Healthcare Settings Research Articles

Cervical cancer screening rates in females living with HIV at three healthcare settings in the United States, 2010-2019.

Females living with human immunodeficiency virus (FLWHIV) are at increased risk of cervical cancer and U.S. guidelines, first published in 2009 and updated since then, recommend more frequent screening in this population. We examined screening rates among FLWHIV in the U.S. during 2010-2019. This cohort study included 18-89-year-old FLWHIV during 2010-2019 at three U.S. healthcare settings. Sociodemographics, comorbidities, and cervical cancer screening tests were ascertained from administrative and clinical databases. We reported cervical cancer screening rates overall and by modality. Generalized estimating equations with Poisson distribution were used to estimate screening rate ratios (SRRs) and 95% confidence intervals (CIs) for the associations between screening rates and calendar year, age, race and ethnicity, and comorbidity. Among 3,556 FLWHIV, a total of 7,704 cervical cancer screening tests were received over 18,605 person-years during 2010-2019 (screening rate = 41.4 per 100 person-years). Relatively lower screening rates were associated with later calendar years (SRR = 0.71 [95% CI 0.68-0.75] for 2017-2019 versus 2010-2013), older age (SRR = 0.82 [95% CI 0.74-0.89] for 50-65-year-olds versus 18-29-year-olds), non-Hispanic white race versus non-Hispanic Black race (SRR = 0.89 [95% CI 0.81-0.98]) and greater comorbidity burden (SRR = 0.89 [95% CI 0.82-0.98] for ≥ 9 versus 0-6 comorbidity score). The decrease in cervical cancer screening rates during 2010-2019 in this large cohort of FLWHIV may be explained at least partly by guideline changes during the study period recommending longer screening intervals. Our findings of relatively lower screening rates in FLWHIV who were non-Hispanic white, older, and with greater comorbidity burden should be confirmed in other U.S.

Evaluating Factors Affecting Knowledge Sharing Among Health Care Professionals in the Medical Imaging Departments of 2 Cancer Centers: Concurrent Mixed Methods Study.

Knowledge sharing is a crucial part of any knowledge management implementation. It refers to sharing skills and experience among team members in an organization. In a health care setting, sharing knowledge, whether tacit or explicit, is important and can lead to better health care services. In medical imaging departments, knowledge sharing can be of particular importance. There are several factors that affect knowledge-sharing practices in medical imaging departments: individual, departmental, and technological. Evaluating the importance of these factors and understanding their use can help with improving knowledge-sharing practices in medical imaging departments. We aimed to assess the level of motivation, identify current knowledge-sharing tools, and evaluate factors affecting knowledge sharing in the medical imaging departments of 2 cancer centers, The Christie, United Kingdom, and the Kuwait Cancer Control Center (KCCC). A concurrent mixed methods study was conducted through nonprobability sampling techniques between February 1, 2023, and July 30, 2023. Semistructured interviews were used to validate the results of the quantitative analysis. Data were collected using an electronic questionnaire that was distributed among health care professionals in both cancer centers using Qualtrics. Semistructured interviews were conducted online using Microsoft Teams. The quantitative data were analyzed using the Qualtrics MX software to report the results for each question, whereas the qualitative data were analyzed using a thematic approach with codes classified through NVivo. In total, 56 respondents from the KCCC and 29 from The Christie participated, with a 100% response rate (56/56, 100% and 29/29, 100%, respectively) based on the Qualtrics survey tool. A total of 59% (17/29) of health care professionals from The Christie shared their knowledge using emails and face-to-face communication as their main tools on a daily basis, and 57% (32/56) of health care professionals from the KCCC used face-to-face communication for knowledge sharing. The mean Likert-scale score of all the components that assessed the factors that affected knowledge-sharing behaviors fell between "somewhat agree" and "strongly agree" in both centers, excepting extrinsic motivation, which was rated as "neither agree nor disagree." This was similar to the results related to incentives. It was shown that 52% (15/29) of health care professionals at The Christie had no incentives to encourage knowledge-sharing practices. Therefore, establishing clear policies to manage incentives is important to increase knowledge-sharing practices. This study offered an evaluation of factors that affect knowledge sharing in 2 cancer centers. Most health care professionals were aware of the importance of knowledge-sharing practices in enhancing health care services. Several challenges were identified, such as time constraints, a lack of staff, and the language barrier, which limit knowledge-sharing practices. Therefore, establishing a clear policy for knowledge sharing is vital to practicing knowledge-sharing behaviors and facing any challenges that limit this practice.

