Vascular access specialist teams versus standard practice for catheter insertion and prevention of failure: a systematic review.

OBJECTIVE: Billions of vascular access devices (VADs) are inserted annually for intravenous therapy worldwide. However, their use is not without challenges. Facilitating the process and enhancing results, hospital authorities have created vascular access specialist teams (VASTs) with advanced competencies in the evaluation, insertion, care and management of VADs. The objective is to compare the effectiveness of VASTs versus standard practice regarding cannulation success and vascular access maintenance in hospitalised adults. DESIGN: Systematic review, using the Mixed Methods Appraisal Tool. DATA SOURCES: We conducted a structured data search on Cochrane Library, MEDLINE, Web of Science, Scopus and EBSCOhost up to 31 May 2023. We did not impose a time limit regarding the date of publication. ELIGIBILITY CRITERIA: Studies were eligible for inclusion in the review if they were randomised and non-randomised trials and observational studies. DATA EXTRACTION AND SYNTHESIS: We included studies that described or evaluated the activity of VASTs compared with clinical practitioners. The outcomes analysed were the success of the cannulation and the incidence of associated adverse effects. RESULTS: The search strategy produced 3053 papers published between 1984 and 2020, from which 12 were selected for analysis. VASTs are heterogeneously described among these studies, which mainly focus on insertions, frequently for patients with difficult intravenous access. Some patients presented with specific needs or requirement for specific insertion technique or catheter type. Compared with usual practice, these studies indicate that the involvement of a VAST is associated with a higher effectiveness in terms of first attempt insertions and insertion success rates, and a reduction in catheter-associated adverse events. However, meta-analyses confirming this trend are not currently possible. CONCLUSIONS: It seems apparent that VASTS contribute to improving the health of patients during the administration of intravenous. VASTs seem to increase the effectiveness of VAD insertion and care and reduce complications. PROSPERO REGISTRATION NUMBER: CRD42021231259.

Evaluating ChatGPT's moral competence in health care-related ethical problems.

Objectives: Artificial intelligence tools such as Chat Generative Pre-trained Transformer (ChatGPT) have been used for many health care-related applications; however, there is a lack of research on their capabilities for evaluating morally and/or ethically complex medical decisions. The objective of this study was to assess the moral competence of ChatGPT. Materials and methods: This cross-sectional study was performed between May 2023 and July 2023 using scenarios from the Moral Competence Test (MCT). Numerical responses were collected from ChatGPT 3.5 and 4.0 to assess individual and overall stage scores, including C-index and overall moral stage preference. Descriptive analysis and 2-sided Student's t-test were used for all continuous data. Results: A total of 100 iterations of the MCT were performed and moral preference was found to be higher in the latter Kohlberg-derived arguments. ChatGPT 4.0 was found to have a higher overall moral stage preference (2.325 versus 1.755) when compared to ChatGPT 3.5. ChatGPT 4.0 was also found to have a statistically higher C-index score in comparison to ChatGPT 3.5 (29.03 ± 11.10 versus 19.32 ± 10.95, P =.0000275). Discussion: ChatGPT 3.5 and 4.0 trended towards higher moral preference for the latter stages of Kohlberg's theory for both dilemmas with C-indices suggesting medium moral competence. However, both models showed moderate variation in C-index scores indicating inconsistency and further training is recommended. Conclusion: ChatGPT demonstrates medium moral competence and can evaluate arguments based on Kohlberg's theory of moral development. These findings suggest that future revisions of ChatGPT and other large language models could assist physicians in the decision-making process when encountering complex ethical scenarios.

Oral glucose tolerance test-The imperfect gold standard for gestational diabetes screening: A qualitative study involving clinicians in regional, rural and remote areas of Western Australia.

