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Through 'Aneuploidy' I poeticise bioethicist Chris Kaposy's lived experience of prenatal screening as expressed in a personal essay that recounts how he reacted to the positive result of Down Syndrome testing for his unborn son. The poem aims to capture the shock of the unexpected diagnosis through the morbidities that are evoked and associated with the condition. It also offers a poeticised exposé of 'neoliberal perfectionism' a term Kaposy uses to critique the technologisation of reproduction that can encourage a norm of ableist perfectionism. A prominent motive, he argues, for seeking to terminate foetuses with Down Syndrome is the belief that children born with the condition are limited market actors with diminished economic opportunities. Similarly, the poet asks readers to reconsider the neoliberal, societal dictates that lead to the stigmatisation of people with disabilities and the empathic potential of poetry and its ability to delineate complex, reprogenetic consumption scenarios. [ABSTRACT FROM AUTHOR]

Specialize? Diversify? Do patients care? The authors investigate the demand-side effects of a hospital's portfolio strategy, which entails decisions about the depth and breadth of its service offerings. Positing that both depth (focus) and breadth (related focus) signal expertise, the authors use both archival and experimental evidence to examine these effects. The archival study is based on Florida's State Inpatient Databases for 2006–2015 and spans all major departments in health care delivery. The empirical analysis exploits plausible exogenous variation from other health care markets and reveals that patient choice is positively influenced by a hospital's depth (focus) and breadth (related focus) of expertise in a department. Complementing the archival evidence, the authors also conducted online experiments to examine the signaling effects of hospital portfolio strategy on patient choice behavior. The results provide support for the idea that hospital portfolio strategy influences patients' perceptions of hospital expertise in focal and related areas and, subsequently, their choice behavior. The authors also highlight potential synergistic effects between focus and related focus and heterogeneity in the effects across departments, payer types, and hospital profit status. These findings underscore the need for managers to adopt a targeted approach to portfolio decisions in health care. [ABSTRACT FROM AUTHOR]

Background and Objectives: Cenobamate (CNB) is a new antiseizure medication (ASM) to treat drug-resistant, focal-onset seizures. Data on its use in early therapy lines are not yet available, and clinicians frequently consider CNB to be a later ASM drug choice. We investigated the efficacy and safety of CNB as an early adjunctive treatment in drug-resistant, focal-onset seizures. Methods: The study population were patients with drug-resistant, focal-onset seizures who were initiated with CNB after they did not respond to two or three lifetime ASMs, including all prior and concomitant ASMs. These patients were matched (1:2) by sex, age, and seizure frequency to controls who were initiated with any ASM other than CNB. All participants participated in the Mainz Epilepsy Registry. We evaluated the retention rate after 12 months of CNB and after each new adjunctive ASM in the control group. In addition, seizure freedom and the response rate (reduction of seizure frequency by ≥ 50% from baseline) after 12 months were estimated. Results: We included 231 patients aged 44.4 ± 15.8 years. Of these, 33.3% (n = 77) were on CNB, 19.0% (n = 44) on valproate (VPA), 17.3% (n = 40) on lacosamide (LCS), 16.4% (n = 38) on levetiracetam (LEV), and 13.9% (n = 32) on topiramate (TPM). The highest retention rate after 12 months since the beginning of the early adjunctive therapy was observed on CNB (92.0%), compared with LCS (80.0%), LEV (73.3%), VPA (68.2%), or TPM (62.5%) (p < 0.05). Seizure freedom and response rate were also the best on CNB (19.5% and 71.4%, respectively) compared with other ASMs (8.3% and 52.5%, respectively; p < 0.05). No significant differences in adverse events between CNB and other ASMs were observed. Conclusions: Our study provides evidence that CNB is an effective ASM with a good safety profile in the early therapy lines of drug-resistant, focal-onset seizures. This data should support medical decision making in the management of patients with refractory epilepsy. Clinical Trial ID: NCT05267405. [ABSTRACT FROM AUTHOR]

Computed tomography (CT) is a common modality employed for musculoskeletal imaging. Conventional CT techniques are useful for the assessment of trauma in detection, characterization and surgical planning of complex fractures. CT arthrography can depict internal derangement lesions and impact medical decision making of orthopedic providers. In oncology, CT can have a role in the characterization of bone tumors and may elucidate soft tissue mineralization patterns. Several advances in CT technology have led to a variety of acquisition techniques with distinct clinical applications. These include four-dimensional CT, which allows examination of joints during motion; cone-beam CT, which allows examination during physiological weight-bearing conditions; dual-energy CT, which allows material decomposition useful in musculoskeletal deposition disorders (e.g., gout) and bone marrow edema detection; and photon-counting CT, which provides increased spatial resolution, decreased radiation, and material decomposition compared to standard multi-detector CT systems due to its ability to directly translate X-ray photon energies into electrical signals. Advanced acquisition techniques provide higher spatial resolution scans capable of enhanced bony microarchitecture and bone mineral density assessment. Together, these CT acquisition techniques will continue to play a substantial role in the practices of orthopedics, rheumatology, metabolic bone, oncology, and interventional radiology. [ABSTRACT FROM AUTHOR]

In this research, we introduce a comprehensive epidemiological model that accounts for multiple strains of an infectious disease and two distinct vaccination options. Vaccination stands out as the most effective means to prevent and manage infectious diseases. However, when there are various vaccines available, each with its costs and effectiveness, the decision-making process for individuals becomes paramount. Furthermore, the factor of waning immunity following vaccination also plays a significant role in influencing these choices. To understand how individuals make decisions in the context of multiple strains and waning immunity, we employ a behavioral model, allowing an epidemiological model to be coupled with the dynamics of a decision-making process. Individuals base their choice of vaccination on factors such as the total number of infected individuals and the cost-effectiveness of the vaccine. Our findings indicate that as waning immunity increases, people tend to prioritize vaccines with higher costs and greater efficacy. Moreover, when more contagious strains are present, the equilibrium in vaccine adoption is reached more rapidly. Finally, we delve into the social dilemma inherent in our model by quantifying the social efficiency deficit (SED) under various parameter combinations. [ABSTRACT FROM AUTHOR]

Radiation therapy is a localized, tailored cancer treatment modality. The goal is either durable, long-term tumor control (definitive intent) or alleviation of pain and discomfort (palliative intent). An understanding of the patient's entire clinical picture, as well as the clinical biology of different cancers, is essential for decision making. This article highlights some of the essential elements for clinical decision making in veterinary radiation oncology, with case examples to give general practitioners a better understanding of what types of cases may be appropriate for radiation therapy. [ABSTRACT FROM AUTHOR]

