Care Decisions Research Articles

Navigating Data Warehousing Implementation in Jordanian Healthcare Sector: Challenges and Opportunities

Introduction: The implementation of data warehouse systems offers great potential for improving patient care, operational efficiency, and strategic decision-making. This study explores the challenges and opportunities of implementing data storage solutions in the Jordanian healthcare industry. Objectives: To investigate current data management practices, perceptions of data warehouses, and factors influencing adoption readiness among IT professionals in Jordanian healthcare organizations. Methods: A survey was conducted involving 102 IT professionals from various healthcare organizations in Jordan. Participants responded to a structured questionnaire, providing insights into key benefits, expected challenges, technical requirements, and future prospects for data warehousing in their organizations. Results: The study demonstrated the critical role of data warehouses in enhancing decision-making, patient care coordination, and operational efficiency within the Jordanian healthcare system. However, significant challenges such as data integration, security concerns, and regulatory compliance were identified. Conclusions: The paper provides recommendations to address these challenges and maximize the benefits of healthcare data warehouses in Jordan. Key strategies include investing in technical expertise, ensuring compatibility with existing systems, and improving data management practices. This study enhances understanding of the complexities associated with implementing data warehousing in the Jordanian healthcare industry and offers valuable insights for future research and practice in this evolving field.

Transforming Health Care Through Chatbots for Medical History-Taking and Future Directions: Comprehensive Systematic Review.

The integration of artificial intelligence and chatbot technology in health care has attracted significant attention due to its potential to improve patient care and streamline history-taking. As artificial intelligence-driven conversational agents, chatbots offer the opportunity to revolutionize history-taking, necessitating a comprehensive examination of their impact on medical practice. This systematic review aims to assess the role, effectiveness, usability, and patient acceptance of chatbots in medical history-taking. It also examines potential challenges and future opportunities for integration into clinical practice. A systematic search included PubMed, Embase, MEDLINE (via Ovid), CENTRAL, Scopus, and Open Science and covered studies through July 2024. The inclusion and exclusion criteria for the studies reviewed were based on the PICOS (participants, interventions, comparators, outcomes, and study design) framework. The population included individuals using health care chatbots for medical history-taking. Interventions focused on chatbots designed to facilitate medical history-taking. The outcomes of interest were the feasibility, acceptance, and usability of chatbot-based medical history-taking. Studies not reporting on these outcomes were excluded. All study designs except conference papers were eligible for inclusion. Only English-language studies were considered. There were no specific restrictions on study duration. Key search terms included "chatbot*," "conversational agent*," "virtual assistant," "artificial intelligence chatbot," "medical history," and "history-taking." The quality of observational studies was classified using the STROBE (Strengthening the Reporting of Observational Studies in Epidemiology) criteria (eg, sample size, design, data collection, and follow-up). The RoB 2 (Risk of Bias) tool assessed areas and the levels of bias in randomized controlled trials (RCTs). The review included 15 observational studies and 3 RCTs and synthesized evidence from different medical fields and populations. Chatbots systematically collect information through targeted queries and data retrieval, improving patient engagement and satisfaction. The results show that chatbots have great potential for history-taking and that the efficiency and accessibility of the health care system can be improved by 24/7 automated data collection. Bias assessments revealed that of the 15 observational studies, 5 (33%) studies were of high quality, 5 (33%) studies were of moderate quality, and 5 (33%) studies were of low quality. Of the RCTs, 2 had a low risk of bias, while 1 had a high risk. This systematic review provides critical insights into the potential benefits and challenges of using chatbots for medical history-taking. The included studies showed that chatbots can increase patient engagement, streamline data collection, and improve health care decision-making. For effective integration into clinical practice, it is crucial to design user-friendly interfaces, ensure robust data security, and maintain empathetic patient-physician interactions. Future research should focus on refining chatbot algorithms, improving their emotional intelligence, and extending their application to different health care settings to realize their full potential in modern medicine. PROSPERO CRD42023410312; www.crd.york.ac.uk/prospero.

Pulmonary Function after Nonmyeloablative Hematopoietic Cell Transplant for Sickle Cell Disease.