ISSUE ADDRESSED: The oral glucose tolerance test is the 'gold standard' for detecting gestational diabetes in Australian and International guidelines. Test completion in regional, rural and remote regions may be as low as 50%. We explored challenges and enablers for regional, rural and remote antenatal clinicians providing gestational diabetes screening to better understand low oral glucose tolerance test completion. METHODS: We conducted a qualitative descriptive study using semi-structured interviews. Participants eligible for the study were doctors or midwives providing antenatal care in regional, rural and remote Western Australia, between August 2019 and November 2020. Interviews were recorded digitally and transcribed into a Word document. We conducted a thematic analysis after initial categorisation and deduction of themes through workshops involving the research team. RESULTS: We found a diversity of viewpoints on oral glucose tolerance test reliability for detecting gestational diabetes. Themes that emerged were; good collaboration between antenatal clinicians is required for successful screening; screening occurs throughout pregnancy using various tests; clinicians make significant efforts to address barriers; clinicians prioritise therapeutic relationships. CONCLUSIONS: Effective universal screening for gestational diabetes in regional, rural and remote Western Australia is difficult and more complex in practice than guidelines imply. Detecting gestational diabetes requires creative solutions, early identification of at risk women and trust and collaboration between clinicians and women. SO WHAT?: Detection of gestational diabetes in regional, rural and remote Western Australia remains poorly completed. New strategies are required to adequately identify women at risk of adverse birth outcomes relating to hyperglycaemia in pregnancy.

Medication administration in aged care facilities: A mixed-methods systematic review.

AIM(S): To synthesize aged care provider, resident and residents' family members' perspectives and experiences of medication administration in aged care facilities; to determine the incidence of medication administration errors, and the impact of medication administration on quality of care and resident-centredness in aged care facilities. DESIGN: A mixed-methods systematic review. PROSPERO ID: CRD42023426990. DATA SOURCES: The AMED, CINAHL, MEDLINE, EMBASE, EMCARE, PsycINFO, Scopus and Web of Science core collection databases were searched in June 2023. REVIEW METHODS: Included studies were independently screened, selected and appraised by two researchers. The Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) checklist was followed, with the Mixed Methods Appraisal Tool was used for critical appraisal. Convergent synthesis of data, thematic synthesis and meta-analysis were performed. RESULTS: One hundred and twenty-eight studies were included (33 qualitative, 85 quantitative and 10 mixed-methods). Five themes were formulated, including 1) Staffing concerns, 2) The uncertain role of residents, 3) Medication-related decision-making, 4) Use of electronic medication administration records and 5) Medication administration errors. Educational interventions for aged care workers significantly reduced medication administration errors, examined across five studies (OR = 0.37, 95%CI 0.28-0.50, p < .001). CONCLUSIONS: Medication administration in aged care facilities is challenging and complex on clinical and interpersonal levels. Clinical processes, medication errors and safety remain focal points for practice. However, more active consideration of residents' autonomy and input by aged care workers and providers is needed to address medication administration's interpersonal and psychosocial aspects. New directions for future research should examine the decision-making behind dose form modification, aged care workers' definitions of medication omission and practical methods to support residents' and their family members' engagement during medication administration. IMPLICATIONS FOR THE PROFESSION AND/OR PATIENT CARE: It is important that medication administration in aged care facilities be more clearly acknowledged as both a clinical and interpersonal task. More attention is warranted regarding aged care workers clinical decision-making, particularly concerning dose form modification, covert administration and medication omissions. Resident-centred care approaches that support resident and family engagement around medication administration may improve adherence, satisfaction and quality of care. IMPACT: What Problem Did the Study Address? Medication administration in aged care facilities is a complex clinical and interpersonal activity. Still, to date, no attempts have been made to synthesize qualitative and quantitative evidence around this practice. There is a need to establish what evidence exists around the perspectives and experiences of aged care workers, residents and resident's family members to understand the challenges, interpersonal opportunities and risks during medication administration. What Were the Main Findings? There is a lack of empirical evidence around resident-centred care approaches to medication administration, and how residents and their families could be enabled to have more input. Dose form modification occurred overtly and covertly as part of medication administration, not just as a method for older adults with swallowing difficulties, but to enforce adherence with prescribed medications. Medication administration errors typically included medication omission as a category of error, despite some omissions stemming from a clear rationale for medication omission and resident input. WHERE AND ON WHOM WILL THE RESEARCH HAVE AN IMPACT?: The findings of this systematic review contribute to aged care policy and practice regarding medication administration and engagement with older adults. This review presents findings that provide a starting point for aged care workers in regards to professional development and reflection on practice, particularly around clinical decision-making on dose form modification, medication administration errors and the tension on enabling resident input into medication administration. For researchers, this review highlights the need to develop resident-centred care approaches and interventions, and to assess whether these can positively impact medication administration, resident engagement, adherence with prescribed medications and quality of care. REPORTING METHOD: This systematic review was reported in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (Page et al., 2021). PATIENT OR PUBLIC CONTRIBUTION: No patient or public contribution to this systematic review.

The impact of AI-based decision support systems on nursing workflows in critical care units.

