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Assessing Circumstances and Offering Resources for Needs (ACORN) is a US Department of Veterans Affairs (VA) clinical intervention designed to identify and address social needs to improve health and well-being among all veterans. We co-designed the ACORN Dashboard to facilitate access to real-time social needs and intervention data for VA clinical care teams and leadership. This study aimed to (1) describe the iterative development of the ACORN Dashboard, (2) assess end user feedback and Dashboard usage, and (3) discuss the role of social needs dashboards in facilitating continuous quality improvement in health care settings. An interprofessional team of subject-matter experts and end user feedback contributed to the design. Phase 1 included more than 7 months of weekly working meetings. We initially constructed a wireframe in Microsoft PowerPoint, then translated it into a prototype in Power BI, a data visualization software. Using Microsoft Power BI, we built data visualizations to communicate population-level sociodemographic and ACORN screening data. Through feedback sessions, staff from 8 VA medical centers (VAMCs) reviewed the prototype and recommended improvements regarding the Dashboard's purpose, content, and usability. Phase 2 involved 6 weeks of weekly working meetings, where we developed and iteratively refined 5 written drafts of clinically relevant variables for potential inclusion in the Patient-Level Data Page. This list informed a Power BI prototype. We also developed the ACORN Implementation Map page in Power BI to display implementation locations and settings. We again used feedback sessions with 8 VAMCs to review and refine the newly added pages and discuss improvements. To assess usage, we obtained metadata from a VA-specific Power BI report and user experience data from an ACORN VAMC survey. The ACORN Dashboard displays national data that are updated daily, reflecting 83,546 screens administered across 82 VAMCs facilities between July 1, 2021, and April 30, 2025. The Dashboard was viewed 18,192 times by 2251 unique users, and, on average, 263 (SD 91.2) unique users viewed the Dashboard every month between October 1, 2023, and April 30, 2025. Dashboard variables include the number of screens completed, sociodemographic characteristics of veterans screened, prevalence of social needs, and interventions provided to address needs. Phase 1 semistructured feedback sessions included recommendations for a page with patient-level data to supplement the population-level pages, incorporation of additional filters to select specific data, and development of a user guide. In phase 2, key insights included enhancement of end users' ability to search by veteran or staff name, guidance about screening frequency, changing the display order of variables, and the inclusion of variable definitions. Using co-design to develop, maintain, and continually refine data dashboards enhances implementation of social screening and interventions in health care settings. In addition to supporting individual-level patient care, population-level dashboard data inform continuous quality improvement, promote health equity, and identify gaps in services to address identified needs.

Aims/Introduction This study aimed to evaluate and compare the effectiveness of oral semaglutide after adding to or switching from incretin‐related drugs by assessing the changes in HbA1c and body weight (BW) in participants with type 2 diabetes in clinical settings. Materials and Methods A total of 368 participants were divided into groups according to antidiabetic medications before oral semaglutide treatment; incretin‐related drug‐naïve (naïve), switching from dipeptidyl peptide‐4 inhibitors (DPP‐4i) or glucagon‐like peptide‐1 receptor agonist (GLP‐1 RA) groups. Adjusted mean changes in HbA1c and BW at 6 months after oral semaglutide administration were compared among the three groups. Similar analyses were performed in the GLP‐1 RAs group between GLP‐1RAs before switching. Results Mean change of HbA1c in DPP‐4i and GLP‐1 RA groups was −0.67% (95% confidence interval [CI]: −0.79 to −0.54) and −0.13% (95% CI: −0.40 to 0.15), respectively, which were significantly smaller than incretin‐related drug‐naïve group; −0.85% (95% CI: −1.08 to −0.62). Mean change in BW between the naïve and DPP‐4i groups had no differences; however, these changes were lower in the GLP‐1 RA group than in the naïve group. Mean change in HbA1c between pretreatment with GLP‐1 RAs had no differences; however, the mean change in BW in the dulaglutide group was significantly higher than that in the injectable semaglutide group. Conclusion Oral semaglutide reduced HbA1c levels and BW after adding or switching from other incretin‐related drugs in Japanese participants with type 2 diabetes. Oral semaglutide reduced HbA1c levels and BW after adding or switching from other incretin‐related drugs in Japanese participants with type 2 diabetes. Oral semaglutide had effects on HbA1c and BW similar to that of injectable GLP‐1 RAs.

