Abstract Rationale, aims and objectives Patient-centered care is considered as a vital component of good quality of care for breast cancer patients. Nevertheless, the implementation of this valuable theoretical concept into practice appears to be difficult. The goal of this study was to bridge the gap between the theoretical elaboration of ‘patient-centered care’ and clinical practice. For that purpose, the current application of the term ‘patient-centered care in breast cancer treatment’ was deduced from present-day literature. Method The methodology of a scoping review was employed. Results A notable lack of consistency in use of the term ‘patient-centered care’ is demonstrated in recent literature concerning breast cancer treatment. We also observe an unambiguous positive vision on this rather vague concept. Conclusions Contrary to previous efforts to define ‘patient-centered care’ more narrowly, we propose to embrace the heterogeneity of this concept and apply ‘patient-centered care’ as an umbrella-term for all healthcare that (intends to) contribute to the acknowledgement of the person in the patient. For the justification of measures to realize patient-centered care, we insist on the demonstration of desirable real-world effects, instead of a mere contribution to this abstract term.

TitleOn Metabolism: Ensuring Our Health Care System Remains “Ready-to-Hand”

Rationale, aims, and objectives: The complexity of healthcare systems makes errors unavoidable. To strengthen the dialogue around how physicians experience and share medical errors, the objective of this study was to understand how experienced generalist physicians make meaning of and grow from their medical errors. Methods: This study used a narrative inquiry approach to conduct and analyze in-depth interviews from 26 physicians from the generalist specialties of emergency, internal, and family medicine. We gathered stories via individual interview, analyzed them for key components, and rewrote a ‘meta-story’ in a chronological sequence. We conceptualized the findings into a metaphor to draw similarities, learn from, and apply new principles from other fields of practice. Results: Through analysis we interpreted the story of an elite athlete (physician) who is required to make numerous decisions in a short period of time within the construct of a chaotic sports field (clinical environment) among spectators (the patient’s family) whilst abiding by existing rules and regulations. Through sharing stories of success and failure, the team coach (clinical mentor) helps optimize the players’ professional and psychological development. Similarly, through sharing and learning from stories, team members (colleagues) and junior team members (trainees) also contribute to the growth of the protagonist’s character and the development of the overall team (clinic/hospital) and sport (healthcare system). Conclusion: We draw parallels between the clinical setting and a generalist physician’s experiences of a medical error with the environment and practices within professional sports. Using this comparison, we discuss the potential for meaningful coaching in medical education.

Rationale. Evidence-based practice (EBP) can improve health care in underprivileged countries. Bolivia’s EBP movement is nascent and the factors contributing to better implementation in nursing are unknown. Aim. To explore Bolivian nurses’ readiness to engage in EBP while highlighting the facilitators and barriers for pursuing EBP. Method. International collaborators used a sequential explanatory mixed methods study. First, general trends were disclosed via a survey of 170 nurses in La Paz, Bolivia, holding at least a baccalaureate regarding their perceived beliefs about EBP. The survey identified facilitators and barriers for implementing EBP in acute and ambulatory settings. Second, qualitative data was gathered via a focus group of nine nurses with the purpose of enhancing the survey findings. Results. The survey results showed that nurses believe that engaging in EBP can improve their clinical practice. However, the nurses’ research behaviors were found to be infrequent. Lack of support from the nurses’ clinics and hospitals and from non-nursing professionals were identified as barriers for engaging in EBP. The qualitative results revealed underlying limitations to nurses’ clinical practice, including “feeling undervalued.” Conclusions. There is a dearth of EBP knowledge among Bolivian nurses stemming from a lack of preparation in EBP environments, including EBP training opportunities. This situation affects nurses’ professional dimensions of relational work, power, and collaboration. Collaborative research among educators, professional nursing societies, and local and international organizations could provide initiatives for implementing EBP, based on local health profiles. Key words: international collaboration, evidence-based practice, nurse-multidisciplinary relationship, barriers to EBP.