AIM: This research examines the effects of artificial intelligence (AI)-based decision support systems (DSS) on the operational processes of nurses in critical care units (CCU) located in Amman, Jordan. BACKGROUND: The deployment of AI technology within the healthcare sector presents substantial opportunities for transforming patient care, with a particular emphasis on the field of nursing. METHOD: This paper examines how AI-based DSS affect CCU nursing workflows in Amman, Jordan, using a cross-sectional analysis. A study group of 112 registered nurses was enlisted throughout a research period spanning one month. Data were gathered using surveys that specifically examined several facets of nursing workflows, the employment of AI, encountered problems, and the sufficiency of training. RESULT: The findings indicate a varied demographic composition among the participants, with notable instances of AI technology adoption being reported. Nurses have the perception that there are favorable effects on time management, patient monitoring, and clinical decision-making. However, they continue to face persistent hurdles, including insufficient training, concerns regarding data privacy, and technical difficulties. DISCUSSION: The study highlights the significance of thorough training programs and supportive mechanisms to improve nurses' involvement with AI technologies and maximize their use in critical care environments. Although there are differing degrees of contentment with existing AI systems, there is a general agreement on the necessity of ongoing enhancement and fine-tuning to optimize their efficacy in enhancing patient care results. CONCLUSION AND IMPLICATIONS FOR NURSING AND/OR HEALTH POLICY: This research provides essential knowledge about the intricacies of incorporating AI into nursing practice, highlighting the significance of tackling obstacles to guarantee the ethical and efficient use of AI technology in healthcare.

Pharmacists and pharmacy students' perceptions on how a new teaching model supports their clinical decision-making.

BACKGROUND AND PURPOSE: Clinical decision-making (CDM) is crucial in pharmacy practice, necessitating effective teaching in undergraduate and postgraduate pharmacy education. This study aims to explore undergraduates and postgraduates' perceptions of how a new teaching model supports their CDM when addressing patient cases. EDUCATIONAL ACTIVITY AND SETTING: Implemented in a full-day CDM course for pharmacy students and a half-day course for pharmacists in the Netherlands, the model, accompanied by a learning guide, facilitated CDM in patient cases. Eight courses were conducted between September 2022 to June 2023, followed by an online survey measuring participants' agreement on how the model supported their CDM, using a 5-point Likert scale. Additionally, three open-ended questions were included to elicit learning outcomes and self-development opportunities. FINDINGS: Of 175 invited participants, 159 (91%) completed the survey. Most agreed the teaching model supported their CDM, particularly in considering the patient's healthcare needs and context (96%), and exploring all available options (96%). Participants found the model provided a clear structure (97%), and fostered critical thinking (93%). The most frequently mentioned learning outcomes and self-development opportunities included collecting sufficient relevant information, maintaining a broad perspective, and decelerating the process to avoid premature closure. SUMMARY: Participants agreed that the teaching model helped them to make clinical decisions. Both undergraduate and postgraduate pharmacy education could possibly benefit from the teaching model's implementation in supporting pharmacy students and pharmacists conducting CDM in pharmacy practice.

Real world management of individuals with severe FXI deficiency and its impact on clinical outcomes: Experience from a haemophilia treatment centre.

INTRODUCTION: The management of Factor XI deficiency is challenged by a variable association between FXI level and bleeding phenotype. Additionally, there is scarce data describing management strategies and their outcomes, specifically bleeding, thrombosis, and other complications. AIMS: To evaluate bleeding, thrombosis, and other complications in individuals with severe FXI deficiency seen in our comprehensive haemophilia treatment centre (HTC). Peri-procedural management strategies and the resulting impact on bleeding and other clinically relevant outcomes were reported. METHODS: Retrospective review of the electronic medical record of adult patients with severe FXI deficiency (< 20% activity) seen at a New York City comprehensive HTC between 2017 and 2022. Procedures, haemostatic management, and outcomes were collected and analysed. RESULTS: We identified 38 individuals (64%) females with severe FXI deficiency. The mean age was 56 ± 21 years (SD). The median FXI activity level was 3% (IQR: 1-8%). The mean BAT score was 3.1 ± 2.4; (52%) individuals did not have a history of bleeding. A total of 256 surgeries and procedures were performed. There was reduced bleeding with preventative or reactive treatment during procedures. Arterial but not venous thrombotic complications were observed. Plasma was mostly used for procedures associated with higher risk of bleeding and antifibrinolytics for procedures at sites of high fibrinolysis. CONCLUSIONS: Current management strategies pose a burden of care for these patients and manifested as nonbleeding adverse events and changes in clinical management. These findings highlight the need for novel investigation in predicting and managing bleeding for individuals with severe FXI deficiency.