Cultural Adaptation and Psychometric Properties of the Spanish Version of the Gay Affirmative Practice Scale (GAP-ES)

Background/Objectives: Lesbian, gay, bisexual, and transgender (LGBT) individuals often face discrimination in healthcare settings, resulting in health disparities. Evaluating healthcare professionals’ affirmative practices is essential for promoting inclusive care and addressing these disparities. The aim of this study was to assess the psychometric properties of the Spanish version of the Gay Affirmative Practice Scale (GAP-ES), which measures healthcare professionals’ affirmative practices towards gay individuals. Methods: Before assessing its psychometric properties, the original Gay Affirmative Practice Scale (GAP) was translated and culturally adapted from English to Spanish. Following the translation, the psychometric properties were tested on a sample of 236 healthcare professionals. The internal consistency of the questionnaire was measured using Cronbach’s alpha and the discriminatory power index. Factor structure was evaluated with Confirmatory Factor Analysis (CFA) using the Diagonally Weighted Least Squares method. Results: The sample consisted of 152 female (64.41%) and 84 male (35.59%) participants, with 58.05% identifying as heterosexual, 28.81% as homosexual, and 13.14% as bisexual. The internal consistency of the GAP-ES was strong, with Cronbach’s alpha values of 0.915 for the Beliefs subscale and 0.902 for the Behaviors subscale. The McDonald’s Omega coefficient was 0.942, indicating high reliability. CFA confirmed a two-factor structure with satisfactory fit indices (CFI = 0.999, RMSEA = 0.071). Conclusions: The GAP-ES demonstrates strong internal consistency and a stable factor structure. It is a reliable tool for evaluating affirmative practices toward LGBT patients in Spanish-speaking healthcare contexts, supporting improved care for this population. The integration of the GAP-ES into clinical practice and training programs may support the enhancement of cultural competence among healthcare professionals, contributing to the reduction of health disparities for LGBT patients in Spanish-speaking settings.

Awareness and Knowledge of Hepatitis B Vaccination Among Newly Enrolled First-Year Medical Undergraduates in South India: A Cross-Sectional Survey.

Hepatitis B poses a significant public health risk, particularly for healthcare professionals who face heightened exposure in clinical settings. This study assesses the awareness and knowledge of hepatitis B vaccination among first-year medical undergraduates in their preclinical stage before transitioning to clinical phases. This cross-sectional survey was conducted among newly enrolled first-year medical undergraduate students at a medical college before the commencement of a planned vaccination drive, allowing the institution to assess baseline knowledge and logistical needs for the drive. A self-administered questionnaire was used to evaluate students' awareness and understanding of hepatitis B transmission, vaccination, and the occupational risks associated with healthcare work. The data gathered from this survey provided critical insights for optimizing the logistics and educational components of the upcoming vaccination program for the incoming cohort. Among the 126 respondents, there was a slightly higher representation of male participants (53.17%, n=67), while 46.83% (n=59) were females. Awareness of hepatitis B as a highly contagious liver infection was high, with 88.9% of students agreeing or strongly agreeing. The knowledge that hepatitis B is a public health concern and can lead to severe conditions such as liver cancer was similarly prevalent (97.6% and 90.4%, respectively). Most respondents (80.2%) were aware of the heightened risk for healthcare professionals and viewed vaccination as an effective preventive measure (96.1%). Awareness of transmission routes, including contact with infected blood (96%) and unprotected sexual contact (97.6%), was also strong. However, fewer students were informed about the recommended vaccination schedule (63.4%) or the necessity of booster doses for high-risk individuals (70.6%). Additionally, 93.7% believed healthcare workers should be vaccinated, while 88.9% recognized the need for immunity status checks in healthcare settings. Only 16.66% (n=21) reported receiving the hepatitis B vaccine, with 14.28% having completed the full three-dose series, while 2.38% received only one or two doses. A significant portion (62.69%) reported not being vaccinated, and 20.63% were unsure of their vaccination status. Key reasons for incomplete vaccination included lack of awareness about the full series (58.73%), fear of side effects (6.34%), and perceived lack of necessity (7.93%). Access challenges were also noted by 2.38% of students. Only 1.58% of respondents had checked their immunity status through anti-hepatitis B surface antibody (HBsAb) testing. Newly enrolled medical undergraduates show substantial foundational knowledge of hepatitis B and its prevention. However, targeted educational and peer-led initiatives are recommended to bridge the remaining gaps, ensuring future healthcare professionals have comprehensive knowledge for effective hepatitis B prevention. The findings also underscore the need for improved vaccination awareness and accessibility to achieve comprehensive immunization among medical undergraduates.