ABSTRACT Rationale, aims and objectives The primary aim of the study was to understand the mindset of doctors and pharmacists, as they embark upon prescribing in a polypharmacy and multi-morbidity context during routine practice at a hospital acute admissions unit. The study also aimed to evaluate to what extent attitudes, embedded within real-life decision-making scenarios, relate to existing theory and models of prescribing decisions. Methods Anonymised case studies were identified from the medical notes of patients aged 65 and over with conditions likely to be associated with multi-morbidity, medication issues and polypharmacy: namely: fall, urinary tract infection, confusion or lower respiratory tract infection. A total of 39 doctors based on the acute medical admissions unit and 9 pharmacists were recruited to one of three focus groups. Patient case-studies provided the context for discussion from which verbatim transcripts were thematically analysed using an interpretative, qualitative approach. Sub-themes were matched to Murshid and Mohaidin’s proposed model of physician prescribing decisions. Results Seven principal themes were identified that were associated with prescribing decisions on the acute medical unit, namely, ‘patient characteristics’, ‘drug characteristics’, ‘pharmacist factors’, ‘trustworthiness’, ’reliability of medication history, ‘competing pressures and priorities’ and ‘responsibilities of prescribers’. Conclusion Prescribing decisions on the acute medical admissions unit were influenced by a variety of factors, some of which have already been acknowledged within existing theories and models. The findings provisionally offer new insights, which, subject to confirmation by further research, bring to light three attitudinal characteristics that may impact negatively upon the quality of prescribing decisions. These include, first, how perceived poor reliability of medication history may result in information gaps that compromise prescribing decisions; second, how competing pressures and priorities restrict doctors’ aptitude to conduct a review of medication and finally, how doctors may rationalise the assignment of medication review to the GP.