The impact of regional disparities on the availability of meningococcal vaccines in the US.

BACKGROUND: In the United States (US), three types of vaccines are available to prevent invasive meningococcal disease (IMD), a severe and potentially fatal infection: quadrivalent conjugate vaccines against serogroups A, C, W, Y (MenACWY), and monovalent vaccines against serogroup B (MenB) as well as a newly licensed pentavalent vaccine (MenABCWY) protecting against serogroup A, B, C, W, and Y. The CDC's Advisory Committee on Immunization Practices (ACIP) routinely recommends MenACWY vaccine for all 11- to 12-year-olds with a booster dose at 16 years. MenB vaccination is recommended based on shared clinical decision-making (SCDM) for 16- to 23-year-olds. Recently, the pentavalent meningococcal vaccine (MenABCWY) was recommended by the ACIP. Meningococcal vaccine uptake is suboptimal across the country, particularly among individuals with lower socioeconomic status (SES), despite these recommendations. The objective of the spatial analyses was to assess the relationship between stocking of MenACWY and MenB vaccines, area-level SES, and state-level policies. METHODS: The number of MenACWY and MenB doses stocked by vaccinators was obtained from IQVIA and the CDC's Vaccine for Children (VFC) program and compiled into a county-level dataset from 2016 to 2019. SES, as measured using the CDC's Social Vulnerability Index (SVI), state-level school recommendations, and universal purchasing programs were among the main county-level covariates included to control for factors likely influencing stocking. Data were stratified by public and private market. Bayesian spatial regression models were developed to quantify the variations in rates of stocking and the relative rates of stocking of both vaccines. RESULTS: After accounting for county-level characteristics, lower SES counties tended to have fewer doses of MenB relative to MenACWY on both public and private markets. Lower SES counties tended to have more supply of public vs. private doses. Universal purchasing programs had a strong effect on the markets for both vaccines shifting nearly all doses to the public market. School vaccination strategy was key for improving stocking rates. CONCLUSIONS: Overall, the results show that MenACWY has greater stock relative to MenB across the US. This difference is exacerbated in vulnerable areas without school entry requirements for vaccination and results in inequity of vaccine availability. Beyond state-level policy and SES differences, SCDM recommendations may be a contributing factor, although this was not directly assessed by our model.

Precision medicine: Externally validated explainable AI support tool for predicting sustainability of infliximab and vedolizumab in ulcerative colitis.

OBJECTIVE: Drug sustainability (DS), a surrogate marker for drug efficacy, is important, especially when aiming for precision medicine. However, it lacks reliable prediction methods. AIMS: To develop and externally validate a web-based artificial intelligence(AI)-derived tool for predicting DS of infliximab and vedolizumab in patients with moderate-to-severe Ulcerative Colitis (UC). METHODS: Data from three Israeli centers included infliximab or vedolizumab patients treated for >54 weeks. Sustainability meant no corticosteroids, hospitalizations or surgeries. Machine learning techniques predicted >54-week and overall DS using baseline clinical data. RESULTS: The model was developed using data from 246 patients from Rabin Medical Center and externally validated on 67 patients from Rambam Health Care Campus and Sheba Medical Center. No significant difference in DS was observed across the datasets. Most patients were biologic-naïve and primarily treated with vedolizumab. The model performed well, with an area under the ROC curve of 0.86, and showed good accuracy (65.5 %-76.9 %) across the test sets. CONCLUSIONS: The study introduces a novel, AI-based tool for predicting >54-week DS of infliximab and vedolizumab in moderate-to-severe UC, using baseline parameters. This can aid clinical decision-making in the framework of precision medicine, promising to optimize disease management while maintaining physician autonomy.

Artificial Intelligence in Spinal Imaging and Patient Care: A Review of Recent Advances.