Use of Data Augmentation and Fine-tuned Transfer Learning Models for Classification of Cervical Cancer

Innovative strategies for early and accurate diagnosis of cervical cancer continue to be a global health priority. In this research, we present a powerful framework for improving cervical cancer classification by combining data augmentation methods with tailored transfer learning models. The lack of properly labelled medical data is a major roadblock to developing reliable diagnosis models. The geometric transformations, contrast tweaks, and noise addition that we use to increase the dataset artificially help us overcome this difficulty. The model's robustness is improved as a result of the additional exposure to diverse real-world circumstances provided by this supplemented dataset. We use a transfer learning strategy based on pre-trained convolutional neural networks (CNNs) to harness the potential of deep learning. These networks are well-suited for medical image analysis due to their ability to quickly and accurately identify features in a wide variety of images. Our expanded cervical cancer dataset is used to fine-tune these algorithms for their diagnostic purpose. Our experiments show that utilising both data augmentation and fine-tuned transfer learning considerably raises the accuracy of cervical cancer categorization. In terms of sensitivity, specificity, and overall accuracy, the model performs at a state-of-the-art level. This suggests that it may be useful in the diagnosis and early identification of cervical cancer. Additionally, our method demonstrates the significance of efficient data utilisation and model adaptability in the field of medicine. Our method is scalable and affordable, and it can be easily implemented in healthcare settings since we handle the problem of data scarcity and take advantage of the features of pre-trained deep learning models.

Bridging technostress and continuous learning in knowledge-intensive organizations: A socio-technical systems approach for the future of healthy working life

We present an interdisciplinary exploration of technostress in knowledge-intensive organizations, including both business and healthcare settings, and its impact on a healthy working life. Technostress, a contemporary form of stress induced by information and communication technology, is associated with reduced job satisfaction, diminished organizational commitment, and adverse patient care outcomes. This article aims to construct an innovative framework, called The Integrated Technostress Resilience Framework, designed to mitigate technostress and promote continuous learning within dynamic organizational contexts. In this perspective article we incorporate a socio-technical systems approach to emphasize the complex interplay between technological and social factors in organizational settings. The proposed framework is expected to provide valuable insights into the role of transparency in digital technology utilization, with the aim of mitigating technostress. Furthermore, it seeks to extend information systems theory, particularly the Technology Acceptance Model, by offering a more nuanced understanding of technology adoption and use. Our conclusion includes considerations for the design and implementation of information systems aimed at fostering resilience and adaptability in organizations undergoing rapid technological change.

Increased use of Dermoscopy in Primary Healthcare Following the Implementation of Teledermatology in Southeast Sweden: A Retrospective Cohort Study of 2,137 Patients.

In the last 5 decades there has been a steady increase in skin cancer incidence globally. As patients wait for treatment before or after referral, the prognosis for those with melanoma worsens. Teledermatology was introduced to help reduce waiting times. The objective of this study was to investigate how the introduction of teledermatology affected management of skin tumours, from primary care physicians to dermatologists. A retrospective cohort study was performed 1 year before and 1 year after introduction of teledermatology in Östergötland County, Sweden. Patients were included from 3 primary healthcare centres by 3 independent observers. A total of 2,139 patients were included in the study. The 2 cohorts were well matched. At 2 of the 3 primary healthcare centres there was a significant increase in the use of dermoscopy, and almost 66% of all referrals were teledermatological in the year following its introduction. There was a trend towards higher diagnostic accuracy in the post-teledermatology cohort. No apparent effect on melanoma referral times was observed. The results of this study confirm previous findings showing the value of teledermatology as well as a novel finding of an increase in dermoscopy use in primary healthcare settings.