Linden and Yarnold1 recently proposed classification tree analysis (CTA), a machine‐learning procedure, as an alternative to conventional methods for analyzing mediation effects in treatment-outcome research. They note that CTA may have a number of advantages in this regard. It requires no assumptions about the distribution of variables or the functional form of the best-fitting model, for example, thus affording greater potential flexibility in identifying complex forms of association among variables with varying scales of measurement (e.g., binary and continuous). The authors further argue that CTA, unlike conventional approaches to testing mediation, “will not generate a model if a treatment-mediator-outcome relationship does not exist” (p. 359) and, conversely, that CTA “will systematically identify a treatment-by-mediator interaction if it exists, as well as any other interaction between variables.” (p. 359). Using data from the Job Search Intervention Study (JOBS II), they find that structural equation modeling, a conventional approach to testing mediation, failed to indicate support for job-search self-efficacy as a mediator of the effects of the intervention on whether the study participant was reemployed at follow-up. In contrast, the authors conclude that CTA applied to the same set of variables revealed that job-search self-efficacy was a mediator of intervention effects on employment among those in the treatment group.There are, however, two problematic aspects of the authors’ approach. First, as they point out, causal inference of a mediational pathway depends on the assumption that the associations involved exist net of potential confounding variables. In a randomized control trial such as JOBS II, confounding of the association between the mediator and outcome is of particular concern.2 The authors seek to address this concern by conducting a CTA that includes a set of 9 potential confounders (e.g., income, age, initial level of depressive symptoms) as candidate predictors. This approach does not ensure statistical control for these variables, however, for at least two reasons. First, there is no guarantee that the variables involved will actually be included in the resulting classification tree; failing to meet the criterion for inclusion does not rule out the possibility that a given potential confounder or combination of such confounders nonetheless share an association with the mediator and outcome to an extent that renders their association non-significant. This concern proves pertinent to the authors’ analysis as only 3 of the potential confounders earn entry into the resulting classification tree for reemployment status. A second concern with the approach taken by the authors is that whatever covariates are included in the classification tree may be included in positions that are inadequate for the purpose of controlling for confounding of the mediator-outcome association. Gender, for example, in their analysis is included in the control group branch of the tree, whereas job-search self-efficacy, the potential mediator, is included only in the treatment group arm. As a further example, education is included on the treatment group arm, but only after job-search self-efficacy’s role in the model already has already been established through its inclusion on a higher tier of the model. An alternative approach for addressing confounding in the context of CTA would be to residualize the candidate mediator on possible confounders and then fit a classification tree with this adjusted variable. If the residualized mediator continues to discriminate across levels of the outcome, conditional on treatment status, it could be concluded that the mediate-outcome portion of the potential mediational pathway of interest is evident independent of the measured confounders. Applying this approach, I find that the job-search self-efficacy continues to emerge as a discriminating variable for reemployment in the treatment arm branch of the classification tree that I fit with the same JOBS-II data. However, it cannot be assumed that this more rigorous approach to taking into account confounders will always yield the same result as one in which they are merely included as candidate predictors within a CTA.A more fundamental concern with the CTA approach to identifying mediation employed by the authors is that the mediator in the predictor-mediator and mediator-outcome segments of the mediational pathway are not assured of having a consistent definition. This is a result of the optimal cut-point on the mediator being determined separately for the two segments, through an optimal discriminant analysis for the treatment-mediator segment and CTA for the mediator-outcome segment. Thus, in the case of the mediational pathway for reemployment, treatment status predicts a dichotomous measure of job-search self-efficacy determined by a cut-score of 3.92 (i.e., high job-search self-efficacy corresponds to values above 3.92 and low to values equal to and below 3.92), whereas the dichotomous measure of job-search self-efficacy predicting reemployment is determined by a different cut-score of 4.92. Yet, it is essential by definition that the mediator in a mediational pathway that is influenced by the initial variable in the pathway (in this case, treatment) be the same variable that then influences the outcome (in this case, reemployment). In this case, nearly one half of the sample (47.3%; n = 426) has a different high-low classification on the job-search self-efficacy, suggesting considering divergence between the versions of this variable determined by the respective cut-scores. One approach to addressing this concern would be to define a new mediator that reflects the overlapping portion of the differing definitions. In the present example, this could be a dichotomous measure of job-search self-efficacy defined by a cut-score of greater 3.92, which would ensure that all those with scores classified as relatively high on the measure continue to be classified as such; alternatively, a cut-score of 4.92 could be used if priority is given to ensuring that all those classified as low remain in this category. Still another option would be to use the mid-point between the two cut-scores of 4.42. One could then evaluate the mediational pathway of interest using one or more of these options. Applying this approach using PROC CAUSALMED in SAS3, allowing for the suggested treatment-mediator interaction and including all covariates, I find evidence of an indirect mediated pathway when using the lower bound cut-off score of 3.92 for job-search self-efficacy (Odds Ratio for natural indirect effect of .959, 95% CI limits of .893, .998), but not when using the other two cut-off scores, although the differences in estimates are admittedly small in this case (complete results are available upon request).To summarize, Linden and Yarnold (2018) make a significant contribution by introducing CTA as a promising strategy for identifying mediated effects in intervention research. Further refinements to their approach, however, are recommended to more fully incorporate fundamental assumptions that accompany all tests for mediation as well as to evaluate and confirm potential mediational pathways using conventional procedures.References1Linden A, Yarnold PR. Identifying causal mechanisms in health care interventions using classification tree analysis. J Eval Clin Pract. 2018;24:353–361. https://doi.org/10.1111/jep.128482Imai K, Keele L, Tingley D. A general approach to causal mediation analysis. Psychol Methods . 2010;15:309‐334.3Yung, Y, Lamm, M, Zhang, W. Causal Mediation Analysis with the CAUSALMED Procedure . Paper SAS1991-2018. Cary, NC: SAS Institute Inc.; 2018.

Rationale, aims and objectives In the US, the reluctance of the federal government to impose a national stay-at-home policy in wake of COVID19 pandemic has left the decision of how to achieve social distancing to individual state governors. We hypothesized that in the absence of formal guidelines, the decision to close a state reflects the classic Weber-Fechner law of psychophysics- the amount by which a stimulus (such as number of cases or deaths) must increase in order to be noticed as a fraction of the intensity of that stimulus. Methods On April 12, 2020 we downloaded data from the New York Times database from all 50 states and the District of Columbia; by that time all but 7 states had issued the stay-at-home orders. We fitted the Weber-Fechner logarithmic function by regressing the log2 of cases and deaths respectively against the daily counts. We also conducted Cox regression analysis to determine if the probability of issuing the stay-at-home order increases proportionally as the number of cases or deaths increases. Results We found that the decision to issue the state-at-home order reflects the Weber-Fechner law. Both the number of infections (p=<0.0001; R2=0.79) and deaths (p<0.0001; R2=0.63) were significantly associated with the decision to issue the stay-at-home orders. The results indicate that for each doubling of infections or deaths, an additional 4 to 6 states will issue stay-at-home orders. Cox regression showed that when the number of deaths reached 256 and the number of infected people were over 16,000 the probability of issuing “stay-at-home” order was close to 100%. We found no difference in decision-making according to the political affiliation; the results remain unchanged on July 16,2020. Conclusions when there are not clearly articulated rules to follow, decision-makers resort to simple heuristics, in this case one consistent with the Weber-Fechner law.