Rationale: Sickle cell disease (SCD) is a monogenetic condition with recurring vasoocclusive events causing lifelong pulmonary morbidity and mortality. There is increasing access to curative therapies, such as hematopoietic cell transplant (HCT), for people living with SCD. However, more information on pulmonary function in adults with SCD after HCT is needed to best guide decisions for HCT and post-HCT care. Objectives: To test the hypothesis that forced expiratory volume in 1 second (FEV1) and other pulmonary function testing (PFT) parameters remain stable 3 years after HCT. Methods: People living with SCD undergoing nonmyeloablative HCT in a prospective cohort at the NIH Clinical Center from 2004 to 2019 were evaluated for enrollment. Global Lung Function Initiative reference equations and descriptive statistics were calculated before HCT and annually for 3 years. Six-minute-walk distance (6MWD) testing was performed. Generalized estimating equations were employed to evaluate interindividual changes in PFT parameters and 6MWD. Results: Of 97 patients with SCD undergoing HCT, 41 (42%) were female with median (25th, 75th percentile) age 31.8 (24.8, 38.0) years. Each year of measurement included the following numbers of subjects available for analysis with PFTs: baseline (n = 97), Year 1 (n = 91), Year 2 (n = 72), and Year 3 (n = 55); and the following numbers of subjects available for analysis with 6MWD: baseline (n = 79), Year 1 (n = 73), Year 2 (n = 57), and Year 3 (n = 41). Pre-HCT FEV1 was median (25th, 75th percentile) 68.3% (61.3%, 80.3%) and 69.2% (60.8%, 77.7%) 3 years after HCT, and pre-HCT diffusing capacity of the lung for carbon monoxide (DlCO) was 60.5% (53.0%, 66.3%) and 64.6% (55.1%, 73.4%) 3 years after HCT. Generalized estimating equations estimated that DlCO percent predicted increased significantly by 3.7% (95% confidence interval, 1.0%, 6.3%), and the 6MWD significantly increased by 25.9 (6.6, 45.2) meters 3 years after HCT, whereas there was no significant change in percent predicted FEV1 or FVC compared with before HCT. Conclusions: Overall, PFT results remained stable and there was an improvement in DlCO and 6MWD in this predominantly adult cohort undergoing nonmyeloablative HCT for SCD. Allogeneic HCT for SCD may cease the cycle of vasoocclusive pulmonary injury and prevent continued damage. Multicenter studies are needed to evaluate the long-term lung health effects of HCT for SCD in adults and children.

Patient and Caregiver Perspectives on Gender Disparity in Chronic Kidney Disease: Questionnaire Survey, Based on an Interview Study

Introduction: Chronic kidney disease (CKD) in stages 3–5 without albuminuria occurs more often in women than in men; however, most patients initiating and receiving kidney replacement therapy are men. Sex-determined biological factors and gender-related aspects both likely account for this discrepancy. Patient opinions on gender-related discrepancies in kidney care have not been investigated. Methods: Building upon the findings of semi-structured interviews previously conducted with CKD patients and their caregivers, two questionnaires were developed to investigate patient behavior and opinions relating to gender and CKD. These questionnaires containing 39 items were distributed to eight outpatient clinics in Austria. Responses were descriptively analyzed and compared between genders, as well as between age-groups and CKD stages. Results: Questionnaires from 783 patients and 98 caregivers were included in the analysis and covered health awareness and self-management of disease, the impact of gender roles and gender equality, and patient autonomy and trust in the health-care system. A total of 56.1% of men patients and 63.1% of women patients found that women were better at looking after their health compared to men (41.1%/34.3% no difference, 2.8%/2.6% men better). A total of 95.4% of men patients, 95.0% of women patients, 100% of men caregivers, and 95.5% of women caregivers stated that all patients with kidney disease were treated completely equally, irrespective of gender. Conclusion: Neither the patients nor the caregivers stated gender-determined treatment decisions in CKD care. Both men and women however agreed that women are better at maintaining their own health and excel in disease self-management.

Toward Realizing the Promise of AI in Precision Health Across the Spectrum of Care

Significant progress has been made in augmenting clinical decision-making using artificial intelligence (AI) in the context of secondary and tertiary care at large academic medical centers. For such innovations to have an impact across the spectrum of care, additional challenges must be addressed, including inconsistent use of preventative care and gaps in chronic care management. The integration of additional data, including genomics and data from wearables, could prove critical in addressing these gaps, but technical, legal, and ethical challenges arise. On the technical side, approaches for integrating complex and messy data are needed. Data and design imperfections like selection bias, missing data, and confounding must be addressed. In terms of legal and ethical challenges, while AI has the potential to aid in leveraging patient data to make clinical care decisions, we also risk exacerbating existing disparities. Organizations implementing AI solutions must carefully consider how they can improve care for all and reduce inequities.