Capacity Planning in Paediatric Palliative and Hospice Care: An Italian Case

Although the growing demand for healthcare services has enhanced the occurrence of inefficiencies in care provision, healthcare systems should ensure safe, timely and equitable access to care. In particular, the long waiting lists, the lack of beds, and the shortage of healthcare workforce have highlighted the necessity to effectively manage and strategically plan the available resources. Capacity Planning (CP) contributes to determine what, when, where and how much product or service to deliver, with the goal of analysing and optimizing the use and allocation of human and material resources (e.g., physical spaces, equipment, beds, workforce) based on the demand. CP demonstrates to be extremely relevant for hospital units to schedule appointments, diagnostics, surgeries and admissions. Complex contexts and broader healthcare networks could benefit even more from this approach, helping to coordinate multiple care providers and aligning the available resources with the demand pace. The current research presents the implementation of CP in the context of Paediatric Palliative and Hospice Care (PPHC), delivered in an Italian facility. PPHC provides long-term, interdisciplinary and coordinated care between territorial, ambulatory and hospice services. It encompasses follow-up activities, parental training, end-of-life and respite care. In the Italian case analysed, the shortage of beds affects the quality of care delivered to these patients, in terms of accessibility to the service, effectiveness and timeliness of care. Hence, a CP analysis has been performed to pursue a twofold objective: a) to understand if the current capacity of the facility meets the demand for care; b) to improve productivity through an optimized allocation of resources, particularly the available beds and the healthcare workforce. The expected results involve a more effective use of resources, an increased bed occupancy rate and a reduction in rescheduled admissions due to inadequate planning. Optimizing capacity in this specific setting can serve as a pilot project for other similar contexts, aiming to improve patients’ access to healthcare services, their quality of life and supporting the workforce involved in PPHC. This research offers new insights from both the academic and managerial point of view, providing evidence about the implementation of CP in complex healthcare settings.

Abstract 4118668: Understanding Medication Adherence to Oral Anticoagulants in Atrial Fibrillation Management: Patient and Provider Perspectives in a Mixed Methods Study

Background: Atrial fibrillation (AF) increases risk of stroke. National guidelines recommend oral anticoagulant (OAC) use to reduce this risk. Medication adherence is pivotal for effective AF management, necessitating an understanding of adherence barriers. Aims: This mixed-methods study aimed to identify patient and provider factors influencing OAC adherence. Methods: Patients with nonvalvular AF and OAC prescriptions were sampled from a large community health system serving seven states. A stratified random sample of 2,000 patients was surveyed by mail, achieving a 13.3% response rate (266 patients). Twenty-eight semi-structured interviews were conducted with a purposive sample of patient survey respondents. Eligible providers were surveyed by email, resulting in a 3% response rate (78 providers). Survey data were analyzed descriptively and using multivariable regression models. Interview data were analyzed thematically. Results: Of 213 patients with an adherence score available, 31.5% reported non-adherence. Nonadherent patients were more likely to report poor healthcare experiences, including discrimination in a healthcare setting and poorer mental/emotional health. Receiving information from providers was significantly associated with adherence, especially among younger patients and those with fewer chronic conditions. High self-efficacy score was associated with adherence, particularly among older and rural patients. Interview analyses showed provider communication about AF medications, perceptions of AF as a serious illness, and a sense that medication was helping manage AF were all important for medication adherence. In contrast, most providers (87%) perceived high non-adherence among AF patients, citing forgetfulness, cost, and side effects as the main reasons. Providers’ responses indicate a need for improving communication and support for addressing adherence barriers. Conclusion: Most patients reported adherence to their medications, with adherence being associated with positive healthcare experiences and better mental/emotional health. Providers perceived relatively low adherence among their patients but aligned with patients on the need for improved communication and shared decision making. Tools that encourage discussion with patients and open communication between providers and patients are pivotal for optimizing patient care and enhancing medication adherence and treatment outcomes.