A main research goal in various studies is to use an observational data set and provide a new set of counterfactual guidelines that can yield causal improvements. Dynamic Treatment Regimes (DTRs) are widely studied to formalize this process and enable researchers to find guidelines that are both personalized and dynamic. However, available methods in finding optimal DTRs often rely on assumptions that are violated in real-world applications (e.g., medical decision making or public policy), especially when (a) the existence of unobserved confounders cannot be ignored, and (b) the unobserved confounders are time varying (e.g., affected by previous actions). When such assumptions are violated, one often faces ambiguity regarding the underlying causal model that is needed to be assumed to obtain an optimal DTR. This ambiguity is inevitable because the dynamics of unobserved confounders and their causal impact on the observed part of the data cannot be understood from the observed data. Motivated by a case study of finding superior treatment regimes for patients who underwent transplantation in our partner hospital (Mayo Clinic) and faced a medical condition known as new-onset diabetes after transplantation, we extend DTRs to a new class termed Ambiguous Dynamic Treatment Regimes (ADTRs), in which the causal impact of treatment regimes is evaluated based on a "cloud" of potential causal models. We then connect ADTRs to Ambiguous Partially Observable Markov Decision Processes (APOMDPs) proposed by Saghafian (2018), and consider unobserved confounders as latent variables but with ambiguous dynamics and causal effects on observed variables. Using this connection, we develop two reinforcement learning methods termed Direct Augmented V-Learning (DAV-Learning) and Safe Augmented V-Learning (SAV-Learning), which enable using the observed data to effectively learn an optimal treatment regime. We establish theoretical results for these learning methods, including (weak) consistency and asymptotic normality. We further evaluate the performance of these learning methods both in our case study (using clinical data) and in simulation experiments (using synthetic data). We find promising results for our proposed approaches, showing that they perform well even compared with an imaginary oracle who knows both the true causal model (of the data-generating process) and the optimal regime under that model. Finally, we highlight that our approach enables a two-way personalization; obtained treatment regimes can be personalized based on both patients' characteristics and physicians' preferences. This paper was accepted by David Simchi-Levi, data science. Supplemental Material: The data files and online appendix are available at https://doi.org/10.1287/mnsc.2022.00883. [ABSTRACT FROM AUTHOR]

The article considers the pathways pilot model and technology appraisal process proposed by the National Institute for Health and Care Excellence (NICE) of Great Britain as a pursuit for quality decision-making in difficult circumstances. It describes the experience of the Peninsula Technology Assessment Group in developing the Exeter Oncology Model in advanced renal cell carcinoma. It shares ideas on health technology assessment and incorporation of real-world evidence into the economic model.

People are inundated with popular press reports about medical research concerning what is healthy, get advice from doctors, and hear personal anecdotes. How do people integrate conflicting anecdotal and statistical information when making medical decisions? In four experiments (N = 4126), we tested how people use conflicting information to judge the efficacy of artificial and real medical treatments. Participants read an anecdote from someone in a clinical trial, or who had undergone a medical treatment previously, for whom the medical treatment was ineffective. We found that reading anecdotes for either artificial or real medical treatments shifted participants' beliefs about the efficacy of a medical treatment. We observed this result even when the anecdote was uninformative, was paired with an icon array, or when participants were provided with thorough medical decision aids about reproductive health procedures. Our findings highlight the pervasive effect of anecdotes on medical decision making. [ABSTRACT FROM AUTHOR]

Adolescent Medical Decision Making (aMDM) is frequently discussed but presents a significant challenge in practice, especially in cases of adolescents with life threatening or life limiting illnesses. In this paper, we present a case that explores the importance of aMDM, the difficulties for providers when engaging adolescents in these discussions, and how certain skills may be incorporated into pediatric practice. Literature suggests that patients of this age group, while being legally without capacity, have meaningful insights into their care. However, unless physicians feel comfortable and competent engaging adolescents in a manner that honors their developmentally appropriate understanding of their illness, these insights can be lost. [ABSTRACT FROM AUTHOR]

The drivers for medical students’ decision making when considering which Student Selected Component (SSC) to undertake is poorly understood. Furthermore, it is unclear why students undertake a specific SSC allowing them to have an extended placement in GP in their final year. It is known that high quality GP placements encourage students to subsequently choose GP as their career, therefore if the decision-making process of students in this area can be better understood, then this may help inform medical school actions to encourage a greater uptake of these extended placements.Semi-structured interviews were conducted with final year medical students at a Scottish University. Students were selected to provide a mixture of those who had and had not chosen to undertake the extended placement. The data was transcribed and analysed using thematic analysis to generate themes which represented the data.This showed that career intention was a major factor driving SSC choice. Additionally, students sought peer feedback and tended to avoid specific SSCs if they felt a lack of internal motivation. Considering the choice for the extended placement, students tended, again, to choose based on career intentions, and they also based their decision on previous experiences of GP.Career intention and prior experience are key factors in student choice of SSC and whether to undertake an extended GP. In order to address the national shortage of GPs medical schools need to consider how they might influence these drivers. [ABSTRACT FROM AUTHOR]

Objective: Pulmonary embolism (PE) is usually non-specific in terms of symptoms and signs and needs to be confirmed by an objective test. Pulmonary computed tomography angiography (PCTA) has been widely used for diagnosis in recent years. Our aim was to evaluate the potential of the YEARS algorithm to reduce the need for PCTA compared with the classical algorithm. Materials and Methods: This prospective observational study. Between 15.03.2018 and 15.09.2019, patients admitted to the emergency department with suspected PE who underwent PCTA according to the classical algorithm (Wells) were included in the study. YEARS criteria were reviewed according to the patients' files and general laboratory results without knowing the results of PCTA. The need for PCTA was investigated according to classical clinical decision-making rules and YEARS algorithms. Results: The study included 300 patients. According to YEARS, 69% of patients required PCTA, whereas 31% required the YEARS PE exclusion group. According to YEARS, PE was detected in 16.4% of patients with an indication for PCTA, whereas only 2.2% of patients in the PCTA exclusion group had PE. In the patient cohort that included the "probable PE" group according to the Wells, the sensitivity according to the YEARS was 94.4%. Conclusion: In this study, the YEARS protocol used in addition to the classical algorithm resulted in a 31% reduction in the need for PCTA. However, we also showed that the YEARS algorithm may be insufficient for the diagnosis of low rate, positive PE. [ABSTRACT FROM AUTHOR]