Artificial intelligence (AI) is transforming spinal imaging and patient care through automated analysis and enhanced decision-making. This review presents a clinical task-based evaluation, highlighting the specific impact of AI techniques on different aspects of spinal imaging and patient care. We first discuss how AI can potentially improve image quality through techniques like denoising or artifact reduction. We then explore how AI enables efficient quantification of anatomical measurements, spinal curvature parameters, vertebral segmentation, and disc grading. This facilitates objective, accurate interpretation and diagnosis. AI models now reliably detect key spinal pathologies, achieving expert-level performance in tasks like identifying fractures, stenosis, infections, and tumors. Beyond diagnosis, AI also assists surgical planning via synthetic computed tomography generation, augmented reality systems, and robotic guidance. Furthermore, AI image analysis combined with clinical data enables personalized predictions to guide treatment decisions, such as forecasting spine surgery outcomes. However, challenges still need to be addressed in implementing AI clinically, including model interpretability, generalizability, and data limitations. Multicenter collaboration using large, diverse datasets is critical to advance the field further. While adoption barriers persist, AI presents a transformative opportunity to revolutionize spinal imaging workflows, empowering clinicians to translate data into actionable insights for improved patient care.

Reassessing the Use of Race in Clinical Algorithms: An Interactive, Case-Based Session for Medical Students Using eGFR.

Introduction: Medical curricula implicitly teach that race has a biological basis. Clinical rotations reinforce this misconception as race-based algorithms are used to guide clinical decision-making. This module aims to expose the fallacy of race in clinical algorithms, using the estimated glomerular filtration rate (eGFR) equation as an example. Methods: We created a 60-minute module in consultation with nephrologists. The format was an interactive, case-based presentation with a didactic section. A third-year medical student facilitated the workshops to medical students. Evaluation included pre/post surveys using 5-point Likert scales to assess awareness regarding use of race as a biological construct. Higher scores indicated increased awareness. Results: Fifty-five students participated in the module. Pre/post results indicated that students significantly improved in self-perceived knowledge of the history of racism in medicine (2.6 vs. 3.2, p < .001), awareness of race in clinical algorithms (2.7 vs. 3.7, p < .001), impact of race-based eGFR on quality of life/treatment outcomes (4.5 vs. 4.8, p = .01), differences between race and ancestry (3.7 vs. 4.3, p < .001), and implications of not removing race from the eGFR equation (2.7 vs. 4.2, p < .001). Students rated the workshops highly for quality and clarity. Discussion: Our module expands on others' work to expose the fallacy of race-based algorithms and define its impact on health equity. Limitations include a lack of objective assessment of knowledge acquisition. We recommend integrating this module into preclinical and clinical curricula to discuss the use of race in medical literature and clinical practice.

Hospital Staff Perspectives on the Drivers and Challenges in Implementing a Virtual Rehabilitation Ward: Qualitative Study.

Background: Over the past decade, the adoption of virtual wards has surged. Virtual wards aim to prevent unnecessary hospital admissions, expedite home discharge, and enhance patient satisfaction, which are particularly beneficial for the older adult population who faces risks associated with hospitalization. Consequently, substantial investments are being made in virtual rehabilitation wards (VRWs), despite evidence of varying levels of success in their implementation. However, the facilitators and barriers experienced by virtual ward staff for the rapid implementation of these innovative care models remain poorly understood. Objective: This paper presents insights from hospital staff working on an Australian VRW in response to the growing demand for programs aimed at preventing hospital admissions. We explore staff's perspectives on the facilitators and barriers of the VRW, shedding light on service setup and delivery. Methods: Qualitative interviews were conducted with 21 VRW staff using the Nonadoption, Abandonment, Scale-up, Spread, and Sustainability (NASSS) framework. The analysis of data was performed using framework analysis and the 7 domains of the NASSS framework. Results: The results were mapped onto the 7 domains of the NASSS framework. (1) Condition: Managing certain conditions, especially those involving comorbidities and sociocultural factors, can be challenging. (2) Technology: The VRW demonstrated suitability for technologically engaged patients without cognitive impairment, offering advantages in clinical decision-making through remote monitoring and video calls. However, interoperability issues and equipment malfunctions caused staff frustration, highlighting the importance of promptly addressing technical challenges. (3) Value proposition: The VRW empowered patients to choose their care location, extending access to care for rural communities and enabling home-based treatment for older adults. (4) Adopters and (5) organizations: Despite these benefits, the cultural shift from in-person to remote treatment introduced uncertainties in workflows, professional responsibilities, resource allocation, and intake processes. (6) Wider system and (7) embedding: As the service continues to develop to address gaps in hospital capacity, it is imperative to prioritize ongoing adaptation. This includes refining the process of smoothly transferring patients back to the hospital, addressing technical aspects, ensuring seamless continuity of care, and thoughtfully considering how the burden of care may shift to patients and their families. Conclusions: In this qualitative study exploring health care staff's experience of an innovative VRW, we identified several drivers and challenges to implementation and acceptability. The findings have implications for future services considering implementing VRWs for older adults in terms of service setup and delivery. Future work will focus on assessing patient and carer experiences of the VRW.