Background: The health care delivery model in the United States does not work; it perpetuates unequal access to care, favors treatment over prevention, and contributes to persistent health disparities and lack of insurance. The historical lack of support in the United States for primary health care, universal health coverage, population health, addressing the social determinants of health, and community empowerment, creates opportunities for community health scientists to develop innovative solutions for addressing community health needs. Methods: We developed a model community health science approach combining community-oriented primary care (COPC), community-based participatory research (CBPR), asset-based community development, and service learning principles. The approach defines health as a social outcome, resulting from a combination of clinical science, collective responsibility, and informed social action. Results: From 2000-2020, we established partnerships with community organizations to reduce the risk of chronic disease in vulnerable minority communities. Our programs have provided structured community health science training for hundreds of physicians and other health care workers in training. Conclusion: As the U.S. begins to seek solutions to chronic health disparities and health inequities, community health science provides useful lessons in how to engage communities to address the deficits of the current system. Perhaps the greatest error that U.S. health care systems could make in trying to better address population health and the social determinants of health, would be ignoring the important community initiatives already underway in most local communities. Building partnerships based on local resources and ongoing social determinants of health initiatives is the key for medicine to meaningfully engage communities for reducing health disparities. This has been the greatest lesson we have learned during the past two decades, has provided the foundation for our community health science approach, and accounts for whatever success we have achieved.

Rationale Assessing the performance of diagnostic tests requires evaluation of the amount of diagnostic uncertainty the test reduces (i.e. 0% - useless test, 100% - perfect test). Statistical measures currently dominating the evidence-based medicine (EBM) field and particularly meta-analysis (e.g. sensitivity and specificity), cannot explicitly measure this uncertainty reduction. Mutual information (MI), an information theory statistic, is a more appropriate metric for evaluating diagnostic tests as it explicitly quantifies uncertainty and, therefore, facilitates natural interpretation of a test’s value. In this paper, we propose the use of MI as a single measure to express diagnostic test performance and demonstrate how it can be used in meta-analysis of diagnostic test studies. Methods We use two cases from the literature to demonstrate the applicability of MI meta-analysis in assessing diagnostic performance. These cases are: 1) Meta-analysis of studies evaluating ultrasonography (US) to detect endometrial cancer and 2) meta-analysis of studies evaluating magnetic resonance angiography to detect arterial stenosis. Results Results produced by the MI meta-analyses are comparable to the results of meta-analyses based on traditionally used statistical measures. However, the results of MI are easier to understand as it relates directly to the extent of uncertainty a diagnostic test can reduce. For example, a US test diagnosing endometrial cancer is 40% specific and 94% sensitive. The combination of these values is difficult to interpret and may lead to inappropriate assessment (e.g. one could favour the test due to its high sensitivity, ignoring its low specificity). In terms of MI however, the test reduces diagnostic uncertainty by 10%, which is marginal and thus the test is clearly not very useful. Conclusions We have demonstrated the suitability of MI in assessing the performance of diagnostic tests, which can facilitate easier interpretation of the true utility of diagnostic tests.

Purpose This paper aims to elucidate the factors that play into physicians’ experience of receiving practice data and to subsequently develop a model that describes how individuals may interact with the data they receive. Methods In a prior study, we conducted a needs analysis of 105 physicians in the Hamilton-Niagara area in order to understand which data metrics were most valuable to physicians. Using these results, we designed an interview guide to study physicians’ perspectives on audit and feedback. By intentional sampling, we recruited 15 physicians amongst gender groups, types of practice (academic vs community), and duration of practice. The interviews were conducted by a single author and transcribed without identifiers. We then began with an open coding analysis for all of the transcripts, and thereafter conducted axial coding to group the data into larger themes. Results Several environmental and personal attributes were identified as either enabling or counterproductive attributes for participant improvement. The final proposed model identifies different zones of engagement on the basis of both the individual practitioner’s growth mindset and the quality of the existing data system. In the highest engagement zone, the mindset of the collective leadership is one of growth. Systemic supports are in place which potentiates learning that may come from an individual motivated to use their own data. Conclusion Our model shows how data feedback systems and individual growth-oriented mindsets interact to augment or hinder clinical practice improvement. This model provides important guidance to academic and administrative structures looking to develop appropriate performance feedback systems with clinicians.