Background: A central goal of modern evidence-based medicine is the development of simple and easy to use tools that help clinicians integrate quantitative information into medical decision-making. The Bayesian Pre-test/Post-test Probability (BPP) framework is arguably the most well known of such tools and provides a formal approach to quantify diagnostic uncertainty given the result of a medical test or the presence of a clinical sign. Yet, clinical decision-making goes beyond quantifying diagnostic uncertainty and requires that that uncertainty be balanced against the various costs and benefits associated with each possible decision. Despite increasing attention in recent years, simple and flexible approaches to quantitative clinical decision-making have remained elusive. Methods: We extend the BPP framework using concepts of Bayesian Decision Theory. By integrating cost, we can expand the BPP framework to allow for clinical decision-making. Results: We develop a simple quantitative framework for binary clinical decisions (e.g., action/inaction, treat/no-treat, test/no-test). Let p be the pre-test or post-test probability that a patient has disease. We show that r ∗ = (1 - p) / p represents a critical value called a decision boundary. In terms of the relative cost of under- to over-acting, r ∗ represents the critical value at which action and inaction are equally optimal. We demonstrate how this decision boundary can be used at the bedside through case studies and as a research tool through a reanalysis of a recent study which found widespread misestimation of pre-test and post-test probabilities among clinicians. Conclusions: Our approach is so simple that it should be thought of as a core, yet previously overlooked, part of the BPP framework. Unlike prior approaches to quantitative clinical decision-making, our approach requires little more than a hand-held calculator, is applicable in almost any setting where the BPP framework can be used, and excels in situations where the costs and benefits associated with a particular decision are patient-specific and difficult to quantify. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

The factors influencing caregivers' understanding of pediatric respiratory diseases, such as bronchiolitis, can guide patient care and the acceptability of treatment methods within the healthcare system. This study aims to identify illness perceptions and perform a needs assessment among caregivers of children diagnosed with respiratory diseases. This is a prospective, cross-sectional, questionnaire-driven study of a representative sample of caregivers whose children had an acute respiratory illness. The telephone-administered questionnaire was comprised of (1) demographic items; (2) illness perception questionnaire-revised (IPQ-R); and (3) items about personal barriers, the latter 2 of which employed a 5-point Likert response. Cronbach's alpha (α) was used to measure the internal consistency reliability for each item within the IPQ-R. The Pearson 2-tailed correlation coefficient was used to correlate questionnaire items. We included 75 caregivers whose children have been diagnosed with bronchiolitis (51%), reactive airway disease (RAD) (35%), asthma (33%), and wheezing (44%). We found no significance between the child's diagnosis and the site of recruitment. The most important components of the illness perception were illness coherence (α =0.849), psychological attributions (α =0.903), and barriers to diagnosis (α =0.633). Understanding caregivers' perceptions of respiratory diseases will lead to better treatment acceptance. We must clarify the terms used to define bronchiolitis from viral-induced wheezing, RAD, and the first asthma episode in older infants. Identifying caregivers' gaps in knowledge will help establish a cohesive approach to personalized treatment of respiratory diseases in children and their diagnosis. [ABSTRACT FROM AUTHOR]

AbstractPurposeMaterials and MethodsResultsConclusionWe aimed to develop a tool that would allow assessment of ethics competency and moral distress during the Internal Medicine Clerkship and to introduce curricular changes that could empower students to better address ethical dilemmas and challenges encountered during the clerkship.A structured ethics assignment was introduced where students could reflect on impactful stressful scenarios and address questions related to emotional responses, identified ethical issues, management themes, and professional obligations. A 4-tiered grading rubric and individual narrative feedback was provided for each assignment, and small-group debriefing sessions were introduced for reflective thought and future planning. De-identified assignments were analyzed and classified into subgroups according to 5 main ethical issue subgroups and 10 specific management themes. Assignments were also analyzed for the presence of moral distress.357 students completed the reflective ethics activities. The most commonly identified ethical issues were related to Shared Medical Decision Making (>40%), Primary of Patient Welfare challenges, (>20%), and Social/Organizational dilemmas. Management themes often pertained to Patient Wishes/Legal Obligations, Professional Behaviors, and Limited Resources. 87% of assignments demonstrated moral distress.Medical school is a stressful time and challenges are augmented during clinical years. Our reflective activity demonstrated significant exposures to ethical dilemmas, reviewed earlier principles of ethics training, and provided a safe forum in which to discuss these important aspects of healthcare. We captured powerful images of challenging situations eliciting moral distress, and students greatly appreciated the activity. We encourage future investigations that support student well-being and enable smooth transitions into residency training. [ABSTRACT FROM AUTHOR]

Previous observational studies have indicated that social influences, such as arising from herding-like behaviour, can contribute to medical errors. In this study, we experimentally examined whether general practitioners (GPs) would follow incorrect prescription recommendations from fellow GP or specialists. To investigate this, we conducted an online survey with 475 GPs practicing in England that included two case vignettes. Case vignette 1 focused on sleeping tablets, and case vignette 2 was centred around antibiotics. The vignettes were presented in random order, and within each vignette, study participants were assigned to one of three experimental conditions: control condition (lacking peer recommendation), fellow GP condition (including a recommendation from a fellow GP not aligned with best practice clinical guidelines), or specialist condition (including a recommendation from a specialist not aligned with best practice clinical guidelines). The primary outcome measure was the proportion of GPs who prescribed medication that deviated from best practice clinical guidelines. We found that, in both case vignettes, the percentage of respondents prescribing such medication was highest in those assigned to the specialist condition, followed by those assigned to the control condition. It was lowest in those assigned to the fellow GP condition (case vignette 1: 73.8% vs. 55.6% vs. 36.6% and case vignette 2: 24.0% vs. 12.4% vs. 10.1%). In the case of vignette 1, the difference between the fellow GP condition and the control condition is statistically significant, suggesting that GPs are less likely to prescribe sleeping tablets when recommended by a fellow GP. This implies that GPs are more inclined to prescribe non-guideline-recommended medication when advised by specialists. This study is the first to experimentally demonstrate that physician herding behaviour can result in prescription errors. Future research could extend this inquiry to diverse contexts, including diagnosis. [ABSTRACT FROM AUTHOR]

Background: Stroke is one of the most dangerous and life-threatening disease as it cancause lasting brain damage, long-term disability, or even death. The early detectionof warning signs of a stroke can help save the life of a patient. In this paper, we adoptedmachine learning approaches to predict strokes and identify the three most important factors that are associated with strokes. Methods: This study used an open-access strokeprediction dataset. We developed 11 machine learning models and compare the results tothose found in prior studies. Results: The accuracy, recall and area under the curve for therandom forest model in our study is significantly higher than those of other studies. Machinelearning models, particularly the random forest algorithm, can accurately predict the riskof stroke and support medical decision making. Conclusion: Our findings can be appliedtodesign clinical prediction systems at the point of care. [ABSTRACT FROM AUTHOR]