Management of periprosthetic joint infection of the shoulder: A narrative review

Evidence for management of shoulder periprosthetic joint infection (PJI) has traditionally originated from the hip and knee literature. The differing microbiome, anatomy and implants used in the shoulder mean this evidence is not always directly transferrable. The 2018 Philadelphia International Consensus Meeting for the first-time produced evidence-based guidelines and diagnostic criteria relating specifically to PJI of the shoulder. These guidelines and criteria recognize the pathogenicity of lower virulence organisms in the shoulder which often means clinical presentation is less obvious than other joints.The role of Cutibacterium acnes in shoulder PJI is the subject of increasing basic science and clinical research and advances in microbiological research may help to understand the pathology behind shoulder infections. There is new evidence that outcomes after revision shoulder arthroplasty are dependent on the virulence of the causative organism. An individualised approach to treatment considering host factors, organism, soft tissues and bone stock is recommended.Debate continues in the literature regarding the indications of one- or two-stage revision and the latest evidence is discussed and synthesized in this review article. We advocate careful multidisciplinary team decision making for cases of shoulder PJI and recognize a limited role for debridement and implant retention in acute shoulder PJI (<6 weeks). There appears to be a role for one-stage revision in lower risk cases with low virulence organisms but caution against its’ universal adoption. In higher risk or complex cases, there remains a clear role for two-stage revision arthroplasty, and we detail the specifics of this protocol and procedure from our tertiary shoulder and elbow unit.

Does serum neurofilament light chain measurement influence therapeutic decisions in multiple sclerosis?

BackgroundThe assessment of serum neurofilament light chain (sNfL) concentration in multiple sclerosis (MS) is a useful tool for predicting clinical outcomes and assessing treatment response. However, its use in clinical practice is still limited. We aimed to assess how measurement of sNfL influences neurologists’ treatment decisions in MS. MethodsWe conducted a cross-sectional, web-based study in collaboration with the Spanish Society of Neurology. Neurologists involved in MS care were presented with different simulated case scenarios of patients experiencing either their first demyelinating MS event or a relapsing-remitting MS. The primary outcome was therapeutic inertia (TI), defined as the absence of treatment initiation or intensification despite elevated sNfL levels. Nine cases were included to estimate the TI score (range 0–9, where higher values represented a higher degree of TI). ResultsA total of 116 participants were studied. Mean age (standard deviation-SD) was 41.9 (10.1) years, 53.4 % male. Seventy-eight (67.2 %) were neurologists fully dedicated to the care of demyelinating disorders. Mean (SD) TI score was 3.65 (1.01). Overall, 92.2 % of participants (n = 107) presented TI in at least 2/9 case scenarios. The lack of full dedication to MS care (p = 0.014), preference for taking risks (p = 0.008), and low willingness to adopt evidence-based innovations (p = 0.009) were associated with higher TI scores in the multivariate analysis after adjustment for confounders. ConclusionTI was a common phenomenon among neurologists managing MS patients when faced with the decision to initiate or escalate treatment based on elevated sNfL levels. Identifying factors associated with this phenomenon may help optimize treatment decisions in MS care.

Toward Laboratory Notification in Pediatric Emergency Departments.

This study explores how patient's laboratory result are accessed in pediatric emergency departments. The rapid turnaround of laboratory results and their timely access by the medical team are crucial for effective patient management and care decision-making. This study revealed a systematic access prioritization to the Electronic Health Record, led by physicians, followed by nurses, and then other healthcare staff Despite efforts to streamline access through computerized laboratory results, optimized laboratory turnaround time and integration of final results into the electronic health record remain key challenges. Delays in accessing analysis results issued by the central hospital laboratory are consistently experienced across various laboratory types, indicating broader systemic workflow issues rather than inefficiencies specific to individual laboratories.

Multi-Objective Performance Optimization of Machine Learning Models in Healthcare.