Health professionals implicit bias of patients with low socioeconomic status (SES) and its effects on clinical decision-making: a scoping review.

OBJECTIVES: Research indicates that people with lower socioeconomic status (SES) receive inferior healthcare and experience poorer health outcomes compared with those with higher SES, in part due to health professional (HP) bias. We conducted a scoping review of the impact of HP bias about SES on clinical decision-making and its effect on the care of adults with lower SES. DESIGN: JBI scoping review methods were used to perform a systematic comprehensive search for literature. The scoping review protocol has been published in BMJ Open. DATA SOURCES: Medline, Embase, ASSIA, Scopus and CINAHL were searched, from the first available start date of the individual database to March 2023. Two independent reviewers filtered and screened papers. ELIGIBILITY CRITERIA: Studies of all designs were included in this review to provide a comprehensive map of the existing evidence of the impact of HP bias of SES on clinical decision-making and its effect on the care for people with lower SES. DATA EXTRACTION AND SYNTHESIS: Data were gathered using an adapted JBI data extraction tool for systematic scoping reviews. RESULTS: Sixty-seven papers were included from 1975 to 2023. 35 (73%) of the included primary research studies reported an association between HP SES bias and decision-making. Thirteen (27%) of the included primary research studies did not find an association between HP SES bias and decision-making. Stereotyping and bias can adversely affect decision-making when the HP is fatigued or has a high cognitive load. There is evidence of intersectionality which can have a powerful cumulative effect on HP assessment and subsequent decision-making. HP implicit bias may be mitigated through the assertiveness of the patient with low SES. CONCLUSION: HP decision-making is at times influenced by non-medical factors for people of low SES, and assumptions are made based on implicit bias and stereotyping, which compound or exacerbate health inequalities. Research that focuses on decision-making when the HP has a high cognitive load, would help the health community to better understand this potential influence.

Psychosocial Factors Associated With Thoughts Regarding Life-Sustaining Treatment for Oneself and Family Members.

OBJECTIVE: This study aims to investigate the thoughts of the general population regarding life-sustaining treatment for both oneself and family members and to assess the factors associated with those thoughts. METHODS: A total of 1,500 individuals participated in this study by completing a questionnaire consisting of self-reporting items with some instructions, basic demographic information, thoughts on life-sustaining treatment, and psychosocial scales. The disease status was calculated using the Charlson Comorbidity Index. The psychosocial scales included the Patient Health Questionnaire-9 (PHQ-9), Generalized Anxiety Disorder-7 (GAD-7), Pittsburgh Sleep Quality Index, and Multidimensional Scale of Perceived Social Support. RESULTS: The majority of participants did not want to receive life-sustaining treatment for both themselves and their families. However, more people wanted life-sustaining treatment for their family members (35.9%) than for themselves (21.6%). Among the basic demographic characteristics, there were significant differences in age, sex, marital status, living arrangements, occupational status, religion, and disease status. Regarding the psychosocial scales, there were significant differences in the PHQ-9 and GAD-7 scores between the group that preferred life-sustaining treatment for family members and the group that did not. CONCLUSION: The findings suggest that life-sustaining treatment decisions for oneself and for one's family members can be different. We recommend a more clear expression of one's preferences regarding the last moments of one's life, including advance directives.

Reweighting and validation of the hospital frailty risk score using electronic health records in Germany: a retrospective observational study.