This study was conducted to develop and validate an instrument to measure the medical professionalism climate in clinical settings. The item pool was developed based on the Tehran University of Medical Sciences Guideline for Professional Conduct. The items were distributed between two questionnaires, one for health-care providers and the other for patients. To assess the construct validity of the questionnaires, 350 health-care providers and 88 patients were enrolled in the study. The reliability of the questionnaires was evaluated by calculating Cronbach’s alpha and ICC. At first a 74-item pool was generated. After assessing and confirming face and content validity, 41 items remained in the final version of the scale. Exploratory factor analysis revealed the three factors of “personal behavior”, “collegiality” and “respect for patient autonomy” in a 25-item questionnaire for service providers and a single factor of “professional behavior” in a 6-item questionnaire for patients. The three factors explained 51.775% of the variance for service providers’ questionnaire and the single factor explained 63.9% of the variance for patients’ questionnaire. The findings demonstrated that from the viewpoints of patients and service providers, this instrument could be applied to assess the medical professionalism climate in hospital clinical settings.  

Aims/Introduction To evaluate and compare the efficacy of insulin degludec (IDeg) and insulin glargine 300 U/mL (Gla300) 6 months after switching from other basal insulins by assessing the changes in glycated hemoglobin (HbA1c), body mass index (BMI), and insulin doses in patients with type 1 and type 2 diabetes in a real‐world clinical setting. Materials and Methods A total of 307 patients with type 1 diabetes and 294 patients with type 2 diabetes with HbA1c >7.0% were studied. Adjusted mean changes in HbA1c, BMI, and insulin doses were compared between IDeg (IDeg group) and Gla300 (Gla300 group) switchers. Multivariable logistic regression analyses were carried out to examine whether the IDeg or Gla300 group was associated with HbA1c or insulin dose reduction and BMI gain. Results HbA1c was significantly decreased in both the IDeg and Gla300 groups. Adjusted mean changes in HbA1c (approximately −0.3% and −0.5% in type 1 diabetes and type 2 diabetes patients, respectively) and BMI were similar between both groups. The mean change in insulin dose was slightly larger for dose reduction in the IDeg group than in the Gla300 group. Multivariable logistic regression models showed that the IDeg group was significantly associated with insulin dose reduction after adjusting for basal insulin type, insulin dose, and number of basal insulin injections at baseline and other confounding factors. Conclusions The current study suggested that IDeg and Gla300 have similar effects in reducing HbA1c and gaining BMI after switching from other basal insulins in Japanese patients with type 1 diabetes and type 2 diabetes. IDeg selection was associated with insulin dose reduction. Insulin degludec and insulin glargine 300 U/mL showed similar values of reduction in glycated hemoglobin with body mass index almost unchanged 6 months after switching from other basal insulins in both type 1 and type 2 diabetes patients. Switching to insulin degludec was significantly associated with a reduction of basal and total insulin doses in both type 1 and type 2 diabetes patients.

Professional behavior with patients and interactions with colleagues, the institution and professional bodies are influenced by many factors. The purpose of this manuscript is to clarify those personal factors affecting medical professionalism in clinical settings affiliated with Tehran University of Medical Sciences. For this purpose, a qualitative study was carried out. One hundred and eighty-two participants were recruited through purposive sampling of clinical staff, physicians, and medical students in Tehran. Data were collected through 22 focus group discussions, and conventional content analysis was used to analyze the data.  The results were reported in five categories to present the participants’ views. Categories were extracted from 103 codes and consisted of 1) people's belief in professionalism, 2) personality traits, 3) problems in family, 4) mental or physical health status, and 5) communication skills. The results showed that despite the facilitator roles of some personal factors, others act as barriers to professional behaviors. In order to control their impact, it is crucial to pay attention to them at the time of student/staff selection. Strengthening support systems in the organization is also essential for decreasing the effect of family problems or physical and mental health problems.