The COVID-19 has posed a wide range of urgent questions: about the disease, testing, immunity, treatments, and outcomes. Extreme situations, such as pandemics, call for exceptional measures. However, this threatens the production and application of evidence. This paper directs evidence production towards four types of uncertainty in order to address the challenges of the pandemic: Risk, Fundamental uncertainty, Ignorance, and Ambiguity. Eliminating ambiguity, being alert to the unknown, and gathering data to estimate risks are crucial to preserve evidence and save lives. Hence, in order to avoid fake facts and to provide sustainable solutions we need to pay attention to the various kinds of uncertainty. Producing high quality evidence is the solution, not the problem.

Rationale, aims and objectives New therapies are increasingly approved by regulatory agencies such as the Food and Drug Administration (FDA) and the European Medicines Agency (EMA) based on testing in non-randomized clinical trials. These treatments have typically displayed “dramatic effects” (i.e., effects that are considered large enough to obviate the combined effects of bias and random error). The agencies, however, have not identified how large these effects should be to avoid the need for further testing in randomized controlled trials (RCTs). We investigated the effect size that would circumvent the need for further RCTs testing by the regulatory agencies. We hypothesized that the approval of therapeutic interventions by regulators is based on heuristic decision-making whose accuracy can be best characterized by the application of signal detection theory (SDT). Methods We merged the EMA and FDA database of approvals based on non-RCT comparisons. We excluded duplicate entries between the two databases. We included a total of 134 approvals of drugs and devices based on non-RCTs. We integrated Weber-Fechner law of psychophysics and recognition heuristics within SDT to provide descriptive explanations of the decisions made by the FDA and EMA to approve new treatments based on non-randomized studies without requiring further testing in RCTs. Results Our findings suggest that when the difference between novel treatments and the historical control is at least one logarithm (base 10) of magnitude, the veracity of testing in non-RCTs seems to be established. Conclusion Drug developers and practitioners alike can use the change in one logarithm of effect size as a benchmark to decide if further testing in RCTs should be pursued, or as a guide to interpreting the results reported in non-randomized studies. However, further research would be useful to better characterize the threshold of effect size above which testing in RCTs is not needed.

Sturmberg and Martin in 2020 argue that Universal Health Care (UHC) is mainly about financing and Primary Health Care (PHC) is about the right care at the right time to ensure health. They maintain the World Health Organisation (WHO) has recently sent the wrong message about the “pillars” of PHC in their relationship to UHC. An understanding of political economy is required in order to come to terms with the bases of PHC and the fundamentals of UHC, that dealing with inequities is not only an economic issue but fundamentally a political issue. Neoliberal decision making can enhance inequities in society. Two chronic health conditions, diabetes and multiple sclerosis are examples of conditions that lead to costly and debilitating consequences for patients but also lead to substantial economic costs in terms of lost workforce participation and lost productivity. These cases demonstrate the socio-political issues involved in the management of care for a number of illnesses. The upsurge of COVID–19 has placed an enormous strain on health and broader social and economic resources and challenged the pretext of UHC as health for all: substantial differences in equity and political commitment have emerged. Sturmberg and Martin argue that the joining of UHC and PHC needs leadership which involves local communities and resourcing. PHC is a changing system based on power relationships involving funders and the health community. In Australia as in several countries out of pocket costs have grown rapidly and have affected access for some groups to PHC and have challenged the pretext of equity in UHC. In the context of PHC and UHC we support the position that health for all goes beyond healthcare for all, to embrace healthy lives promoting wellbeing.

The outbreak of the Covid-19 pandemic obliged us all to handle many dilemmas, some of which we took upon ourselves as philosophers, ethicists, doctors and nurses to discuss around four key ethical notions : responsibility, dignity, fairness and honouring death. The following collection of the symposium acts held online in May 2020 with the Paris Global Center of Columbia University and Columbia Global Centers, attempts to testify to the ongoing pandemic emergency and difficult challenges while evaluating whether the ethical principles in the official recommendations were able to meet the lived reality. Looking at accountability and consistency in regard to the context of exercise, it seemed equally important to examine, through an international exchange, whether the contextuality of Coronavirus across countries and cultures affected the ethical decision making processes. We hope that our discussion can serve as a resource for advanced care planning, helping medical providers and other specialists to consider the shared important aspects of medical ethics in times of great uncertainty.