BACKGROUND: In the hospital setting, frailty is a significant risk factor, but difficult to measure in clinical practice. We propose a reweighting of an existing diagnoses-based frailty score using routine data from a tertiary care teaching hospital in southern Germany. METHODS: The dataset includes patient characteristics such as sex, age, primary and secondary diagnoses and in-hospital mortality. Based on this information, we recalculate the existing Hospital Frailty Risk Score. The cohort includes patients aged ≥ 75 and was divided into a development cohort (admission year 2011 to 2013, N = 30,525) and a validation cohort (2014, N = 11,202). A limited external validation is also conducted in a second validation cohort containing inpatient cases aged ≥ 75 in 2022 throughout Germany (N = 491,251). In the development cohort, LASSO regression analysis was used to select the most relevant variables and to generate a reweighted Frailty Score for the German setting. Discrimination is assessed using the area under the receiver operating characteristic curve (AUC). Visualization of calibration curves and decision curve analysis were carried out. Applicability of the reweighted Frailty Score in a non-elderly population was assessed using logistic regression models. RESULTS: Reweighting of the Frailty Score included only 53 out of the 109 frailty-related diagnoses and resulted in substantially better discrimination than the initial weighting of the score (AUC = 0.89 vs. AUC = 0.80, p < 0.001 in the validation cohort). Calibration curves show a good agreement between score-based predictions and actual observed mortality. Additional external validation using inpatient cases aged ≥ 75 in 2022 throughout Germany (N = 491,251) confirms the results regarding discrimination and calibration and underlines the geographic and temporal validity of the reweighted Frailty Score. Decision curve analysis indicates that the clinical usefulness of the reweighted score as a general decision support tool is superior to the initial version of the score. Assessment of the applicability of the reweighted Frailty Score in a non-elderly population (N = 198,819) shows that discrimination is superior to the initial version of the score (AUC = 0.92 vs. AUC = 0.87, p < 0.001). In addition, we observe a fairly age-stable influence of the reweighted Frailty Score on in-hospital mortality, which does not differ substantially for women and men. CONCLUSIONS: Our data indicate that the reweighted Frailty Score is superior to the original Frailty Score for identification of older, frail patients at risk for in-hospital mortality. Hence, we recommend using the reweighted Frailty Score in the German in-hospital setting.

Reaching the ceiling? Empirical scaling behaviour for deep EEG pathology classification.

Machine learning techniques, particularly deep convolutional neural networks (ConvNets), are increasingly being used to automate clinical EEG analysis, with the potential to reduce the clinical burden and improve patient care. However, further research is required before they can be used in clinical settings, particularly regarding the impact of the number of training samples and model parameters on their testing error. To address this, we present a comprehensive study of the empirical scaling behaviour of ConvNets for EEG pathology classification. We analysed the testing error with increasing the training samples and model size for four different ConvNet architectures. The focus of our experiments is width scaling, and we have increased the number of parameters to up to 1.8 million. Our evaluation was based on two publicly available datasets: the Temple University Hospital (TUH) Abnormal EEG Corpus and the TUH Abnormal Expansion Balanced EEG Corpus, which together contain 10,707 training samples. The results show that the testing error follows a saturating power-law with both model and dataset size. This pattern is consistent across different datasets and ConvNet architectures. Furthermore, empirically observed accuracies saturate at 85%-87%, which may be due to an imperfect inter-rater agreement on the clinical labels. The empirical scaling behaviour of the test performance with dataset and model size has significant implications for deep EEG pathology classification research and practice. Our findings highlight the potential of deep ConvNets for high-performance EEG pathology classification, and the identified scaling relationships provide valuable recommendations for the advancement of automated EEG diagnostics.

Shared decision-making in advanced physiotherapy and first contact physiotherapy management of adults with musculoskeletal disorders in the United Kingdom: An online cross-sectional survey.

RATIONALE: Advanced practice physiotherapy roles (Advanced Physiotherapy Practitioners [APPs] and First Contact Physiotherapists [FCPs]) are pivotal in supporting patients to manage their musculoskeletal (MSK) conditions. Having a greater understanding of how decisions are made by these practitioners will inform competency frameworks and improve the provision of patient-centred care. AIM: To evaluate the current knowledge, views and use of shared decision-making in MSK advanced physiotherapy practice in the United Kingdom. METHODS: A cross-sectional survey using an online questionnaire was used to collect demographic information, knowledge, views and self-reported use of shared decision-making (SDM) of APPs and FCPs who work with adults with MSK disorders in the United Kingdom. RESULTS: Responses from 49 participants (25 APPs and 24 FCPs) were included in the study. In total, 80% of participants had received SDM training and overall high levels of knowledge were shown. Only 12% of participants used a communication model to facilitate SDM. In total, 80% of participants reported making decisions together with the patient either always or most of the time. FCPs favoured a more patient-led approach to decision-making compared to APPs who favoured collaborative decision-making. The most commonly reported barriers to SDM included lack of time, lack of patient education resources, lack of access to patient decision aids and treatment pathway restrictions. CONCLUSIONS: The responses in this study showed that overall APPs and FCPs have good knowledge of SDM and report routine use of collaborative and patient-led decision-making approaches.

Comparing the diagnostic considerations between general practitioners with a special interest in cardiovascular disease and those without in patients with symptoms suggestive of heart failure: a vignette study.