Sex-related differences have been shown to deeply affect health-related aspects of patients. However, the lack of gender-specific analysis makes it difficult to advance personalized medicine in terms of a gender-based approach. The aim of the present study was to describe gender-specific features of patients diagnosed with heart failure (HF), with a focus on the clinical presentation. Data were collected from a properly designed database and referred to an Italian hospital. Patients aged ≥18 years with a primary or secondary diagnosis of HF between 1 January 2012 and 31 December 2016 were included, and their demographic and clinical characteristics were analyzed according to gender. Of the 719 HF patients included, 317 (44.1%) were male and 402 (55.9%) were female. Women tended to be older compared to men (82.4±8.8 years and 77.1±10.6 years, respectively). As for clinical presentation, 62.1% of female and 38.3% of male patients had preserved ejection fraction, and 56.1% of men and 58.2% of women suffered from atrial fibrillation. The left atrium was partially compromised in 62.4% of male and 63% of female patients, while right atrium dysfunction tended to be more frequent in male patients compared to female patients (29.1% and 25.5%, respectively). In conclusion, gender-specific features of a cohort of HF patients from a clinical setting were accurately described.

Up to 50% of antibiotic prescriptions for upper respiratory infections (URIs) are inappropriate. Clinical decision support (CDS) systems to mitigate unnecessary antibiotic prescriptions have been implemented into electronic health records, but their use by providers has been limited. As a delegation protocol, we adapted a validated electronic health record-integrated clinical prediction rule (iCPR) CDS-based intervention for registered nurses (RNs), consisting of triage to identify patients with low-acuity URI followed by CDS-guided RN visits. It was implemented in February 2022 as a randomized controlled stepped-wedge trial in 43 primary and urgent care practices within 4 academic health systems in New York, Wisconsin, and Utah. While issues were pragmatically addressed as they arose, a systematic assessment of the barriers to implementation is needed to better understand and address these barriers. We performed a retrospective case study, collecting quantitative and qualitative data regarding clinical workflows and triage-template use from expert interviews, study surveys, routine check-ins with practice personnel, and chart reviews over the first year of implementation of the iCPR intervention. Guided by the updated CFIR (Consolidated Framework for Implementation Research), we characterized the initial barriers to implementing a URI iCPR intervention for RNs in ambulatory care. CFIR constructs were coded as missing, neutral, weak, or strong implementation factors. Barriers were identified within all implementation domains. The strongest barriers were found in the outer setting, with those factors trickling down to impact the inner setting. Local conditions driven by COVID-19 served as one of the strongest barriers, impacting attitudes among practice staff and ultimately contributing to a work infrastructure characterized by staff changes, RN shortages and turnover, and competing responsibilities. Policies and laws regarding scope of practice of RNs varied by state and institutional application of those laws, with some allowing more clinical autonomy for RNs. This necessitated different study procedures at each study site to meet practice requirements, increasing innovation complexity. Similarly, institutional policies led to varying levels of compatibility with existing triage, rooming, and documentation workflows. These workflow conflicts were compounded by limited available resources, as well as an implementation climate of optional participation, few participation incentives, and thus low relative priority compared to other clinical duties. Both between and within health care systems, significant variability existed in workflows for patient intake and triage. Even in a relatively straightforward clinical workflow, workflow and cultural differences appreciably impacted intervention adoption. Takeaways from this study can be applied to other RN delegation protocol implementations of new and innovative CDS tools within existing workflows to support integration and improve uptake. When implementing a system-wide clinical care intervention, considerations must be made for variability in culture and workflows at the state, health system, practice, and individual levels. ClinicalTrials.gov NCT04255303; https://clinicaltrials.gov/ct2/show/NCT04255303.