Competence based education (CBE) has become increasingly popular as of late among health professions training programs. Models of CBE have been developed and implemented by major licensing bodies and professional Colleges (and affiliated education programs), such as the Royal College of Physicians and Surgeons of Canada (RCPSC) and the Association of American Medical Colleges (AAMC). In this month’s issue of theJournal of Evaluation in Clinical Practice , several studies describe an experience with designing and implementing a CBE model [1-6]. On the surface, the desire to ensure that health professions trainees are competent is commendable – just as it is likely few would argue that the care they receive should not be evidence based, I suspect that few (if any) would be comfortable with the clinician prescribing or managing said care being less than competent. However, the notion of a need for a CBE model might suggest that there was some issue with competence in the training of past clinicians that needed remedy, i.e. there is a lack of competence among some clinicians entering their profession that is in part a product of their training.When considering public perception of clinician competence, that of physicians in particular, history is not kind. Over the past two millennia, medicine got it wrong more often than right – humoral theory, bloodletting, miasma and contagion were all highly subscribed among the healthcare community but are now relics of a bygone era. In fact, the poor track record of medicine was the basis for a need for evidence based medicine (EBM). Practitioners of healthcare were often portrayed as ineffective, as providing little more than palliative support while nature took its course for better or worse, or even crueler, as charlatans peddling nostrums [7]. Artists were no kinder to clinicians. For example, Shaw’s The Doctors Dilemma portrays a group of physicians as self-absorbed, greedy, overly confident in their unproven (and presumably, ineffective) pet “cures”, with only the poorest among them as having any sense of humility and patient centred focus in his practice [8]. It seems that only within the last century did clinicians develop a good public reputation, much of which might be more appropriately attributed to improvements in hygiene practices/standards of living at a societal level (e.g. the McKeown Thesis[9]) or likewise to medical science and the discovery of “silver bullet” cures (e.g. antibiotics, insulin, etc.) rather than to a change in how clinicians approached the learning of their craft and care of their patients. However, a historical lack of curative success and a poor reputation does not entail a lack of competence. A clinician working in Europe during the first millennium of the Common Era would have been considered competent provided he (or much rarer, she) mastered humoralism according to the teachings of Galen. Is it possible that future generations will look at the clinicians of today – even those who train under CBE – in the same light as we do clinicians of the past? Should a failure of today’s medicine in the eyes of future generations invalidate the competence of contemporary clinicians? I suppose the impact of the answer to such questions on the issue of competence hinges on how we define (and measure) competence.What then makes a clinician competent? The obvious answer is technical knowledge in the clinician’s given area. By that, I assume that for a clinician to be considered competent, she requires a minimum understanding of the content and technique of her given profession contemporaneous with the period of practice.11A minimum understanding of content and technique is required to be accepted into the profession, but it is not the desirable end. Clinicians are expected to participate in a model of lifelong learning with a goal of mastery over that content and technique. However, knowledge might be considered the minimum requirement. Several frameworks of competence outline additional requirements. For example, the “CanMEDS” framework, issued by the RCPSC, identifies “the abilities physicians require to effectively meet the health care needs of the people they serve”22http://www.royalcollege.ca/rcsite/canmeds/canmeds-framework-e, accessed on June 8, 2020., which includes the roles of the physician as medical expert, communicator, collaborator, leader, health advocate, scholar, and professional. The criteria by which these “roles” were selected (and other “roles” excluded), including the theoretical and/or empirical justification for their inclusion as part of “competence” is not clear to me, nor is it entirely clear if available metrics are sufficient in demonstrating that the roles have in fact been achieved by the trainee or how one operationalizes those roles in practice. Are clinicians who lack ability in any of these “roles” incompetent? Does meeting all of them according to some threshold ensure competence? As health professions are typically self-regulating, it is up to the governing bodies of each profession to decide, which might suggest that competence is a product of the times rather than akin to a “natural kind”33If it is the case that “competence” in medical practice, for example, is in fact a standard set by the profession (which I think most people would agree is the case), then judging the competence of past or future physicians by the current standard might be inappropriate. That raises issues about differing standards of competency for currently practicing physicians who trained at different times. In Canada, we are currently going through a transition whereby our training programs have two cohorts – one that is training under the previous “time based” model and the other under the current “competence by design” model. Is it the case that there is a relatively less (or no) guarantee that those training under the previous model are competent? The answer to that question might impact the extent to which we should have confidence in currently practicing clinicians, or at least relative to the next generation. Regardless, all practicing clinicians are accountable to a standard set by their respective professional