The Role Of Machine Learning In Transforming Healthcare: A Systematic Review

This systematic review explores the transformative role of machine learning (ML) in healthcare, focusing on its applications in disease diagnosis, personalized medicine, healthcare operations, and patient monitoring. By analyzing 167 peer-reviewed studies published between 2015 and 2024, the review highlights how ML algorithms have significantly improved early disease detection, treatment personalization, and operational efficiencies in healthcare settings. Findings reveal that ML-powered diagnostic tools, especially deep learning models, demonstrate accuracy levels comparable to human experts in areas like cancer detection. Additionally, ML models tailored for personalized medicine have shown promise in optimizing treatment protocols based on genetic profiles, reducing adverse reactions and improving patient outcomes. In healthcare operations, ML applications have streamlined hospital resource management, enhanced workflow efficiency, and reduced administrative burdens through predictive analytics and natural language processing (NLP). Moreover, ML-driven remote patient monitoring systems have enabled proactive interventions for chronic disease management. Despite these advancements, challenges related to data privacy, algorithmic transparency, and regulatory compliance persist. Addressing these barriers is critical for realizing the full potential of ML in healthcare, ensuring ethical deployment and equitable access. The review concludes by emphasizing the need for robust regulatory frameworks and further research to enhance the integration of ML technologies into clinical practice.

Uncovering Linguistic Strategies in Kuwaiti Doctor’s Patient-Directed Communication

The current study explores linguistic strategies used by Kuwaiti Doctors in their interactions with patients. By examining the language used in standard doctor-patient interactions, it provides preliminary insights into the communication practices of Kuwaiti healthcare professionals. Due to practical and ethical considerations, twenty-six family doctors participated in a Discourse Completion Task featuring six different scenarios to identify preferred linguistic strategies. The findings reveal a tendency towards indirect requests and questions indicating obligation or possibility when advising patients. Doctors frequently offered help using inclusive first-person plural 'we' inflections, especially with apprehensive patients. In supportive contexts, multiple communicative functions were often utilized simultaneously. These insights are valuable for linguists and healthcare providers, contributing to cross-cultural and inter-language communication research. The findings also inform subsequent investigations into patient preferences, enriching the understanding of effective communication in healthcare settings in Kuwait.

AI bias in lung cancer radiotherapy

Aim: In lung cancer research, AI has been trained to read chest radiographs, which has led to improved health outcomes. However, the use of AI in healthcare settings is not without its own set of drawbacks, with bias being primary among them. This study seeks to investigate AI bias in diagnosing and treating lung cancer patients. The research objectives of this study are threefold: 1) To determine which features of patient datasets are most susceptible to AI bias; 2) to then measure the extent of such bias; and 3) from the findings generated, offer recommendations for overcoming the pitfalls of AI in lung cancer therapy for the delivery of more accurate and equitable healthcare. Methods: We created a synthetic database consisting of 50 lung cancer patients using a large language model (LLM). We then used a logistic regression model to detect bias in AI-informed treatment plans. Results: The empirical results from our synthetic patient data illustrate AI bias along the lines of (1) patient demographics (specifically, age) and (2) disease classification/histology. As it concerns patient age, the model exhibited an accuracy rate of 82.7% for patients < 60 years compared to 85.7% for patients ≥ 60 years. Regarding disease type, the model was less adept in identifying treatment categories for adenocarcinoma (accuracy rate: 83.7%) than it was in predicting treatment categories for squamous cell carcinoma (accuracy rate: 92.3%). Conclusions: We address the implications of such results in terms of how they may exacerbate existing health disparities for certain patient populations. We conclude by outlining several strategies for addressing AI bias, including generating a more robust training dataset, developing software tools to detect bias, making the model’s code open access and soliciting user feedback, inviting oversight from an ethics review board, and augmenting patient datasets by synthesizing the underrepresented data.

Cost-effectiveness of midomafetamine-assisted therapy (MDMA-AT) in chronic and treatment-resistant post-traumatic stress disorder of moderate or higher severity: A health-economic model.

