 7.75 out of 10 (3). The desire to receive information was greater in women than men (9.0 (1.5) vs 7.8 (1.4), p = 0.025). It was also correlated with their education (r = 0.2, p = 0.001) and their estimation of the severity of their own disease (r = 0.13, p = 0.027). The score for preference to participate in decision-making was higher in women than in men (7.95 (2.8) and 7.0 (3.2), respectively; β = 0.8, p = 0.022) and was negatively correlated with education (r = −0.14, p = 0.015). Discussion: This study shows that Iranian patients are highly interested in receiving information about their condition and participating in clinical decision-making. No predictive variable for such attitudes was found; therefore, the only way for the physician to recognise patients’ desire is to ask them explicitly. (shrink)

Patient preference predictors aim to solve the moral problem of making treatment decisions on behalf of incapacitated patients. This commentary on a case of an unrepresented patient at the end of life considers 3 related problems of such predictors: the problem of restricting the scope of inputs to the models (the “scope” problem), the problem of weighing inputs against one another (the “weight” problem), and the problem of multiple reasonable solutions to the scope and weight problems (the “multiple (...) reasonable models” problem). Each of these problems poses challenges to reliably implementing patient preference predictors in important, high-stakes health care decision making. This commentary also suggests a way forward. (shrink)

Background: In the USA, the Food and Drug Administration waiver of informed consent permits certain emergency research only if community consultation occurs. However, uncertainty exists regarding how to define the community or their representatives.Objective: To collect data on the actual preferences and values of a group—those at risk for stroke—most directly affected by the waiver of informed consent for emergency research.Design: Face to face focused interviews were conducted with 12 patients who were hospitalised with a stroke diagnosis in the (...) previous year. The interviews were audiotaped and a transcript based method was used for their analysis.Results: All 12 participants felt “that it was important that new treatments for stroke be developed”, but they were initially confused about the distinction between “research for stroke” and “emergency research for stroke”. However, after explanation, most expressed willingness to participate in the latter. In the absence of a surrogate to give informed consent in a stroke emergency situation, the majority said they would want the physician to “go ahead and enrol them in the trial”.Conclusions: This study is the first to identify the values and concerns of individuals most directly affected by stroke emergency research. Further interviews and focus groups are needed to develop and test a validated questionnaire on the preferences and values surrounding emergency research for stroke. (shrink)

Patient preference predictors take us from known demographic descriptors to unknown facts about patients’ preferences over treatment options. However, the use of PPPs to make treatment decisions on behalf of incapacitated patients faces an apparent normative problem: their use in certain contexts appears to involve treating patients paternalistically. In this paper, I consider whether PPPs can find a home in the context of military medicine. On the assumptions that military organizations sometimes permissibly treat their members paternalistically, I identify (...) the specific circumstances in which PPPs can play a role in making treatment decisions on behalf of patients. I show that these circumstances are not only the natural home of PPPs, PPPs – or something very much like them – are precisely the sort of device required for it to be permissible to paternalistically override a patient’s expressed preferences. (shrink)

This study investigated patient preferences for various types of physician persuasion strategies. Four types of persuasion strategies were utilized which involved combination of high and low levels of affectivity and information. In addition, patient variables, receiver apprehension and health beliefs were introduced to predict preference choices by patients. Results indicated that patients are influenced in their decision-making (preferences) by the type of persuasive strategy employed. Further, patients with different characteristics and predispositions prefer different persuasive strategies. The (...) results of this study suggest that the success of physician persuasiveness is dependent upon the type of strategy used and the type of patient being persuaded. (shrink)