Multi-objective optimization holds particular significance for medical applications, wherein enhancing sensitivity is crucial to avoid costly missed diagnoses, and maintaining high specificity is imperative to prevent unnecessary procedures. In particular, when optimizing machine learning architectures for clinical diagnostics, it becomes essential to balance target quality measures such as accuracy, sensitivity, and specificity. Therefore, we developed MOOF, a multi-objective optimization framework that employs NSGA-II and TOPSIS to simultaneously optimize the model parameters of three selected ML algorithms: random forest, support vector machine, and multilayer perceptron. Finally, we evaluated the performance of the optimized MOOF models compared to gold standard methods such as multi-score grid search and single objective optimizations. Our results show that MOOF generally outperforms other approaches by inherently providing optimal solutions, representing the trade-offs between the target objectives. In conclusion, the study supports the importance of multi-objective optimization in medical informatics, with MOOF as a powerful tool for precise ML models, potentially improving patient care and clinical decision support systems.

Nurses' Perspectives Regarding Challenges of Providing Perinatal/Neonatal End-of-Life Care in a Regional Hospital: An Exploratory Qualitative Study.

This qualitative study aimed to explore nurses' perspectives regarding the challenges of providing perinatal/neonatal end-of-life care in a regional hospital. This exploratory qualitative study was conducted with 20 nurses working in Turkey. Study data were collected through in-depth and semi-structured individual interviews. The interviews were then submitted to thematic analysis. Three themes emerged from analyses of the interviews: (1) inadequate support for delivery of palliative care, (2) perceptions of family readiness, and (3) providing information/education to the family. The most prominent difficulties experienced by nurses were inadequacy of unit and equipment and lack of trained personnel. Another important issue that stood out was families' not accepting the end-of-life care decision for the fetus or the neonate and their having unrealistic expectations. Study results have provided important considerations for regional isolated neonatal and perinatal units, and they will be used to inform clinical practice improvements, staff education support, policies/procedures, family support, and further research relating to end-of-life care provision for the most vulnerable babies and their families.

Exploring Pediatric Vertebral, Sacral, and Pelvic Osteosarcomas through the NCDB: Demographics, Treatment Utilization, and Survival Outcomes.

Retrieve data from the National Cancer Database (NCDB) to examine information on the epidemiological prevalence, treatment strategies, and survival outcomes of pediatric vertebral, sacral and pelvic osteosarcomas. We reviewed NCDB data from 2008 to 2018, concentrating on vertebral, sacral, and pelvic osteosarcomas in children 0 to 21 years. Our analysis involved logistic and Poisson regression, Kaplan-Meier survival estimates, and Cox proportional hazards models. The study population included 207 patients. For vertebral osteosarcomas, 62.5% of patients were female, and 78.1% were white. Regional lymph node involvement predicted 80 times higher mortality hazard (p = 0.021). Distant metastasis predicted 25 times higher mortality hazard (p = 0.027). For sacral and pelvic osteosarcomas, 58.3% of patients were male, and 72% were white. Patients with residual tumor were 4 times more likely to have prolonged LOS (p = 0.031). No residual tumor (HR = 0.53, p = 0.03) and radiotherapy receipt (HR = 0.46, p = 0.034) were associated with lower mortality hazards. Distant metastasis predicted 3 times higher mortality hazard (p < 0.001). Hispanic ethnicity was linked to lower resection odds (OR = 0.342, p = 0.043), possibly due to language barriers affecting patient understanding and care decisions. In conclusion, our examination of NCDB offers a thorough exploration of demographics, treatment patterns, and results, highlighting the importance of personalized approaches to enhance patient outcomes.

Through the eyes of Spanish-speaking patients, caregivers, and community leaders: a qualitative study on the in-patient hospital experience

BackgroundSpanish-speakers with non-English language preference and complex medical needs suffer disparities in quality of care, safety, and health outcomes. Communication challenges during prolonged hospitalizations for complex illnesses negatively influence how this group engages in their care and decision-making while hospitalized. Limited literature capturing the perspectives of Spanish-speaking patients in this context exists. Given the impact of language barriers on care and medical decision-making, this study documents the experiences of Spanish-speaking patients with NELP and hospitalized with complex care needs as well as caregivers and community leaders.MethodsUsing community-engaged recruitment strategies and semi-structured interviews and a focus group, we gathered insights from Spanish-speaking patients hospitalized for prolonged periods, caregivers, and community leaders from three geographic regions. Data were deidentified, transcribed, translated, coded in duplicate, and analyzed guided by grounded theory using NVivo.ResultsWe interviewed 40 participants: 27 patients, 10 caregivers and 3 community leaders. We identified four major themes: (1) Disconnected experiences impeding interactions, communication, and decision-making (2) Inadequate interpreter services (3) Benefits and consequences of family at the bedside (4) Community -informed recommendations.ConclusionThe study showed that in-person interpreters were preferred to virtual interpreters; yet interpreter access was suboptimal. This resulted in ad hoc family interpretation. Participants noted language negatively impacted patient’s hospital experience, including decreasing confidence in medical decision-making. Recommendations from patients, caregivers, and community leaders included expanding interpreter access, bolstering interpreter quality and accuracy, and increasing resources for patient education.