Vertebral compression fractures (VCFs) are typically treated nonoperatively but can be treated with either kyphoplasty or vertebroplasty when indicated. The decision to treat patients with/without surgical intervention is dependent on the severity of deformity and patient risk profile. The aims of this study were to: 1) compare baseline patient demographics, 2) identify risk factors of patients undergoing operative vs. nonoperative management, and 3) identify patient-specific risk factors associated with postoperative readmissions. This retrospective database study used patient information from January 1st, 2010, to October 31st, 2021. Cohorts were identified by patients diagnosed with VCFs through International Classification of Disease, Ninth Revision (ICD-9), ICD-10 codes, identifying those undergoing kyphoplasty/vertebroplasty via Current Procedural Terminology codes. The 2 research domains utilized in this investigation were baseline demographic profiles of patients who underwent kyphoplasty or vertebroplasty for treatment of VCFs, and those who underwent nonoperative management served as the control cohort. Of the 703,499 patients diagnosed with VCFs, 76,126 patients (10.8%) underwent kyphoplasty or vertebroplasty within 90 days of diagnosis of a VCF. Univariate analysis demonstrated female sex was associated with increased risk of undergoing surgical management for VCF (P < 0.0001). Several comorbidities were significantly associated with increased rates of readmission including hypertension, tobacco use, coronary artery disease, and chronic obstructive pulmonary disease (P < 0.0001 for all). This study highlights specific comorbidities that are significantly associated with higher rates of kyphoplasty or vertebroplasty for the treatment of thoracolumbar wedge compression fractures and increased risk for 90-day postoperative hospital readmission. [ABSTRACT FROM AUTHOR]

The article deals with the requirements for a Medical Care Center (MVZ) and the role of the medical director. It emphasizes that an MVZ must have a medical director who manages the operational processes and ensures that medical decisions are made independently. A judgment of the Social Court of Munich deals with the rejection of an application for correction of the fee settlement of an MVZ. In the legal dispute between a dentist and an MVZ, it was determined that the MVZ did not have a dental management and therefore the settlements were not lawful. The correction of the settlements does not constitute a pre-emptive revocation of authorization. [Extracted from the article]

In recent years, concerns about the financial burdens of health care and growing recognition of the relevance of cost to decision making and patient experience have increasingly focused attention on financial 'transparency' and disclosure of costs to patients. In some jurisdictions, there have been calls not only for timely disclosure of costs information, but also for 'informed financial consent'. However, simply putting the 'financial' into 'informed consent' and invoking an informed consent standard for cost information encounters several ethical, legal, and practical difficulties. This article will examine the viability and desirability of 'informed financial consent', and whether it is possible to derive ideas from traditional informed consent that may improve decision making and the patient experience. We argue that, while there are important legal, ethical, and practical challenges to consider, some of the principles of informed consent to treatment can usefully guide financial communication. We also argue that, while medical practitioners (and their delegates) have an important role to play in bridging the gap between disclosure and enabling informed (financial) decision making, this must be part of a multi-faceted approach to financial communication that acknowledges the influence of non-clinical providers and other structural forces on discharging such obligations. [ABSTRACT FROM AUTHOR]

As the use of Artificial Intelligence (AI) technologies in healthcare is expanding, patients in the European Union (EU) are increasingly subjected to automated medical decision-making. This development poses challenges to the protection of patients' rights. A specific patients' right not to be subject to automated medical decision-making is not considered part of the traditional portfolio of patients' rights. The EU AI Act also does not contain such a right. The General Data Protection Regulation (GDPR) does, however, provide for the right 'not to be subject to a decision based solely on automated processing' in Article 22. At the same time, this provision has been severely critiqued in legal scholarship because of its lack of practical effectiveness. However, in December 2023, the Court of Justice of the EU first provided an interpretation of this right in C-634/21 (SCHUFA)—although in the context of credit scoring. Against this background, this article provides a critical analysis of the application of Article 22 GDPR to the medical context. The objective is to evaluate whether Article 22 GDPR may provide patients with the right to refuse automated medical decision-making. It proposes a health-conformant reading to strengthen patients' rights in the EU. [ABSTRACT FROM AUTHOR]

BACKGROUND: We aimed to evaluate the utility of point-of-care ultrasound (POCUS) in the assessment of hand infections that present to the emergency department (ED) and its impact on medical decision making and patient management. METHODS: We conducted a retrospective review of patients who presented to two urban academic EDs with clinical presentations concerning for skin and soft tissue infections (SSTI) of the hand between December 2015 and December 2021. Two trained POCUS fellowship physicians reviewed an ED POCUS database for POCUS examinations of the hand. We then reviewed patients’ electronic health records (EHR) for demographic characteristics, history, physical examination findings, ED course, additional imaging studies, consultations, impact of POCUS on patient care and final disposition. RESULTS: We included a total of 50 cases (28 male, 22 female) in the final analysis. The most common presenting symptoms and exam findings were pain (100%), swelling (90%), and erythema (74%). The most common sonographic findings were edema (76%), soft tissue swelling (78%), and fluid surrounding the tendon (57%). POCUS was used in medical decision making 68% of the time (n=34), with the use of POCUS leading to changes in management 38% of the time (n=19). POCUS use led to early antibiotic use (11/19), early consultation (10/19), and led to the performance of a required procedure (8/19). The POCUS diagnosis was consistent with the discharge diagnosis of flexor tenosynovitis 8/12 times, abscess 12/16 times, and cellulitis 14/20 times. CONCLUSION: POCUS is beneficial for evaluating of hand infections that present to the ED and can be used as an important part of medical decision making to expedite patient care. [ABSTRACT FROM AUTHOR]