Colleges, which likely makes the issue moot once trainees enter independent practice..It would be silly to suggest that clinicians who trained under a pre-CBE model are not competent any more than it is to suggest that clinical decisions prior to the adoption of the EBM movement were not based on evidence. Certainly, we have no shortage of competent clinicians practicing today. Those clinicians were accepted into the profession (and maintain standing) on some assessment of competence. However, institutions may have good reason for implementing CBE beyond simple competence concerns. For example, CBE programs can facilitate the development of an infrastructure of accountability that extends beyond activities of remediation or accelerating advancement to independent practice. That infrastructure can be leveraged to ensure transparency in assessment and advancement, identify individualized training needs, etc. that can be important components of ensuring and achieving equitable access to health professions, particularly for traditionally underrepresented populations.44It is important to note that while CBE might drive the development of such an infrastructure, a CBE training model is not necessary to do so. Certainly, institutions can and should be striving to improve on accountability, equitable access, etc., irrespective of a CBE model.On the other hand, we have no shortage of experience with poor decisions, suboptimal patient outcomes, iatrogenic effects, etc., that often raise concern about clinician ability (or competence). Poor outcomes, or at least those not aligned with the expectations of the public (irrespective of if those expectations are realistic) could be construed by some as a result of incompetence. Likewise, inequitable access (within or between communities) to appropriate expertise might raise concern of a lack of professional competence (i.e. the profession is not meeting the needs of the population inclusively). One way such perceptions by the public can be problematic for healthcare professions is that may erode the powerful position of institutionalized healthcare (and its providers) that exists in many societies. One could argue that EBM had a powerful effect on securing the public’s trust in healthcare by leveraging public perception of science as apolitical, objective, etc. Does CBE play a similar role by highlighting high professional standards only achievable by those “worthy” of the profession, who were rigorously assessed using quantifiable (often presented as “objective”) metrics, irrespective of whether that results in better care for patients? If so, then CBE may constitute a political move to retain or grow power rather than a remedial exercise to ensure no one joins the profession without having the skills necessary to provide appropriate care (by some defined public standard) for those seeking service. In other words, one might argue that CBE is not a response to a concern about competence – it is a response to a potential loss of standing relative to alternative modes of care or other social services. I am not suggesting that is necessarily the case, as I know several health professions educators who are honest in their pursuit to train clinicians who will excel in serving and providing care for the community. That seems to be the rule rather than the exception. However, the goals of the educators may not always tightly align with the goals of the institution, which may also be responsible for securing funding, maintaining status, public accountability, etc.Models of health professions training that focus on assessing and achieving defined competencies rather than hoping that important abilities are acquired over a defined time period (that also relies on the reliability and validity of licensing exams) are admirable. It is difficult to argue that achieving competence should not be the explicit focus of training. Perhaps one of the greatest benefits of CBE is that it puts competence to the forefront, just as EBM did for evidence. However, we must be vigilant to ensure that “competence” stays more than a buzzword or a tool of branding. Terms lacking substance can have a negative effect on patient care – too often the terms “patient centred” and “evidence based”, for example, are invoked as placeholders for quality patient care without any evidence to support that whatever intervention or program those terms are describing has any positive impact beyond rhetorical. We have not entered into an era of clinician competence simply because CBE has been implemented. Rather, what I see as the greatest benefit of CBE is the opportunity for improving and ensuring accountability.ReferencesRich J, Young SF, Donnelly C, et al. Competency-based education calls for programmatic assessment: But what does this look like in practice? Journal of Evaluation in Clinical Practice 2020;26(4):Hamza DM, Ross S, Oandasan I. Process and outcome evaluation of a CBME intervention guided by program theory. Journal of Evaluation in Clinical Practice 2020;26(4):Egan R, Chaplin T, Szulewski A, et al. A case for feedback and monitoring assessment in competency-based medical education. Journal of Evaluation in Clinical Practice 2020;26(4):Katoue MG, Schwinghammer TL. Competency-based education in pharmacy: A review of its development, applications, and challenges. Journal of Evaluation in Clinical Practice 2020;26(4):Crawford L, Cofie N, McEwen L, Dagnone D, Taylor SW. Perceptions and barriers to competency-based education in Canadian postgraduate medical education. Journal of Evaluation in Clinical Practice 2020;26(4):Railer J, Stockley D, Flynn L, Hastings-Truelove A, Hussain A. Using outcome harvesting: Assessing the efficacy of CBME Implementation. Journal of Evaluation in Clinical Practice 2020;26(4):Porter R. The Greatest Benefit to Mankind: A Medical History of Humanity. New York: W.W. Norton & Company; 1997.Shaw, B. The Doctor’s Dilemma: A Tragedy. London: Constable and Co.; 1922.McKeown T. The role of medicine: Dream, mirage or nemesis? Nuffield Trust; 1976. Available at: https://www.nuffieldtrust.org.uk/files/2017-01/1485273106_the-role-of-medicine-web-final.pdf. Accessed on June 8, 2020.