The standard approach to treatment decision making for incapacitated patients often fails to provide treatment consistent with the patient’s preferences and values and places significant stress on surrogate decision makers. These shortcomings provide compelling reason to search for methods to improve current practice. Shared decision making between surrogates and clinicians has important advantages, but it does not provide a way to determine patients’ treatment preferences. Hence, shared decision making leaves families with the stressful challenge of identifying the (...) patient’s preferred treatment option. To address this concern, the present paper proposes to incorporate the use of a “Patient Preference Predictor” (PPP) into the shared decision-making process between surrogates and clinicians. A PPP would predict which treatment option a given incapacitated patient would most likely prefer, based on the individual’s characteristics and information on what treatment preferences are correlated with these characteristics. Use of a PPP is likely to increase the chances that incapacitated patients are treated consistent with their preferences and values and might reduce the stress and burden on their surrogates. Including a PPP in the shared decision-making process therefore has the potential to realize important ethical goals for making treatment decisions for incapacitated patients. The present paper justifies this approach on conceptual and normative grounds. (shrink)

David Sackett and Jack Wennberg have each introduced and developed ideas and methods that have had major impacts on how we think about and perform clinical research. Sackett is best known for his work in Evidence-Based Medicine (Sackett et al. 1997); Wennberg, upon noting wide geographic (and other) variations in best practices for the same conditions, stressed the importance of comparative effectiveness in clinical decision-making (Wennberg et al. 1993). When these two collaborated in an editorial about the current state of (...) the art and science of clinical research, it comes as no great surprise that they produced some truly memorable guidance. And, as is so often the case for inspired—and inspiring—advice, their .. (shrink)

Despite the positive effects of including patients’ preferences into therapy on psychotherapy outcomes, there are still few thoroughly validated assessment tools at hand. We translated the 18-item Cooper-Norcross Inventory of Preferences into German and aimed at replicating its factor structure. Further, we investigated the reliability of the questionnaire and its convergence with trait measures. A heterogeneous sample of N = 969 participants took part in our online survey. Performing ESEM models, we found acceptable model fit for a four-factor (...) structure similar to the original factor structure. Furthermore, we propose an alternative model following the adjustment of single items. The German C-NIP showed acceptable to good reliability, as well as small correlations with Big-Five personality traits, trait and attachment anxiety, locus of control, and temporal focus. However, we recommend further replication of the factor structure and further validation of the C-NIP. (shrink)

The Patient Preference Predictor (PPP) is intended to improve treatment decision making for incapacitated patients. The PPP would collect information about the treatment preferences of people with different demographic and other characteristics. It could be used to indicate which treatment option an individual patient would be most likely to prefer, based on data about the preferences of people who resemble the patient. The PPP could be incorporated into existing US law governing treatment for incapacitated patients, (...) although it is unclear whether it would be classified as evidence of a specific patient’s preferences or those of a reasonable person sharing certain characteristics with the patient. Ethical concerns about the quality and significance of PPP choices could influence legal decision makers’ views of the PPP. (shrink)

Bioethics, Volume 36, Issue 4, Page 388-402, May 2022.

Like many, I find the idea of relying on patient preference predictors in life-or-death cases ethically troubling. As part of his stimulating discussion, Sharadin1 diagnoses such unease as a worry that using PPPs disrespects patients’ autonomy, by treating their most intimate and significant desires as if they were caused by their demographic traits. I agree entirely with Sharadin’s ‘debunking’ response to this concern: we can use statistical correlations to predict others’ preferences without thereby assuming any causal claim. However, (...) I suspect that, for at least some of us, our unease about PPPs stems from a different kind of ‘autonomy’ concern. In this commentary, then, I will explore this concern, and show how it relates to Sharadin’s work. Very many of our preferences are caused, ultimately, by facts which are outside our control, such as our demographic features. However, I suggest that we can still act autonomously on the basis of such preferences, when they are preferences which we endorse. Imagine, for example, that Jane has grown up in a church-growing environment, which has shaped many of her preferences, …. (shrink)