To explore the cost-effectiveness of midomafetamine-assisted therapy (MDMA-AT) compared to placebo with therapy (PT) in US healthcare settings. A health state-transition model was used to analyze the cost-effectiveness of MDMA-AT for treating patients with chronic PTSD of moderate or higher severity. Both treatment arms consisted of 3 preparation (90-min), 3 interventional (8-h), and 9 integration (90-min) sessions, lasting ~4 months total. All sessions included psychotherapy, with interventional also including MDMA or placebo. After receiving treatment, patients were distributed across health states of No PTSD (not meeting PTSD diagnostic criteria), Non-Severe PTSD (treatment responders), Severe PTSD (treatment non-responders), and death. Each state had unique healthcare costs and utilities sourced from real-world data analysis and patient data from MDMA-AT clinical trials (including long-term follow-up). The base-case analysis considered the payer's perspective with a 5-year horizon, 3.5% annual cost and effect discounts, and an assumed MDMA medication price of $12,000 per session. Trial-derived utilities and US life tables mortality data were used to calculate quality-adjusted life years (QALY). The main outcome was an incremental cost-effectiveness ratio (ICER) with a $150,000 willingness-to-pay (WTP) threshold. The base-case ICER was $83,845 per QALY. Total direct costs were $64,745 in the MDMA-AT and $33,132 in the PT arms ($31,613 increment). The costs of intervention were $48,376 for MDMA-AT and $12,376 for PT. The highest MDMA medication cost to fit under the WTP threshold was $20,314 per session. Costs related to PTSD healthcare visits and other PTSD treatments were lower with MDMA-AT than PT (-$2,511 and -$1,877 increments, respectively). Utility benefits were higher in MDMA-AT than PT, with 3.691 and 3.314 QALYs generated over 5 years, respectively (0.377 QALY increment). These data suggest MDMA-AT may be a cost-effective treatment compared to PT for patients with chronic PTSD of moderate or higher severity.

The Role of Arts in Health Program Evaluation

Arts-based interventions are gaining recognition for their potential to enhance health outcomes, reduce stigma, and improve the well-being of individuals and communities. As such programs proliferate across healthcare settings, from hospitals to senior centers, the need for rigorous evaluation frameworks becomes essential to assess their effectiveness. This paper examines the intersection of arts and health programs, examining their contribution to physical, emotional, and mental well-being. It emphasizes the importance of evaluation in validating these interventions, outlines key components of arts program evaluation, and highlights methods for assessing impact, including mixed-method approaches. The aim is to provide a comprehensive guide for evaluating arts in health programs, ensuring their sustained integration into healthcare practices. Keywords: Arts in health, Health program evaluation, Mental health, Community well-being, Mixed-methods evaluation, Arts-based interventions.

Panchakarma fitness form for clinical practice and research in Ayurveda

Background: The Panchakarma Fitness Form is an essential tool in Ayurveda, used to assess a patient’s suitability for specific Panchakarma treatments. By evaluating Dashavidha Pareeksha, Sama-Nirama Pareeksha, assessment of Agni, assessment of Koshta, examination of vital parameters, medical history, and other relevant factors, this form ensures that treatment decisions are informed, ethical, and patient-centered. Objectives: To develop and implement a Panchakarma Fitness Form for evaluating patient fitness for Panchakarma therapies and to assess its effectiveness in enhancing treatment safety, personalization, and compliance with clinical and ethical standards over a five-year period. Methods: A comprehensive Panchakarma Fitness Form was designed, incorporating sections on classical advocation on fitness for different Panchakarma therapies, medical history, clinical examination of patient, allergies, medication, and lifestyle factors. The form was used in both routine healthcare and clinical research settings, with a particular emphasis on its role in screening for study eligibility. The implementation of the Panchakarma Fitness Form enhanced patient safety by identifying contraindications and optimizing treatment decisions. This form contributed to improved treatment efficacy by tailoring therapies to individual health conditions and supporting personalized care. In clinical research settings, the form facilitated participant selection, improving study integrity and data reliability. Conclusions: The Panchakarma Fitness Form is a valuable tool that supports safe, effective, and personalized Ayurvedic treatment. By systematically assessing patient readiness, it reduces risks, enhances treatment outcomes, and aids in legal and ethical compliance in both clinical practice and research. This form sets a standard for quality and safety in Ayurveda, supporting patient-centered and informed healthcare.

We Are on the Verge of Breakthrough Cures for Type 1 Diabetes, but Who Are the 2 Million Americans Who Have It?