The outbreak of the Covid-19 pandemic obliged us all to handle many dilemmas, some of which we took upon ourselves as philosophers, ethicists, doctors and nurses to discuss around four key ethical notions : responsibility, dignity, fairness and honouring death. The following collection of the symposium acts held online in May 2020 with the Paris Global Center of Columbia University and Columbia Global Centers, attempts to testify to the ongoing pandemic emergency and difficult challenges while evaluating whether the ethical principles in the official recommendations were able to meet the lived reality. Looking at accountability and consistency in regard to the context of exercise, it seemed equally important to examine, through an international exchange, whether the contextuality of Coronavirus across countries and cultures affected the ethical decision making processes. We hope that our discussion can serve as a resource for advanced care planning, helping medical providers and other specialists to consider the shared important aspects of medical ethics in times of great uncertainty.

Our purpose is to assess epidemiological agent-based models– or ABMs - of the SARS-CoV-2 pandemic methodologically. The rapid spread of the outbreak requires fast-paced decision-making regarding mitigation measures. However, the evidence for the efficacy of non-pharmaceutical interventions such as imposed social distancing and school or workplace closures is scarce: few observational studies use quasi-experimental research designs, and conducting randomized controlled trials seems infeasible. Additionally, evidence from the previous coronavirus outbreaks of SARS and MERS lacks external validity, given the significant differences in contagiousness of those pathogens relative to SARS-CoV-2. To address the pressing policy questions that have emerged as a result of COVID-19, epidemiologists have produced numerous models that range from simple compartmental models to highly advanced agent-based models. These models have been criticized for involving simplifications and lacking empirical support for their assumptions. In order to address these voices and methodologically appraise epidemiological ABMs, we consider AceMod (the model of the COVID-19 epidemic in Australia) as an example of the modeling practice. Our case study shows that, although epidemiological ABMs involve simplifications of various sorts, the key characteristics of social interactions and the spread of SARS-CoV-2 are represented sufficiently accurately. This is the case because these modelers treat empirical results as inputs for constructing modeling assumptions and rules that the agents follow; and they use calibration to assert the adequacy to benchmark variables. Given this, we claim that the best epidemiological ABMs are models of actual mechanisms and deliver both mechanistic and difference-making evidence. Furthermore, the efficacy claims are not only internally valid but also adequately describe the effects of interventions in the targets of the models. We also discuss the limitations of ABMs and put forward policy recommendations.

This paper explores the possibility of AI-based narrative therapy for borderline personality disorder, its potential advantages, drawbacks, and limitations. It is argued that identity disturbance in this condition is strongly connected to self-narratives, and the most important features of narrative therapy, which, in a human-to-human form, is one of the more successful treatment options for BDP, could be adapted to AI. While human oversight cannot and should not be eliminated, AI support would hold forth the prospect of overcoming certain hurdles associated with patient-therapist interaction frequently marring the therapeutic process.