The question of how to treat an incapacitated patient is vexed, both normatively and practically—normatively, because it is not obvious what the relevant objectives are; practically, because even once the relevant objectives are set, it is often difficult to determine which treatment option is best given those objectives. But despite these complications, here is one consideration that is clearly relevant: what a patient prefers. And so any device that could reliably identify a patient’s preferences would be (...) a promising tool for guiding the treatment of incapacitated patients. The patient preference predictor is just such a tool—an algorithm that takes as inputs a patient’s sociodemographic characteristics, and outputs a reliable prediction about that patient’s treatment preferences.1 But some have worried that the use of such a tool would violate or fail to appropriately respect patients’ autonomy. There are, I think, two ways to understand this kind of criticism. First, globally—as a worry that any systematic implementation of the PPP would be problematic on the grounds that it would result in significant or pervasive autonomy violations. Second, locally—as a worry that in some important range of cases, certain uses of the PPP would be problematic on autonomy grounds. Jardas et al, as I read them, address global autonomy-based criticisms, arguing—convincingly, in my view—that there’s no reason to suspect the autonomy concerns raised by the PPP would be so significant and pervasive as to render any implementation of it generally problematic.1 But even with the global criticisms rebuffed, there remains work to be done. Any ethically acceptable implementation of the PPP must be sensitive to the more local autonomy-based criticisms, with restrictions and safeguards in place to ensure respect for autonomy in the kinds of cases in which the use of the PPP might otherwise threaten …. (shrink)

There are substantial data establishing that surrogates are often mistaken in predicting what treatments incompetent patients would have wanted and that supplements such as advance directives have not resulted in significant improvements. Rid and Wendler’s Patient Preference Predictor (PPP) proposal will attempt to gather data about what similar patients would prefer in a variety of treatment choices. It accepts the usual goal of patient autonomy and the Substituted Judgment principle for surrogate decisions. I provide reasons for questioning sole (...) reliance on autonomy when surrogates, not patients, are deciding and for giving some independent weight to patient well-being. Moreover, that family members, typical surrogates, will know best what the patient if incompetent would have wanted is not the only reason why they are chosen. The more pressing problem is that the PPP would fail to remove the more serious mistakes that empirical psychology over the last few decades has shown to infect such decision making. (shrink)

Background Although medical ethicists and educators emphasise patient-centred decision-making, previous studies suggest that patients often prefer their doctors to make the clinical decisions. Objective To examine the associations between a preference for physician-directed decision-making and patient health status and sociodemographic characteristics. Methods Sociodemographic and clinical information from all consenting general internal medicine patients at the University of Chicago Medical Center were examined. The primary objectives were to (1) assess the extent to which patients prefer an active role in (...) clinical decision-making, and (2) determine whether religious service attendance, the importance of religion, self-rated spirituality, Charlson Comorbidity Index, self-reported health, Vulnerable Elder Score and several demographic characteristics were associated with these preferences. Results Data were collected from 8308 of 11 620 possible participants. Ninety-seven per cent of respondents wanted doctors to offer them choices and to consider their opinions. However, two out of three (67%) preferred to leave medical decisions to the doctor. In multiple regression analyses, preferring to leave decisions to the doctor was associated with older age (per year, OR=1.019, 95% CI 1.003 to 1.036) and frequently attending religious services (OR=1.5, 95% CI 1.1 to 2.1, compared with never), and it was inversely associated with female sex (OR=0.6, 95% CI 0.5 to 0.8), university education (OR=0.6, 95% CI 0.4 to 0.9, compared with no high school diploma) and poor health (OR=0.6, 95% CI 0.3 to 0.9). Conclusions Almost all patients want doctors to offer them choices and to consider their opinions, but most prefer to leave medical decisions to the doctor. Patients who are male, less educated, more religious and healthier are more likely to want to leave decisions to their doctors, but effects are small. (shrink)