Background: A risk-stratified breast screening program could offer low-risk women less screening than is currently offered by the National Health Service. The acceptability of this approach may be enhanced if it corresponds to UK women's screening preferences and values. Objectives: To elicit and quantify preferences for low-risk screening options. Methods: Women aged 40 to 70 y with no history of breast cancer took part in an online discrete choice experiment. We generated 32 hypothetical low-risk screening programs defined by 5 attributes (start age, end age, screening interval, risk of dying from breast cancer, and risk of overdiagnosis), the levels of which were systematically varied between the programs. Respondents were presented with 8 choice sets and asked to choose between 2 screening alternatives or no screening. Preference data were analyzed using conditional logit regression models. The relative importance of attributes and the mean predicted probability of choosing each program were estimated. Results: Participants (N = 502) preferred all screening programs over no screening. An older starting age of screening, younger end age of screening, longer intervals between screening, and increased risk of dying had a negative impact on support for screening programs (P < 0.01). Although the risk of overdiagnosis was of low relative importance, a decreased risk of this harm had a small positive impact on screening choices. The mean predicted probabilities that risk-adapted screening programs would be supported relative to current guidelines were low (range, 0.18 to 0.52). Conclusions: A deintensified screening pathway for women at low risk of breast cancer, especially one that recommends a later screening start age, would run counter to women's breast screening preferences. Further research is needed to enhance the acceptability of offering less screening to those at low risk of breast cancer. Highlights: Risk-based breast screening may involve the deintensification of screening for women at low risk of breast cancer. Low-risk screening pathways run counter to women's screening preferences and values. Longer screening intervals may be preferable to a later start age. Work is needed to enhance the acceptability of a low-risk screening pathway. [ABSTRACT FROM AUTHOR]

Background. In Italy, the law n. 219/2017 regarding informed consent states that "Communication time between doctor and patient constitutes treatment time". Legal guardian is designated as a proxy to consent on the child's behalf. The issue of proxy informed consent should be approached with a model for parent-child decision-making that is participatory, collaborative, respects and supports the autonomy of child by recognizing their evolving capacities. We aim to assess the informed consent related to healthcare decisions for medically fragile child, using the MacArthur Competence Assessment Tool for Treatment (MacCAT-T). Materials and Methods. An observational study has been conducted at a Child Neuropsychiatry Service, administering a semi-structured interview with customized questionnaire to examine their capacities in four areas of the MacCAT-T. Results were evaluated with the Pearson correlation coefficient for the cognitive and adaptive levels of the Wechsler-Intelligence-Scale-for-Children (WISC-IV) and the Vineland-Adaptive-Behavior-Scales-II (VABS-II). Conclusions. The MacCAT-T domains Understanding, Appreciation, Reasoning, Expressing a Choice were correlated with the cognitive and adaptive levels of the WISC-IV and the VABS-II. Understanding, Appreciation and Expressing a choice have positive correlation with the Communication and Socialization scores of VABS-II; Reasoning has positive correlation with the Working-Memory-Index scores of the WISC-IV. The study enabled to assess the informed consent processes in vulnerable children and although demonstrating how they participate in their care process in a mostly unconscious way, making the frail children more involved in their own care process was possible. Future studies should assess the impact of incorporating MacCAT-T into standard informed consent in other settings. [ABSTRACT FROM AUTHOR]

Abstract People are inundated with popular press reports about medical research concerning what is healthy, get advice from doctors, and hear personal anecdotes. How do people integrate conflicting anecdotal and statistical information when making medical decisions? In four experiments (N = 4126), we tested how people use conflicting information to judge the efficacy of artificial and real medical treatments. Participants read an anecdote from someone in a clinical trial, or who had undergone a medical treatment previously, for whom the medical treatment was ineffective. We found that reading anecdotes for either artificial or real medical treatments shifted participants’ beliefs about the efficacy of a medical treatment. We observed this result even when the anecdote was uninformative, was paired with an icon array, or when participants were provided with thorough medical decision aids about reproductive health procedures. Our findings highlight the pervasive effect of anecdotes on medical decision making.

Abstract 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.

Abstract 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.

Introduction: The literature confirms the challenges of learning clinical reasoning experienced by junior doctors during their transition into the workplace. This study was conducted to explore junior doctors' experiences of clinical reasoning development and recognise the necessary adjustments required to improve the development of clinical reasoning skills. Methods: A hermeneutic phenomenological study was conducted using multiple methods of data collection, including semi-structured and narrative interviews (n=18) and post-consultation discussions (n=48). All interviews and post-consultation discussions were analysed to generate themes and identify patterns and associations to explain the dataset. Results: During the transition, junior doctors’ approach to clinical reasoning changed from a ‘disease-oriented’ to a ‘practice-oriented’ approach, giving rise to the ‘Practice-oriented clinical skills development framework’ helpful in developing clinical reasoning skills. The freedom to reason within a supportive work environment, the trainees’ emotional commitment to patient care, and their early integration into the healthcare team were identified as particularly supportive. The service-oriented nature of the internship, the interrupted supervisory relationships, and early exposure to acute care settings posed challenges for learning clinical reasoning. These findings highlighted the clinical teachers' role, possible teaching strategies, and the specific changes required at the system level to develop clinical reasoning skills among junior doctors. Conclusion: The ‘Practice-oriented clinical skills development framework’ is a valuable reference point for clinical teachers to facilitate the development of clinical reasoning skills among junior doctors. In addition, this research has provided insights into the responsibilities of clinical teachers, teaching strategies, and the system-related changes that may be necessary to facilitate this process.

Background: Systematic biases in group decision making (i.e., group biases) may result in suboptimal decisions and potentially harm patients. It is not well known how impaired group decision making in patient care may affect medical training. This study aimed to explore medical residents' experiences and perspectives regarding impaired group decision making and the role of group biases in medical decision making. Methods: This study used a qualitative approach with thematic analysis underpinned by a social constructionist epistemology. Semi-structured interviews of medical residents were conducted at a single internal medicine residency program. Residents were initially asked about their experiences with suboptimal medical decision making as a group or team. Then, questions were targeted to several group biases (groupthink, social loafing, escalation of commitment). Interviews were transcribed and transferred to a qualitative data analysis software. Thematic analysis was conducted to generate major themes within the dataset. Results: Sixteen interviews with residents revealed five major themes: (1) hierarchical influence on group decision making; (2) group decision making under pressure; (3) post-call challenges in decision making; (4) interactions between teamwork and decision making; and (5) personal and cultural influences in group decision making. Subthemes were also identified for each major theme. Most residents were able to recognize groupthink in their past experiences working with medical teams. Residents perceived social loafing or escalation of commitment as less relevant for medical team decision making. Conclusions: Our findings provide unique insights into the complexities of group decision making processes in teaching hospitals. Team hierarchy significantly influenced residents' experiences with group decision making—most group decisions were attributed to consultants or senior team members, while lower ranking team members contributed less and perceived fewer opportunities to engage in group decisions. Other factors such as time constraints on decision making, perceived pressures from other staff members, and challenges associated with post-call days were identified as important barriers to optimal group decision making in patient care. Future studies may build upon these findings to enhance our understanding of medical team decision making and develop strategies to improve group decisions, ultimately leading to higher quality patient care and training. [ABSTRACT FROM AUTHOR]