Bedside Magnetocardiography with a Scalar Sensor Array.

Decades of research have shown that magnetocardiography (MCG) has the potential to improve cardiac care decisions. However, sensor and system limitations have prevented its widespread adoption in clinical practice. We report an MCG system built around an array of scalar, optically pumped magnetometers (OPMs) that effectively rejects ambient magnetic interference without magnetic shielding. We successfully used this system, in conjunction with custom hardware and noise rejection algorithms, to record magneto-cardiograms and functional magnetic field maps from 30 volunteers in a regular downtown office environment. This demonstrates the technical feasibility of deploying our device architecture at the point-of-care, a key step in making MCG usable in real-world settings.

Managing hypertension in rural Gambia and Kenya: Protocol for a qualitative study exploring the experiences of patients, health care workers, and decision-makers

Background Hypertension is the single leading risk factor for premature death in Sub-Saharan Africa (SSA). Prevalence is high, but awareness, treatment, and control are low. Community-centred interventions show promise for effective hypertension management, but embedding such interventions sustainably requires a good understanding of the wider context within which they are being introduced. This study aims to conduct a systematic health system assessment exploring the micro (patients/carers), meso (health care workers and facilities), and macro (broader system) contexts in rural Gambia and Kenya. Methods This study will utilise various qualitative approaches. We will conduct (i) focus group discussions with people living with hypertensive to map a ‘typical’ patient journey through health systems, and (ii) in-depth interviews with patients and family carers, health care workers, decision-makers, and NCD partners to explore their experiences of managing hypertension and assess the capacity and readiness of the health systems to strengthen hypertension management. We will also review national guidelines and policy documents to map the organisation of services and guidance on hypertension management. We will use thematic analysis to analyse data, guided by the cumulative complexity model, and theories of organisational readiness and dissemination of innovations. Expected findings This study will describe the current context for the management of hypertension from the perspective of those involved in seeking (patients), delivering (health care workers) and overseeing (decision-makers) health services in rural Gambia and Kenya. It will juxtapose what should be happening according to health system guidance and what is happening in practice, drawing on the experiences of study participants. It will outline the various barriers to and facilitators of hypertension management, as perceived by patients, providers, and decision-makers, and the conditions that would need to be in place for effective and sustainable implementation of a community-centred intervention to improve the management of hypertension in rural settings.

Shared decision-making in maternity care in Saudi Arabia: A cross-sectional study

BackgroundShared decision-making (SDM) in maternity care involves women actively in decisions, thereby reducing decisional conflicts and enhancing satisfaction with care. AimTo investigate SDM and the factors associated with it, and its correlation with respect in maternity care in Saudi Arabia. MethodsA comprehensive, nationwide online questionnaire-based study was conducted between January to May 2023, involving women aged 18 years and above who were either pregnant or had experienced pregnancy/childbirth in the past 12 months. The Mothers’ Autonomy in Decision-Making (MADM) scale and the Mothers of Respect Index (MORi) were used. Low to very low SDM was defined as a score of ≤ 24 on the MADM and low to very low respected was defined as a score of ≤ 49 on the MORi. ResultsA total of 505 women completed the survey. Low to very low SDM was reported by 137 (34.1 %, 95 confidence interval (CI), 29.6 % - 38.9 %) women. Factors significantly associated with low to very low SDM included seeing different obstetricians of different gender at each visit (adjusted odds ratio (AOR) 2.0, 95 % CI, 1.0 – 3.9), not meeting the same obstetrician throughout the pregnancy (AOR 2.6, 95 % CI, 1.2 – 5.6) and having an instrumental vaginal birth (AOR 6.67, 95 % CI, 1.6 - 28.1). There was a positive association between low to very SDM and feeling of low to very low respect ((χ2 = 83.8173, p < 0.001). ConclusionMore than one-third of women experienced low to very low SDM in maternity care. This should alert healthcare providers to the importance of continuity of care in Saudi Arabia.