Background: Two million Americans have type 1 diabetes (T1DM). Innovative treatments have standardized insulin delivery and improved outcomes for patients, but patients’ access to such technologies depends on social determinants of health, including insurance coverage, proper diagnosis, and appropriate patient supports. Prior estimates of US prevalence, incidence, and patient characteristics have relied on data from select regions and younger ages and miss important determinants. Objectives: This study sought to use large, nationally representative healthcare claims data sets to holistically estimate the size of the current US population with T1DM and investigate geographic nuances in prevalence and incidence, patient demographics, insurance coverage, and device use. This work also aimed to project T1DM population growth over the next 10 years. Methods: We used administrative claims from 4 sources to identify prevalent and incident T1DM patients in the US, as well as various demographic and insurance characteristics of the patient population. We combined this data with information from national population growth projections and literature to construct an actuarial model to project growth of the T1DM population based on current trends and scenarios for 2024, 2029, and 2033. Results: We estimated 2.07 million T1DM patients nationally across all insurance coverages in our 2024 baseline model year: 1.79 million adults (≥20 years) and 0.28 million children. This represents a US T1DM prevalence rate of 617 per 100 000 and an incidence rate of 0.016%. By 2033, we project the US population with T1DM will grow by about 10%, reaching approximately 2.29 million patients. Discussion: Our results showed important differences in T1DM prevalence and incidence across regions, payers, and ethnic groups. This suggests studies based on more geographically concentrated data may miss important variation in prevalence and incidence across regions. It also indicates T1DM prevalence tends to vary by income, consistent with several international studies. Conclusions: Accurate projections of T1DM population growth are critical to ensure appropriate healthcare coverage and reimbursement for treatments. Our work supports future policy and research efforts with 2024, 2029, and 2033 projections of demographics and insurance coverage for people with T1DM.

We Are on the Verge of Breakthrough Cures for Type 1 Diabetes, but Who Are the 2 Million Americans Who Have It?

Background: Two million Americans have type 1 diabetes (T1DM). Innovative treatments have standardized insulin delivery and improved outcomes for patients, but patients’ access to such technologies depends on social determinants of health, including insurance coverage, proper diagnosis, and appropriate patient supports. Prior estimates of US prevalence, incidence, and patient characteristics have relied on data from select regions and younger ages and miss important determinants. Objectives: This study sought to use large, nationally representative healthcare claims data sets to holistically estimate the size of the current US population with T1DM and investigate geographic nuances in prevalence and incidence, patient demographics, insurance coverage, and device use. This work also aimed to project T1DM population growth over the next 10 years. Methods: We used administrative claims from 4 sources to identify prevalent and incident T1DM patients in the US, as well as various demographic and insurance characteristics of the patient population. We combined this data with information from national population growth projections and literature to construct an actuarial model to project growth of the T1DM population based on current trends and scenarios for 2024, 2029, and 2033. Results: We estimated 2.07 million T1DM patients nationally across all insurance coverages in our 2024 baseline model year: 1.79 million adults (≥20 years) and 0.28 million children. This represents a US T1DM prevalence rate of 617 per 100 000 and an incidence rate of 0.016%. By 2033, we project the US population with T1DM will grow by about 10%, reaching approximately 2.29 million patients. Discussion: Our results showed important differences in T1DM prevalence and incidence across regions, payers, and ethnic groups. This suggests studies based on more geographically concentrated data may miss important variation in prevalence and incidence across regions. It also indicates T1DM prevalence tends to vary by income, consistent with several international studies. Conclusions: Accurate projections of T1DM population growth are critical to ensure appropriate healthcare coverage and reimbursement for treatments. Our work supports future policy and research efforts with 2024, 2029, and 2033 projections of demographics and insurance coverage for people with T1DM.

An overview of cell salvage in orthopaedic hip and knee arthroplasty surgery.

Blood management is a critical aspect of patient care during surgical procedures. In the United Kingdom, there is a growing recognition of the need to integrate intraoperative cell salvage into blood management protocols, especially for invasive surgeries where significant blood loss is anticipated. While donated blood (allogeneic blood) is traditionally used in such cases, it carries risks and potential complications. Consequently, intraoperative cell salvage presents itself as an appealing alternative, particularly in hip and knee arthroplasty procedures. Intraoperative cell salvage involves the collection and reinfusion of a patient's own blood (autologous blood) lost during surgery. Studies have consistently shown that autologous blood collected via intraoperative cell salvage has fewer complications and greater benefits compared to donated blood. However, despite these advantages, the widespread adoption of intraoperative cell salvage in UK hospitals remains limited, primarily due to associated costs. While the integration of intraoperative cell salvage into blood management services may incur initial expenses, research suggests that it could ultimately prove to be cost-effective. This is because improved patient outcomes associated with intraoperative cell salvage may lead to reduced postoperative complications and shorter hospital stays. Thus, there is a growing imperative to overcome financial barriers and promote the implementation of intraopertive cell salvage as a standard practice in perioperative care across UK health care settings. The purpose of this scoping literature review is to consolidate the available information on the current use of intraoperative cell salvage and to identify intraoperative cell salvage techniques and devices described for use in an arthroplasty setting.