Abstract“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. [ABSTRACT FROM AUTHOR]

Type 1 endometrial adenocarcinoma or endometrioid adenocarcinoma had developed from a precursor lesion known as atypical endometrial hyperplasia (AEH). This study aimed to evaluate the rates and risk factors of concurrent endometrial carcinoma in patients with preoperative diagnosis of AEH and assessed the role of intraoperative frozen section examination among these patients. Sixty-six patients undergone hysterectomy after the preoperative diagnosis of AEH via diagnostic curettage or hysteroscopy biopsy, were included in this retrospective cohort study. The major study outcomes were the rates and risk factors of co-existent endometrial cancer and the frozen section efficacy in detecting concurrent invasive disease. 31.81% AEH patients had endometrial cancer diagnosis in hysterectomy specimens. Among these endometrial cancer patients, 18 were of Stage IA, 1 of Stage IB, and 2 of Stage II. Stage III or IV was not detected in any of the patients. Patients preoperatively diagnosed as AEH via hysteroscopy had less probability of co-existent endometrial carcinoma than those diagnosed by endometrial curettage (17.24% vs. 43.24%) (p < 0.05). BMI (Body Mass Index) >28 kg/m2, post-menopausal status, and endometrial thickness were the determinant factors in diagnosing endometrial carcinoma through final histopathology of AEH patients (p < 0.05). Regarding presence or absence of concomitant endometrial carcinoma, the frozen section diagnoses were consistent with the final histopathology in 47.06% patients. Co-existent endometrial cancer with AEH was prevalent and possessed good prognostic features. The predictive factors of harboring concomitant endometrial cancer included older age, overweight, and endometrial thickness. Intraoperative frozen section analysis of AEH might assist in the clinical decision-making during surgery. [ABSTRACT FROM AUTHOR]

In the realm of medical diagnosis, intuitionistic fuzzy data serves as a valuable tool for representing information that is uncertain and imprecise. Nevertheless, decision-making based on this kind of knowledge can be quite challenging due to the inherent vagueness of the data. To address this issue, we employ power aggregation operators, which prove effective in combining several sources of data, such as expert thoughts and patient information. This allows for a more correct diagnosis; a particularly crucial aspect of medical practice where precise and timely diagnoses can significantly impact medication policy and patient results. In our research, we introduce a novel methodology to the three-way decision idea. Initially, we revamp the three-way decision model using rough set theory and incorporate interval-valued classes to handle intuitionistic fuzzy data. Secondly, we explore the use of intuitionistic fuzzy power weighted and intuitionistic fuzzy power weighted geometric aggregation operators to consolidate attribute values within the data system. Furthermore, we present a case study in the medical field to exhibit the validity and efficiency of our offered technique. This innovative method enables us to classify participants into three distinct zones based on their symptoms. The manuscript concludes with a summary of key points provided by the authors. [ABSTRACT FROM AUTHOR]

Pandemic-related uncertainties and intolerance of uncertainty (IU) could negatively affect physicians' well-being and functioning, being associated with experiences of distress and problematic decision-making processes. To summarize the available quantitative and qualitative evidence of physicians' IU and decisional uncertainty during COVID-19 and problems associated with it, a systematic search was conducted to identify all relevant articles describing physician uncertainty with regard to medical decision making and well-being in COVID-19 pandemic conditions. Medical, psychological, and preprint databases were searched. Ten articles met all eligibility criteria, with eight describing quantitative and two describing qualitative research outcomes, assessed primarily in European regions and via online surveys. Associations between IU and symptoms of poor mental health and mental health risk factors were widespread, but inconsistencies emerged. Qualitative studies emphasized decisional uncertainty as a stressor for physicians, and quantitative studies suggest it may have fostered more unproven treatment choices. While the prevalence and impact of physician uncertainty under COVID-19 conditions requires further investigation, sighting available literature indicates that IU coincided with experiences of poor mental health and, at least towards the beginning of the pandemic, with willingness to endorse unproven treatments. Efforts to reduce uncertainty-related problems for physicians seem warranted, for example, through normalizing experiences of uncertainty or reducing avoidable uncertainty through maintaining open and timely communication channels. [ABSTRACT FROM AUTHOR]

Utilizing massive clinical data in the field of football players injuries for assisted medical decision support is the core technology and inevitable development trend of smart healthcare. However, due to the characteristics of medical data such as feature redundancy and imbalance of data sample categories, it has been difficult for traditional data mining algorithms to be directly applied in medical data research. In this paper, we propose a data-driven football players injury prediction method based on the experimental study of football players injuries occurring during the learning process of youth professional soccer training, which is based on the machine learning method of decision tree classifier. Through a semester of data statistics and experiments, the model has a high accuracy of injury prediction, which can provide early warning of youth football players injuries and support medical decision-making. [ABSTRACT FROM AUTHOR]

Practice-based learning and improvement (PBLI) is an ACGME (Accreditation Council for Graduate Medical Education) core competency. Learning and reflecting on patients through follow-up is one method to help achieve this competency. We therefore designed a study evaluating a structured patient follow-up intervention for senior internal medicine (IM) residents at the University of Colorado Hospital (UCH). Trainees completed structured reflections after performing chart review of prior patients during protected educational time. Two-month follow-up surveys evaluated the exercise's potential influence on clinical and reflective practices. Forty out of 108 (37 %) eligible residents participated in the exercise. Despite 62.5 % of participants lacking specific questions about patient outcomes before chart review, 81.2 % found the exercise at least moderately helpful. 48.4 % of participants believed that the review would change their practice, and 60.9 % felt it reinforced their existing clinical practices. In our qualitative data, residents learned lessons related to challenging clinical decisions, improving transitions of care, the significance of early goals of care conversations, and diagnostic errors/strategies. Our results indicate that IM residents found a structured patient follow-up intervention educational, even when they lacked specific patient outcomes questions. Our results underscore the importance of structured self-reflection in the continuous learning process of trainees and suggest the benefit of dedicated educational time for this process. [ABSTRACT FROM AUTHOR]