Therapeutic Obstinacy in End-of-Life Care-A Perspective of Healthcare Professionals from Romania.

End-of-life care raises ethical, moral, legal and economic dilemmas, especially when physicians have to decide whether to initiate or to stop treatments that may be considered disproportionate and futile. To explore the opinion of health care professionals involved in end-of-life patient care on interventions considered disproportionate and futile at this stage of care, the causes and factors of pressure leading to such situations, and possible solutions to reduce the phenomenon. The study used an adapted, designed questionnaire intended for health professionals caring for patients at the end of life. The 128 respondents were physicians, nurses, psychologists and social workers who expressed their opinions about therapeutic obstinacy in end-of-life care. The results of the research highlight the role of the family as a pressure factor, the causes related to the non-acceptance of the prognosis and diagnosis of a terminal condition, fear of death and ignorance of the patient's wishes. Interventions considered disproportionate at the end of life were cardiopulmonary resuscitation, mechanical ventilation, transfusion of blood derivatives, complex diagnostic investigations and the establishment of gastrostomy/jejunostomy in the last days of life. End-of-life therapeutic obstinacy is a reality in end-of-life care, and healthcare professionals face many ethical challenges in this process. Care decisions must be made together with the patient and their family, respecting the rights, dignity and respect of all parties involved in the process.

Predicting prognostic factors in kidney transplantation using a machine learning approach to enhance outcome predictions: a retrospective cohort study.

Accurate forecasting of clinical outcomes after kidney transplantation is essential for improving patient care and increasing the success rates of transplants. Our study employs advanced machine learning (ML) algorithms to identify crucial prognostic indicators for kidney transplantation. By analyzing complex datasets with ML models, we aim to enhance prediction accuracy and provide valuable insights to support clinical decision-making. Analyzing data from 4077 KT patients (June 1990 - May 2015) at a single center, this research included 27 features encompassing recipient/donor traits and peri-transplant data. The dataset was divided into training (80%) and testing (20%) sets. Four ML models-eXtreme Gradient Boosting (XGBoost), Feedforward Neural Network, Logistic Regression, and Support Vector Machine-were trained on carefully selected features to predict the success of graft survival. Performance was assessed by precision, sensitivity, F1 score, Area Under the Receiver Operating Characteristic (AUROC), and Area Under the Precision-Recall Curve. XGBoost emerged as the best model, with an AUROC of 0.828, identifying key survival predictors like T-cell flow crossmatch positivity, creatinine levels two years post-transplant and human leukocyte antigen mismatch. The study also examined the prognostic importance of histological features identified by the Banff criteria for renal biopsy, emphasizing the significance of intimal arteritis, interstitial inflammation, and chronic glomerulopathy. The study developed ML models that pinpoint clinical factors crucial for KT graft survival, aiding clinicians in making informed post-transplant care decisions. Incorporating these findings with the Banff classification could improve renal pathology diagnosis and treatment, offering a data-driven approach to prioritizing pathology scores.

Pediatric Assent in Clinical Practice: A Critical Scoping Review

Background This study assesses how pediatric assent is conceptualized and justified within the therapeutic context. Pediatric ethicists generally agree that children should participate in medical care decisions in developmentally appropriate ways. Much attention has been paid to pediatric assent for research participation, but ambiguities persist in how assent is conceptualized and operationalized in the therapeutic context where countervailing considerations such as the child’s best interest and parental permission must also be weighed. Methods Searches were conducted in 11 databases including PubMed, Embase, Cochrane Library, and Web of Science. Articles published between 2010 and 2020 were screened in COVIDENCE for meeting each of four criteria: (1) focusing on pediatric assent, (2) focusing on clinical care, (3) including normative claims, and (4) containing substantive statements about the meaning of pediatric assent. Full texts were abstracted for (1) operational definitions of assent, (2) discussion of the temporal nature of assent, (3) description of the concept of “understanding,” and (4) ethical justifications for soliciting assent. These excerpts were coded and code patterns formed themes presented in the results. Results The final analytic data set contained 29 articles. Analysis yielded three key themes. First, valid assent varies by treatment, population (e.g., younger versus older), and geographic/cultural context. Second, assent represents two distinct longitudinal processes: One involves eliciting preferences over a disease course or care episode; the other focuses on children’s developmental maturation. Third, ethical justifications for assent draw variously on instrumental and intrinsic reasons, but often remain ambiguous. Conclusions There is widespread agreement that assent is morally valuable, but there remain substantial ambiguities or disagreements about its meaning, process, and ethical justification.