Background and objectives: Exercise can help ease withdrawal symptoms of smokers. However, there is little information about the physiological responses, such as cardiorespiratory and lactate (La) responses, during exercise from light to moderate intensity combined with transdermal nicotine patches (TNPs) in smokers. This study aimed to investigate the effect of TNPs on the cardiorespiratory and La responses during exercise at light to moderate intensity. Materials and Methods: Fourteen young men (8 non-smokers, 6 current smokers) aged 20 to 26 years participated in this study. They performed an incremental graded submaximal exercise test using an electromagnetic cycle ergometer set from 30 to 210 W with (TNP condition) or without a TNP (control condition) in a random order. The TNP was applied to the left arm 8–10 h prior to starting the exercise to achieve the peak level of blood nicotine concentration. Heart rate (HR), rate of perceived exertion (RPE), oxygen consumption (VO2), ventilation (VE), and blood La at rest and during exercise were measured and analyzed. Results: The HR at rest was significantly higher in the TNP condition than in the control condition (TNP; 74.7 ± 13.8 bpm, control; 65.3 ± 10.8 bpm, p < 0.001). There was no interaction (condition × exercise intensity) between any of the variables, and VO2, VE, RPE, and La during exercise were not significantly different between the conditions. However, HR during exercise was 6.7 bpm higher on average in the TNP condition. Conclusions: The HR during exercise was greater at light to moderate intensity with a TNP. Our study results will guide clinicians or health professionals when prescribing exercise programs combined with TNPs for healthy young smokers.

Importance Large language models (LLMs) like OpenAI’s ChatGPT are powerful generative systems that rapidly synthesize natural language responses. Research on LLMs has revealed their potential and pitfalls, especially in clinical settings. However, the evolving landscape of LLM research in medicine has left several gaps regarding their evaluation, application, and evidence base. Objective This scoping review aims to (1) summarize current research evidence on the accuracy and efficacy of LLMs in medical applications, (2) discuss the ethical, legal, logistical, and socioeconomic implications of LLM use in clinical settings, (3) explore barriers and facilitators to LLM implementation in healthcare, (4) propose a standardized evaluation framework for assessing LLMs’ clinical utility, and (5) identify evidence gaps and propose future research directions for LLMs in clinical applications. Evidence review We screened 4,036 records from MEDLINE, EMBASE, CINAHL, medRxiv, bioRxiv, and arXiv from January 2023 (inception of the search) to June 26, 2023 for English-language papers and analyzed findings from 55 worldwide studies. Quality of evidence was reported based on the Oxford Centre for Evidence-based Medicine recommendations. Findings Our results demonstrate that LLMs show promise in compiling patient notes, assisting patients in navigating the healthcare system, and to some extent, supporting clinical decision-making when combined with human oversight. However, their utilization is limited by biases in training data that may harm patients, the generation of inaccurate but convincing information, and ethical, legal, socioeconomic, and privacy concerns. We also identified a lack of standardized methods for evaluating LLMs’ effectiveness and feasibility. Conclusions and relevance This review thus highlights potential future directions and questions to address these limitations and to further explore LLMs’ potential in enhancing healthcare delivery.

Despite the substantial health and economic burdens posed by the social determinants of health (SDH), these have yet to be efficiently, sufficiently, and sustainably addressed in clinical settings—medical offices, hospitals, and healthcare systems. Our study contextualized SDH application strategies in U.S. clinical settings by exploring the reasons for integration and identifying target patients/conditions, barriers, and recommendations for clinical translation. The foremost reason for integrating SDH in clinical settings was to identify unmet social needs and link patients to community resources, particularly for vulnerable and complex care populations. This was mainly carried out through SDH screening during patient intake to collect individual-level SDH data within the context of chronic medical, mental health, or behavioral conditions. Challenges and opportunities for integration occurred at the educational, practice, and administrative/institutional levels. Gaps remain in incorporating SDH in patient workflows and EHRs for making clinical decisions and predicting health outcomes. Current strategies are largely directed at moderating individual-level social needs versus addressing community-level root causes of health inequities. Obtaining policy, funding, administrative and staff support for integration, applying a systems approach through interprofessional/intersectoral partnerships, and delivering SDH-centered medical school curricula and training are vital in helping individuals and communities achieve their best possible health.