Coercion perceived by psychiatric inpatients is not exclusively determined by formal measures such as involuntary admissions, seclusion or restraint, but is also associated with patients' characteristics and professionals' attitude. This study examined how inpatients' involvement in the decision making process, the respect of their decision making preference, and their feeling of having been treated fairly mediate the relationship between involuntary hospitalisation and perceived coercion both at admission and during hospital stay. Mediation analysis were performed in order to study the relationship between involuntary hospitalisation and perceived coercion among 230 patients, voluntarily and involuntarily admitted in six psychiatric hospitals. 32.2% of the participants were involuntarily hospitalised. Taken individually, stronger participants' involvement in decision making process, better respect for their decision making preference and higher level of perceived fairness partially mediated the relationship between involuntary hospitalisation and perceived coercion by reducing the level of the latter both at admission and during the hospitalisation. In multiple mediator models, only involvement and respect played an important role at admission. During the hospitalisation, perceived fairness was the most relevant mediator, followed by involvement in decision making. During psychiatric hospitalisation patients' involvement in decision making, respect of their decision making preference and perceived fairness determined the relationship between involuntary hospitalisation and perceived coercion, but not in the same way at admission and during the stay. Involving patients in decision making and treating them fairly may be more relevant than taking account of their decision making preference in order to reduce perceived coercion. [ABSTRACT FROM AUTHOR]

Background/Aim: Breast cancer remains the most prevalent type of cancer among women worldwide, and it remains the primary cause of cancer-related deaths in this demographic. Neuroendocrine breast cancer (NBC), an uncommon subtype comprising less than 1% of cases, typically occurs in older women and displays as a slow-growing, low-grade condition. NBC exhibits distinct histological patterns and immunohistochemical markers. Given the limited data on NBC, assays are required that will provide information on molecular profiling and assist in clinical decision making. The aim of the study was to investigate whether a modern Multigene Assay (MGA) could assist on treatment planning of NBC patients. Case Report: A cohort of four patients was analyzed using a MGA. The presented cases featured young, pre-menopausal women with clear NBC, lacking family history. All were lymph nodenegative, with robust expression of neuroendocrine markers. Despite high hormone receptor expression, all tumors were poorly differentiated with elevated Ki67 levels. Oncotype DX analysis indicated a need for chemotherapy in three cases and not in one. This underscores the heterogeneity within NBC, emphasizing the importance of personalized treatment decisions. Conclusion: While NBC is rare and lacks extensive studies, the use of multigene assays like Oncotype DX may play a pivotal role in treatment planning, especially in cases with varying histological parameters. [ABSTRACT FROM AUTHOR]

The principles of law play a crucial role in shaping the legal system of a society and ensuring the rights and freedoms of its citizens. This article explores the importance of general principles of law in establishing the rule of law and guaranteeing human rights, with a focus on the principles of medical law. The article highlights the key principles of medical law, including autonomy, beneficence, non-maleficence, justice, and confidentiality, and examines their role in providing ethical and legal guidelines for healthcare professionals. Additionally, the article discusses the influence of international human rights law on the development of sectoral principles of medical law, with a particular emphasis on the 2005 UNESCO Declaration on Human Rights and Bioethics. The article also addresses the issue of responsibility in medical practice, including the legal liabilities of healthcare professionals and the importance of obtaining informed consent from patients. Through an analysis of international legal instruments, court decisions, and domestic legislation, the article aims to provide a comprehensive understanding of the principles of medical law and their significance in protecting the rights and well-being of patients. Mainly, in the article author explores the key characteristics of autonomy, informed consent, confidentiality, beneficence, non-maleficence, justice, and privacy within the context of medical law and human rights. Autonomy, the right to make decisions about one's own body and medical treatment, is essential in medical ethics and is protected by human rights laws. Informed consent, the process of providing all necessary information to patients so they can make decisions about their medical care, is a fundamental aspect of patient autonomy. Confidentiality, the duty to protect patients' personal information, is crucial for maintaining trust between patients and healthcare providers. Beneficence, the duty to act in the best interest of the patient, and non-maleficence, the duty to do no harm, are two key principles that guide ethical medical practice. Justice, the fair and equal distribution of healthcare resources, is also essential in ensuring that all patients receive the care they need. Privacy, the right to control one's personal information, is another important aspect of medical ethics and human rights. By understanding and upholding these key characteristics, healthcare providers can ensure that patients' rights are respected and protected in the medical setting. [ABSTRACT FROM AUTHOR]

Large language models (LLMs) have demonstrated remarkable capabilities in various natural language processing tasks, including question answering, text generation, and multimodal understanding. However, their performance in specialized domains such as healthcare and their propensity for generating hallucinated (false) information remains an area of active investigation. This research paper explores the capabilities and limitations of Mistral's LLM, mistral-large-2402, in tackling medical challenge problems and assessing its tendency to hallucinate. The study is motivated by the potential of LLMs to augment medical decision-making processes and the need to evaluate their reliability in critical domains like healthcare. We investigate mistrallarge-2402's performance on a curated dataset of medical challenge problems, spanning diagnosis, treatment recommendation, and medical condition analysis tasks. Additionally, we examine the model's propensity for hallucinating by analyzing its responses for factual inconsistencies and unsubstantiated claims. Through quantitative and qualitative analyses, we provide insights into mistral-large-2402's strengths and weaknesses in handling medical challenges. Our evaluation methodology involves measuring the model's accuracy, completeness, and coherence of responses, as well as its ability to recognize and mitigate hallucinations. The findings of this study contribute to the ongoing discourse on the responsible deployment of LLMs in healthcare and highlight potential areas for improvement in model design and training. [ABSTRACT FROM AUTHOR]

Modern medical ethics utilizes an informed consent process that emphasizes patient autonomy by respecting the decisions of patients who have capacity. When patients are incapacitated, decision making for patients who require medical and psychiatric care is often handled differently. When incapacitated patients require medical care, surrogate decision makers are allowed to make decisions immediately and for the duration of incapacitation, with limited court involvement ("treatment-driven" or "best interests" model). In contrast, for psychiatric treatment, most states utilize "rights-driven" models in which an incapacitated patient who would benefit from psychiatric treatment cannot be admitted or treated absent an additional judicial finding of "dangerousness" or "grave disability" ("danger to self") sufficient to justify civil commitment. The divergence of psychiatric and medical decision making for incapacitated patients began in the 1960s when the basis of most mental health law was established and continues to impact the delivery of present-day psychiatric care. [Psychiatr Ann. 2024;54(5):e146–e150.] [ABSTRACT FROM AUTHOR]

Background: Evaluating moral principles in the Society of Medical Sciences and health care workers (HCWs) is imperative due to their direct contact with the community and the significant impact of their attitudes and decisions on people's lives. This study aimed to determine the components related to ethical decisions in medical sciences students. Methods: One thousand two hundred thirty-five eligible students in the Alborz University of Medical Sciences participated in this descriptive study. We gathered their socio-demographic information, assessed their moral reasoning, and used the ethical decisions questionnaire, Lutsen moral sensitivity questionnaire, and general health questionnaire (GHQ) for data gathering. The data were analyzed with SPSS software version 25 and LISREL version 8.8. Results: According to the path analysis test findings, ethical reasoning significantly correlated with ethical decision-making (B = 0.40). The number of clinical courses passed, moral sensation (moral sensitivity), and the total number of passed academic semesters had the greatest positive and negative association with ethical decision-making, respectively. (B = 0.54), (B = 0.524) and (B = -0.11). Conclusion: Based on the findings of the moral reasoning test, the moral sensation was associated with ethical decision-making, which indicates the necessity of attending to ethical aspects, promoting moral reasoning, sensitivity, and students' accuracy. [ABSTRACT FROM AUTHOR]