Abstract 4144549: Proof of Concept of a Novel Culinary Medicine Service Line to Address Diet-Related Cardiovascular Disease Risk Factors

Background: Poor diet has emerged as a top contributor to cardiovascular disease (CVD) in the United States. Evidence-based dietary strategies have been shown to decrease CVD risk by addressing comorbid conditions such as hypertension and diabetes, and there is a growing demand for practical nutrition guidance from health providers. However, implementation of nutrition support in healthcare settings remains limited due to lack of time, expertise, and reimbursement, necessitating creative interprofessional collaboration. Culinary Medicine (CM) combines medical nutrition education with culinary literacy and holds promise to address these challenges. Our study reports on the cascade implementation of a 3-prong CM service line which includes a CM eConsult, 1:1 CM specialty clinic, and shared medical appointment (group visit) in a teaching kitchen at a large, academic medical center from 2021 to 2024. Methods: A CM-specific eConsult was designed and launched on August 1 st 2021 utilizing existing eConsult workflows in the electronic health record. Next, an in-person, interprofessional CM specialty clinic launched at a community-based satellite clinic December 4 th 2022 open to referrals from physicians and patients. In April 2024, established patients in the CM clinic were invited to participate in six, biweekly cooking classes billed as shared medical appointments. A Microsoft PowerBI dashboard was developed to track patient demographics, referrals and participation, associated diagnoses, and billing data for the service line for continuous quality improvement. Results: In the first year of eConsults, 25 eConsults were completed with 19 (76%) reimbursed by insurance. In the first year from launch of the CM specialty clinic, 96 patients completed initial visits with a 100% insurance collections rate. In the recent launch of shared medical appointments, the initial cohort included 17 unique patients with 58% completing at least 4 of 6 classes. Referrals to the CM clinic included hypertension, hyperlipidemia, coronary artery disease, and type 2 diabetes as the top 4 associated diagnoses. Conclusions: We demonstrated proof-of-concept of a novel CM service line as an interprofessional, financially sustainable preventive strategy to target patients with diet-sensitive CVD risk factors such as diabetes, hypertension, and obesity. Future study will investigate the impact on biomarkers of CVD health for patients served by the CM service line.

Co-existence of antibiotic resistance and virulence factors in carbapenem resistant Klebsiella pneumoniae clinical isolates from Alexandria, Egypt.

The emergence and spread of carbapenem resistance among Enterobacteriaceae, particularly Klebsiella pneumoniae, constitute a serious threat to public health, since carbapenems are the last line of defense in the treatment of life-threatening infections caused by drug-resistant Enterobacteriaceae. The current study investigated the co-existence of different virulence factors and carbapenemases in carbapenem-resistant Klebsiella pneumoniae clinical isolates from Alexandria, Egypt. Phenotypic characterization of virulence factors indicated that 41.5% of the isolates were strong biofilm producers, while hypermucoviscosity was detected in 14.9% of the isolates. All isolates harbored five or more virulence factor encoding genes. entB, ycfM, mrkD and fimH were detected in all isolates, while only one isolate was negative for ybtS. uge, iutA, rmpA and kpn were detected in 61 (64.8%), 55 (58.5%), 41 (43.6%) and 27 (28.7%) isolates, respectively, while all isolates lacked magA and k2A. Phenotypic detection of carbapenemases was explored by performing CarbaNP and mCIM/eCIM. CarbaNP test showed positive results in 98.9% of the isolates and positive mCIM tests were observed in all isolates, while 68 (72.3%) isolates showed positive eCIM tests. blaNDM was the most prevalent carbapenemase encoding gene (92.5%) followed by the blaOXA-48 (51.1%), while blaKPC was detected in only one (1.06%) isolate. blaVIM, blaIMP and blaGES were not detected in any of the tested isolates. The widespread of carbapenem-resistant Klebsiella pneumoniae represents a major problem in health care settings. A significant association between certain virulence factors and carbapenemase-encoding genes was observed. Antibiotic stewardship programs and infection control policies should be effectively implemented especially in hospitals to limit the spread of such highly virulent pathogens.