BACKGROUND: General practitioners (GPs) specialized in cardiovascular disease (GPSI-CVD) may suspect heart failure (HF) more easily than GPs not specialized in CVD. We assessed whether GPSI-CVD consider investigations aimed at detecting HF more often than other GPs in two clinical scenarios of an older male person with respiratory and suggestive HF symptoms. METHODS: In this vignette study, Dutch GPs evaluated two vignettes. The first involved a 72-year-old man with hypertension and a 30 pack-year smoking history who presented himself with symptoms of a common cold, but also shortness of breath, reduced exercise tolerance, and signs of fluid overload. The second vignette was similar but now the 72-year-old man was known with chronic obstructive pulmonary disease (COPD). GPs could select diagnostic tests from a multiple-choice list with answer options targeted at HF, COPD or exacerbation of COPD, or lower respiratory tract infection. With Pearson Chi-square or Fisher's exact test differences between the two GP groups were assessed regarding the chosen diagnostic tests. RESULTS: Of the 148 participating GPs, 25 were GPSI-CVD and 123 were other GPs. In the first vignette, GPSI-CVD more often considered performing electrocardiography (ECG) than other GPs (64.0% vs. 32.5%, p = 0.003). In the second vignette, GPSI-CVD were more inclined to perform both ECG (36.0% vs. 12.2%, p = 0.003) and natriuretic peptide testing (56.0% vs. 32.5%, p = 0.006). CONCLUSIONS: Most GPs seemed to consider multiple diagnoses, including HF, with GPSI-CVD more likely performing ECG and natriuretic peptide testing in an older male person with both respiratory and suggestive HF symptoms.

Development of clinical decision-making among undergraduate nursing students: the effect of unfolding case-based learning.

OBJECTIVES: This prospective cohort study evaluated the effect of unfolding case-based learning on undergraduate nursing students' self-perceived clinical decision-making ability. METHODS: Students' self-reported responses to Jenkins's Clinical Decision Making in Nursing Scale were compared between the unfolding case-based learning cohort (n=140) and the comparison cohort (n=126) at a school of nursing in the United States. RESULTS: The results revealed similar students' responses between the two study cohorts. However, unfolding case-based learning significantly increased students' perceived proficiency in "search for information and unbiased assimilation of new information". CONCLUSIONS: Findings from the present study highlight possibilities presented by unfolding case-based learning in undergraduate nursing education. The study supports that unfolding case studies can be introduced early on, and then nurtured throughout the undergraduate program to influence the development of nursing students' clinical decision-making skills.

Use of Real-World FHIR Data Combined with Context-Sensitive Decision Modeling to Guide Sentinel Biopsy in Melanoma.

Background: To support clinical decision-making at the point of care, the "best next step" based on Standard Operating Procedures (SOPs) and actual accurate patient data must be provided. To do this, textual SOPs have to be transformed into operable clinical algorithms and linked to the data of the patient being treated. For this linkage, we need to know exactly which data are needed by clinicians at a certain decision point and whether these data are available. These data might be identical to the data used within the SOP or might integrate a broader view. To address these concerns, we examined if the data used by the SOP is also complete from the point of view of physicians for contextual decision-making. Methods: We selected a cohort of 67 patients with stage III melanoma who had undergone adjuvant treatment and mainly had an indication for a sentinel biopsy. First, we performed a step-by-step simulation of the patient treatment along our clinical algorithm, which is based on a hospital-specific SOP, to validate the algorithm with the given Fast Healthcare Interoperability Resources (FHIR)-based data of our cohort. Second, we presented three different decision situations within our algorithm to 10 dermatooncologists, focusing on the concrete patient data used at this decision point. The results were conducted, analyzed, and compared with those of the pure algorithmic simulation. Results: The treatment paths of patients with melanoma could be retrospectively simulated along the clinical algorithm using data from the patients' electronic health records. The subsequent evaluation by dermatooncologists showed that the data used at the three decision points had a completeness between 84.6% and 100.0% compared with the data used by the SOP. At one decision point, data on "patient age (at primary diagnosis)" and "date of first diagnosis" were missing. Conclusions: The data needed for our decision points are available in the FHIR-based dataset. Furthermore, the data used at decision points by the SOP and hence the clinical algorithm are nearly complete compared with the data required by physicians in clinical practice. This is an important precondition for further research focusing on presenting decision points within a treatment process integrated with the patient data needed.