As emergency physicians are looking at handheld devices as alternatives to the traditional, cart-based systems, concerns center around whether they are forsaking image quality for a lower price point and whether the handheld can be trusted for medical decision making. We aimed to determine the feasibility of using a handheld ultrasound device in place of a cart-based system during the evaluation of trauma patients using the Focused Assessment with Sonography for Trauma (FAST) examination. This was a prospective study of adult trauma patients who received a FAST examination as part of their evaluation. A FAST examination was performed using a cart-based machine and a handheld device. The results of the examinations were compared with computed tomography imaging. Images obtained from both ultrasound devices were reviewed by an expert for image quality. A total of 62 patients were enrolled in the study. The mean (SD) time to perform a FAST examination using the handheld device was 307.3 (65.3) s, which was significantly less (p = 0.002) than the 336.1 (86.8) s with the cart-based machine. There was strong agreement between the examination results of the handheld and cart-based devices and between the handheld and computed tomography. Image quality scores obtained with the handheld device were lower than those from the cart-based system. Most operators and reviewers agreed that the images obtained from the handheld were adequate for medical decision making. Data support that it is feasible to use the handheld ultrasound device for evaluation of the trauma patient in place of the cart-based system. [ABSTRACT FROM AUTHOR]

Introduction: The literature confirms the challenges of learning clinical reasoning experienced by junior doctors during their transition into the workplace. This study was conducted to explore junior doctors' experiences of clinical reasoning development and recognise the necessary adjustments required to improve the development of clinical reasoning skills. Methods: A hermeneutic phenomenological study was conducted using multiple methods of data collection, including semistructured and narrative interviews (n=18) and post-consultation discussions (n=48). All interviews and post-consultation discussions were analysed to generate themes and identify patterns and associations to explain the dataset. Results: During the transition, junior doctors' approach to clinical reasoning changed from a 'disease-oriented' to a 'practiceoriented' approach, giving rise to the 'Practice-oriented clinical skills development framework' helpful in developing clinical reasoning skills. The freedom to reason within a supportive work environment, the trainees' emotional commitment to patient care, and their early integration into the healthcare team were identified as particularly supportive. The service-oriented nature of the internship, the interrupted supervisory relationships, and early exposure to acute care settings posed challenges for learning clinical reasoning. These findings highlighted the clinical teachers' role, possible teaching strategies, and the specific changes required at the system level to develop clinical reasoning skills among junior doctors. Conclusion: The 'Practice-oriented clinical skills development framework' is a valuable reference point for clinical teachers to facilitate the development of clinical reasoning skills among junior doctors. In addition, this research has provided insights into the responsibilities of clinical teachers, teaching strategies, and the system-related changes that may be necessary to facilitate this process. [ABSTRACT FROM AUTHOR]

Three-dimensional (3D) ultrasound offers the possibility of studying the fetal face in a more global way than conventional twodimensional (2D) ultrasound. In normal cases, the images obtained help to transmit a feeling of calmness to the parents and reinforce the affective bonds with their child. In pathological cases, 3D ultrasound can help parents and other doctors involved to take a more realistic view of the problem. It is expected that the use of this technology will provide parents with the knowledge to have a better judgment while taking decisions. [ABSTRACT FROM AUTHOR]

Identifying determinants of vaccination uptake is critical for public and community health. The population became divided in regard to preventative measures and vaccinations during the COVID-19 pandemic. In addition, there are varying opinions on decisions to vaccinate children against childhood diseases and COVID-19. Recent findings suggest that the COVID-19 pandemic has exacerbated existing vaccine hesitancy. Here, we assess vaccine hesitancy in parents by identifying predictors of vaccine acceptance by parents during the COVID-19 pandemic using a survey given to parents in South Carolina. Knowledge about COVID-19 and vaccinations affects vaccination intentions. Age, education, gender, and politics were also found to predict parents' decisions about vaccinating their kids. Understanding potential barriers to vaccine acceptance will aid healthcare providers and public health entities to better reach the community. [ABSTRACT FROM AUTHOR]

In summer 2022, six points of consensus emerged from a symposium addressing the question, "In the context of U.S. pediatric care, what moral precepts ought to guide parents and clinicians in medical decision making for children?" (Salter et al. 2023). The authors of this statement wrote, however, that the points of consensus may require modification or may not apply in their entirety to children in state custody. This article addresses the consensus recommendations in the context of the thousands of children removed annually from the custody of their parents. While the consensus statements developed at the symposium provide a good starting point for decision-making in the context of these children, some alterations and nuance must be applied to attend to the specific needs of this population. The article works through what special considerations and changes ought to be made to expand the reach of the original points of consensus without neglecting the particular conditions of children in state custody, as well as their parents and caregivers. [ABSTRACT FROM AUTHOR]

Decision makers frequently face decisions about optimal resource allocation. A model-based economic evaluation can be used to guide decision makers in their choices by systematically evaluating the magnitude of expected health effects and costs of decision options and by making trade-offs explicit. We provide a guide to an iterative approach to the medical decision-making process by following a coherent framework, and outline the overarching iterative steps of model-based decision making. We systematized the framework by performing three steps. First, we compiled the existing guidelines provided by the ISPOR-SMDM Modeling Good Research Practices Task Force, and the ISPOR Value of Information Task Force. Second, we identified other previous work related to frameworks and guidelines for model-based decision analyses through a literature search in PubMed. Third, we assessed the role of the evidence and iterative process in decision making and formalized key steps in a model-based decision-making framework. We provide guidance on an iterative approach to medical decision making by applying the compiled iterative model-based decision-making framework. The framework formally combines the decision problem conceptualization (Part I), the model conceptualization and development (Part II), and the process of model-based decision analysis (Part III). Following the overarching steps of the framework ensures compliance to the principles of evidence-based medicine and regular updates of the evidence, given that value of information analysis represents an essential component of model-based decision analysis in the framework. Following the provided guide and the steps outlined in the framework can help inform various health care decisions, and therefore it has the potential to improve decision making. [ABSTRACT FROM AUTHOR]