The patient preference predictor is a proposed computer-based algorithm that would predict the treatment preferences of decisionally incapacitated patients. Incorporation of a PPP into the decision-making process has the potential to improve implementation of the substituted judgement standard by providing more accurate predictions of patients’ treatment preferences than reliance on surrogates alone. Yet, critics argue that methods for making treatment decisions for incapacitated patients should be judged on a number of factors beyond simply providing them with the (...) treatments they would have chosen for themselves. These factors include the extent to which the decision-making process recognises patients’ freedom to choose and relies on evidence the patient themselves would take into account when making treatment decisions. These critics conclude that use of a PPP should be rejected on the grounds that it is inconsistent with these factors, especially as they relate to proper respect for patient autonomy. In this paper, we review and evaluate these criticisms. We argue that they do not provide reason to reject use of a PPP, thus supporting efforts to develop a full-scale PPP and to evaluate it in practice. There are no data in this work. (shrink)

Interventional cardiologists are commonly faced with patients who prefer percutaneous coronary intervention (PCI) rather than coronary artery bypass surgery (CABG). Many prefer PCI even when CABG is recommended. Doctors may wonder whether (as the cardiac surgeons suspect) they consciously or unconsciously influence patients to choose PCI. We consider reasons why patient preferences in this context are not irrational.

It has recently been proposed to incorporate the use of a “Patient Preference Predictor” (PPP) into the process of making treatment decisions for incapacitated patients. A PPP would predict which treatment option a given incapacitated patient would most likely prefer, based on the individual’s characteristics and information on what treatment preferences are correlated with these characteristics. Including a PPP in the shared decision-making process between clinicians and surrogates has the potential to better realize important ethical goals for (...) making treatment decisions for incapacitated patients. However, developing and implementing a PPP poses significant practical challenges. The present paper discusses these practical challenges and considers ways to address them. (shrink)

In their contribution ‘Ethics of the algorithmic prediction of goal of care preferences’1 Ferrario et al elaborate a from theory to practice contribution concerning the realisation of artificial intelligence (AI)-based patient preference prediction (PPP) systems. Such systems are intended to help find the treatment that the patient would have chosen in clinical situations—especially in the intensive care or emergency units—where the patient is no longer capable of making that decision herself. The authors identify several challenges that (...) complicate their effective development, application and evaluation—and offer solutions to them. One of these issues is the question of who should ultimately use said systems. While it is undisputed that clinicians should use these AI systems for their decision-making process, there is an ongoing debate about whether next of kin should use them as well. The authors advocate that ‘’access should be provided to both clinicians and loved ones with due explanations and as desired’. We will disagree with this assessment and explain in our commentary why it is important that surrogates provide their own assessments with as little external (AI) influence as possible. Why do next of kin actually participate in the process of preference finding and treatment decision-making? A key reason is that clinicians usually …. (shrink)

When a patient lacks sufficient capacity to make a certain treatment decision, whether because of deficits in their ability to make a judgement that reflects their values or to make a decision that reflects their judgement or both, the decision must be made by a surrogate. Often the best way to respect the patient’s autonomy, in such cases, is for the surrogate to make a ‘substituted’ judgement on behalf of the patient, which is the decision that best (...) reflects the patient’s values and identity-infused beliefs as they were when the patient last possessed capacity. It is by now well-known that there is troubling evidence that surrogates do only slightly better than chance at making accurate substituted judgements. The use of a patient preference predictor, an algorithm that predicts patient preferences based on characteristics like the patient’s age, gender, socioeconomic status and education level, could help. Rid and Wendler have done important work making a moral case for using the PPP.1 If it were shown to enhance accuracy, it is not at all obvious what objections there could be to its use. Yet several subtle criticisms of the PPP have emerged in the literature. In their feature article, Jardas, Wasserman and Wendler select six of the most prominent objections to the PPP in the literature and defend the PPP against them.2 Along the way they make significant contributions to broader issues concerning the proper uses of statistical evidence and limits on the kinds of preferences there can be reasons of autonomy to respect. Since I found the authors’ answers to the final two objections—that the PPP relies on naked statistical evidence and that it uses non-endorsed reasons—to be especially interesting and provocative, I will examine those answers and raise a few questions about …. (shrink)