“How long is life worth living for the horse?” A focus group study on how Austrian equine stakeholders assess quality of life for chronically ill or old horses

BackgroundQuality of life (QoL) provides a comprehensive concept underpinning veterinary decision-making that encompasses factors beyond physical health. It becomes particularly pertinent when seeking responsible choices for chronically ill or old horses that emphasise their well-being and a good QoL over the extension of life. How different stakeholders use the concept of QoL is highly relevant when considering the complexity of these decisions in real-life situations.MethodsSeven focus group discussions (N = 39) were conducted to gain insights into how stakeholders assess and use equine QoL in veterinary care decisions for chronically ill and/or old horses. The discussions included horse owners (n = 17), equine veterinarians (n = 7), veterinary officers (n = 6), farriers (n = 4), and horse caregivers (n = 5). The combination of deductive and inductive qualitative content analysis of the group discussions focused on identifying both similarities and differences in the views of these groups regarding QoL for old and/or chronically ill horses.ResultsFindings show agreement about two issues: the importance of the individuality of the horse for assessing QoL and the relevance of QoL in making decisions about veterinary interventions. We identified differences between the groups with respect to three issues: the time required to assess QoL, stakeholders’ contributions to QoL assessments, and challenges resulting from those contributions. While owners and caregivers of horses emphasised their knowledge of a horse and the relevance of the time they spend with their horse, the veterinarians in the study focused on the differences between their own QoL assessments and those of horse owners. In response to challenges regarding QoL assessments and decision-making, stakeholders described different strategies such as drawing comparisons to human experiences.ConclusionsDifferences between stakeholders regarding equine QoL assessments contribute to challenges when making decisions about the care of chronically ill or old horses. The results of this study suggest that individual and collaborative reflection about a horse’s QoL should be encouraged, for example by developing practicable QoL assessment tools that support relevant stakeholders in this process.

Augmenting intensive care unit nursing practice with generative AI: A formative study of diagnostic synergies using simulation-based clinical cases.

As generative artificial intelligence (GenAI) tools continue advancing, rigorous evaluations are needed to understand their capabilities relative to experienced clinicians and nurses. The aim of this study was to objectively compare the diagnostic accuracy and response formats of ICU nurses versus various GenAI models, with a qualitative interpretation of the quantitative results. This formative study utilized four written clinical scenarios representative of real ICU patient cases to simulate diagnostic challenges. The scenarios were developed by expert nurses and underwent validation against current literature. Seventy-four ICU nurses participated in a simulation-based assessment involving four written clinical scenarios. Simultaneously, we asked ChatGPT-4 and Claude-2.0 to provide initial assessments and treatment recommendations for the same scenarios. The responses from ChatGPT-4 and Claude-2.0 were then scored by certified ICU nurses for accuracy, completeness and response. Nurses consistently achieved higher diagnostic accuracy than AI across open-ended scenarios, though certain models matched or exceeded human performance on standardized cases. Reaction times also diverged substantially. Qualitative response format differences emerged such as concision versus verbosity. Variations in GenAI models system performance across cases highlighted generalizability challenges. While GenAI demonstrated valuable skills, experienced nurses outperformed in open-ended domains requiring holistic judgement. Continued development to strengthen generalized decision-making abilities is warranted before autonomous clinical integration. Response format interfaces should consider leveraging distinct strengths. Rigorous mixed methods research involving diverse stakeholders can help iteratively inform safe, beneficial human-GenAI partnerships centred on experience-guided care augmentation. This mixed-methods simulation study provides formative insights into optimizing collaborative models of GenAI and nursing knowledge to support patient assessment and decision-making in intensive care. The findings can help guide development of explainable GenAI decision support tailored for critical care environments. Patients or public were not involved in the design and implementation of the study or the analysis and interpretation of the data.