The more we know about medicine, the more we realize that many health questions have no one true answer. Realizing this, and thinking carefully about how medicine asks patients to treat their conditions, leads us to some questions. How reliable are the guidelines that might form the basis of doctors’ advice? Is it wrong, after all, to base an approach to medicine on patients’ preferences? And, given that there is often a distance between the treatment a doctor advises and (...) what a patient would like to do, how do we bridge the gap—especially in a health culture of inequality, technical proficiency, and increasing costs? In practical, engaging, narrative-driven chapters about common health conditions that millions of Americans are familiar with—depression and high blood pressure, arthritis and diabetes—Dr. Zackary Berger of Johns Hopkins demystifies the often bewildering disconnect between patients and doctors and asks us all to think more clearly about how best to protect and cure the human body. (shrink)

The authors respond to four JME commentaries on their Feature Article, ‘Autonomy-based criticisms of the patient preference predictor’.

This paper presents the results of a qualitative interview study exploring English and French physicians’ moral perspectives and attitudes towards end-of-life decisions when patients lack capacity to make decisions for themselves. The paper aims to examine the importance physicians from different contexts accord to patient preferences and to explore the role of advance directives in each context. The interviews focus on problems that emerge when deciding to withdraw/-hold life-sustaining treatment from both conscious and unconscious patients; decision-making procedures and (...) the participation of proxies/relatives; previous experience with ADs and views on their usefulness; and perspectives on ways in which the decision-making processes in question might be improved. The analysis reveals differences in the way patient preferences are taken into consideration and shows how these differences influence the reasons physicians in each country invoke to justify their reluctance to adhering to ADs. Identifying cultural differences that complicate efforts to develop the practical implementation of ADs can help to inform national policies governing ADs and to better adapt them to practice. (shrink)

In our recent article ‘The Ethics of the Algorithmic Prediction of Goal of Care Preferences: From Theory to Practice’1, we aimed to ignite a critical discussion on why and how to design artificial intelligence (AI) systems assisting clinicians and next-of-kin by predicting goal of care preferences for incapacitated patients. Here, we would like to thank the commentators for their valuable responses to our work. We identified three core themes in their commentaries: (1) the risks of AI paternalism, (2) (...) worries about attacks to our humanity stemming from the use of AI and (3) the possibility of designing AI systems for more relevant use cases than the one we consider in our work. We shall focus on these themes, leaving aside some other interesting suggestions, given the limited space available for our response. Diaz Milian and Bhattacharyya discuss the risks of AI paternalism highlighting how the use of an AI to predict goal of care preferences may incentivise clinicians and surrogates to shift the burden of decision making to the machine.2 In particular, ‘[i]f the AI-generated response is given priority above the other agents’2 and the AI makes decisions autonomously, then ‘AI paternalism’ would emerge.2 Against this possibility, the authors suggest four safeguards to be implemented in the AI life-cycle.2 These are procedures that may improve the trustworthiness of the AI and human control over it.3 We agree that it is important …. (shrink)

BackgroundMany procedures currently require the use of bone grafts to replace or recover bone volume that has been resorbed. However, the patient’s opinion and preferences must be taken into account before implementing any treatment. Researchers have focused primarily on assessing the effectiveness of bone grafts rather than on patients' perceptions. Thus, the aim of this study was to explore patients' opinions regarding the different types of bone grafts used in dental treatments.MethodsOne hundred patients were randomly chosen participated in (...) the study. A standardized survey of 10 questions was used to investigate their opinions regarding the different types of bone grafts used in dental treatments. Descriptive statistics were calculated for the different variables, and absolute frequencies and percentages were used as summary measures. A value of p <0.05 was selected as the threshold for statistical significance.ResultsThe highest rate of refusal was observed for allografts and xenografts. The grafts with the lowest rates of refusal were autologous grafts and alloplastics. No significant differences were found between the various types of bone grafts in the sociodemographic variables or the refusal/acceptance variable. Similarly, no significant relations were observed between a specific religious affiliation and the acceptance/refusal rates of the various types of graft.ConclusionsAllografts and xenografts elicited the highest refusal rates among the surveyed patients, and autologous bone and alloplastics were the most accepted bone grafts. Moreover, no differences were found in the sociodemographic variables or religious affiliations in terms of the acceptance/refusal rates of the different bone grafts. (shrink)

Previous studies have documented the fallibility of attempts by surrogates and physicians to act in a substituted judgment capacity and predict end-of-life treatment decisions on behalf of patients. We previously reported that physicians misperceive their patients' preferences and substitute their own preferences for those of their patients with respect to four treatments: cardiopulmonary resuscitation in the event of cardiac arrest, ventilator for an indefinite period of time, medical nutrition and hydration for an indefinite period of time, and hospitalization (...) in the event of pneumonia. (shrink)

Aim: To improve clinical and ethical understanding of patient preferences for information and involvement in decision making.Objectives: To develop and evaluate a clinical tool to elicit these preferences and to consider the ethical issues raised.Design: A before and after study.Setting: Three UK hospices.Participants: Patients with advanced life-threatening illnesses and their doctors.Intervention: Questionnaire on information and decision-making preferences.Main outcome measures: Patient-based outcome measures were satisfaction with the amount of information given, with the way information was given, (...) with family or carer information, and confidence about future decision making. Doctor-based outcome measures were confidence in matching information to patient preference, matching family or carer communication to patient preference, knowing patient preferences and matching future decision making with patient preference.Results: Of 336 admissions, 101 patients completed the study . Patient satisfaction with the way information was given and family communication improved after introduction of the tool. Doctor confidence improved across all outcome measures .Conclusions: Patient satisfaction and doctor confidence were improved by administering the questionnaire, but complex ethical issues were raised by implementing and applying this research. The balance of ethical considerations were changed by advanced life-threatening illness, because there is increased risk of harm through delivery of information discordant with the patient’s own preferences. The importance of truly understanding patient preferences towards the end of life is highlighted by this study. (shrink)

Background We present and discuss the results of a Norwegian survey of medical doctors' views on potential ethical dilemmas in professional practice. Methods The study was conducted in 2015 as a postal questionnaire to a representative sample of 1612 doctors, among which 1261 responded. We provided a list of 41 potential ethical dilemmas and asked whether each was considered a dilemma, and whether the doctor would perform the task, if in a position to do so. Conceptually, dilemmas arise because of (...) tensions between two or more of four doctor roles: the patient’s advocate, a steward of societal interests, a member of a profession and a private individual. Results 27 of the potential dilemmas were considered dilemmas by at least 50% of the respondents. For more than half of the dilemmas, the anticipated course of action varied substantially within the professional group, with at least 20% choosing a different course than their colleagues, indicating low consensus in the profession. Conclusions Doctors experience a large range of ethical dilemmas, of which many have been given little attention by academic medical ethics. The less-discussed dilemmas are characterised by a low degree of consensus in the profession about how to handle them. There is a need for medical ethicists, medical education, postgraduate courses and clinical ethics support to address common dilemmas in clinical practice. Viewing dilemmas as role conflicts can be a fruitful approach to these discussions. (shrink)

Previous studies have documented the fallibility of attempts by surrogates and physicians to act in a substituted judgment capacity and predict end-of-life treatment decisions on behalf of patients. We previously reported that physicians misperceive their patients' preferences and substitute their own preferences for those of their patients with respect to four treatments: cardiopulmonary resuscitation (CPR) in the event of cardiac arrest, ventilator for an indefinite period of time, medical nutrition and hydration for an indefinite period of time, and (...) hospitalization in the event of pneumonia. (shrink)