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With artificial intelligence (AI) rapidly advancing, advanced practice nurses must understand and use it responsibly. Here, we describe an assignment in which Doctor of Nursing Practice (DNP) students learned to use generative text AI. Using our program and course outcomes, developed from the 2021 American Association of Colleges of Nursing (AACN) Essentials competency for DNP students to learn and use AI, we reviewed the literature seeking examples using ChatGPT for the DNP informatics course. No published examples existed to guide us toward infusing a ChatGPT assignment into the course. We developed a novel assignment that included a guide for students on how to use ChatGPT. Students were given time before the assignment to learn the AI/chatbot technology. They were then given the assignment and grading rubric. The assignment was to develop a tool for their current or future practice using ChatGPT. During the course faculty debrief, we learned that few students had questions and the assignment was clear. We also learned that students who sought to develop straightforward, uncomplicated patient tools succeeded with the technology. Those who sought to create something for complex patients had more challenges. Nursing education and practice will be influenced by the increasing prevalence of AI. This manuscript outlines an AI-based assignment for graduate nursing education intended for the students to become familiar with current AI and best practices for patient care. The assignment was well received by students. We plan to use it again in the next course offering. [ABSTRACT FROM AUTHOR]

Background: The use of robotic-assisted total knee arthroplasty (RA-TKA) is gaining traction. There is evidence to suggest that RA-TKA can help to optimize the precision and accuracy of implant positioning and that there may be protective effects on surrounding bony and soft tissues. Yet, there are important differences between the various RA-TKA systems currently on the market. One such newly introduced RA-TKA system uses imageless technology and performs bony cuts with the use of a burr-based device. The learning curve and complications unique to this system have yet to be assessed. Methods: We evaluated 500 consecutive RA-TKA cases using a newly developed burr-based and imageless system which were done by a single surgeon between the months of October 2021 and February 2023. Operative times were recorded and compared to the previous 150 conventional TKA cases allowing for the learning curve to be calculated using the CUSUM method. Intraoperative and postoperative complications were categorically profiled. Results: The learning curve of this RA-TKA system was found to be 6 cases. Intraoperative complications included unintended bony over resection (n = 3), soft tissue injury (n = 2), and robotic system hardware (n = 2) or software (n = 2) malfunction. Postoperative complications consisted of superficial pin site infection (n = 1) and periprosthetic fracture near the pin sites (n = 1). There were no identified cases of prosthetic joint infection, instability events, or wound complications. Conclusions: The learning curve and the complication profile of a newly introduced imageless and burr-based RA-TKA system were described. This information serves to guide surgeons in adopting this technology and can counsel them regarding the potential pitfalls and challenges associated with its integration into practice. The work sheds light on the complexity and learning curve of the recently released imageless burr-based RA-TKA system. This important information is intended to help surgeons accept this cutting-edge technology by providing advice on any errors and difficulties that can occur when integrating it into clinical practice. This information can help surgeons navigate the complexities of integrating this new burr-based robotic technology into knee replacement procedures, enabling them to make well-informed decisions and receive guidance. [ABSTRACT FROM AUTHOR]

The American Nephrology Nurses Association (ANNA) and American Society of Nephrology (ASN) have joined forces with the goal of advancing improvements in kidney care through transformative change. Through the integration of expertise, resources, and networks from both organizations, these collaborations have the potential to improve patient outcomes, advance clinical practice, and shape policy initiatives. In this article, we describe our focus on three areas: strengthening the nephrology and nephrology nursing workforce, championing health care equity, and advocating for kidney health. [ABSTRACT FROM AUTHOR]

Background: The field of robotic-assisted surgery is rapidly growing as many robotic surgical devices are in development and about to enter the market. Currently, there is no universally accepted language for labeling the different robotic systems. To facilitate this communication, we created what is, to our knowledge, the first classification of surgical robotic technologies that organizes and classifies surgical robots used for endoscopy, laparoscopy and thoracoscopy. Methods: We compiled a list of surgical robots intended to be used for endoscopy, laparoscopy, and/or thoracoscopy by searching United States, European, Hong Kong, Japan, and Korean databases for approved devices. Devices showcased at the 2023 Annual Meeting for the Society of Robotic Surgery were added. We also systematically reviewed the literature for any existing surgical robotic classifications or categorizations. We then created a multidisciplinary committee of 8 surgeons and 2 engineers to construct a proposed classification of the devices included in our search. Results: We identified 40 robotic surgery systems intended to be used for endoscopy, laparoscopy and/or thoracoscopy. The proposed classification organizes robotic devices with regard to architecture, port design, and configuration (modular carts, multi-arm integrated cart, table-attachable or arm-table integration). Conclusion: This 3-level classification of robotic surgical devices used for endoscopy, laparoscopy and/or thoracoscopy describes important characteristics of robotic devices systematically. [ABSTRACT FROM AUTHOR]

Simple Summary: Breast cancer is a significant cause of female cancer-related deaths in the US. Checking how severe the cancer is helps in planning treatment. Modern AI methods are good at grading cancer, but they are not used much in hospitals yet. We developed and utilized ensemble deep learning algorithms for addressing the tasks of classifying (1) breast cancer subtype and (2) breast cancer invasiveness from whole slide image (WSI) histopathology slides. The ensemble models used were based on convolutional neural networks (CNNs) known for extracting distinctive features crucial for accurate classification. In this paper, we provide a comprehensive analysis of these models and the used methodology for breast cancer diagnosis tasks. Cancer diagnosis and classification are pivotal for effective patient management and treatment planning. In this study, a comprehensive approach is presented utilizing ensemble deep learning techniques to analyze breast cancer histopathology images. Our datasets were based on two widely employed datasets from different centers for two different tasks: BACH and BreakHis. Within the BACH dataset, a proposed ensemble strategy was employed, incorporating VGG16 and ResNet50 architectures to achieve precise classification of breast cancer histopathology images. Introducing a novel image patching technique to preprocess a high-resolution image facilitated a focused analysis of localized regions of interest. The annotated BACH dataset encompassed 400 WSIs across four distinct classes: Normal, Benign, In Situ Carcinoma, and Invasive Carcinoma. In addition, the proposed ensemble was used on the BreakHis dataset, utilizing VGG16, ResNet34, and ResNet50 models to classify microscopic images into eight distinct categories (four benign and four malignant). For both datasets, a five-fold cross-validation approach was employed for rigorous training and testing. Preliminary experimental results indicated a patch classification accuracy of 95.31% (for the BACH dataset) and WSI image classification accuracy of 98.43% (BreakHis). This research significantly contributes to ongoing endeavors in harnessing artificial intelligence to advance breast cancer diagnosis, potentially fostering improved patient outcomes and alleviating healthcare burdens. [ABSTRACT FROM AUTHOR]

This Joel A. DeLisa Lecture on endovascular brain-computer interfaces was presented by Dr Thomas Oxley on February 23, 2023, at the Association of Academic Physiatrists Annual Scientific Meeting. The lecture described how brain-computer interfaces replace lost physiological function to enable direct communication between the brain and external digital devices, such as computers, smartphones, and robotic limbs. Specifically, the potential of a novel endovascular brain-computer interface technology was discussed. The brain-computer interface uses a stent-electrode array delivered via the jugular vein and is permanently implanted in a vein adjacent to the motor cortex. In a first-in-human clinical trial, participants with upper limb paralysiswho received the endovascular brain-computer interface could use the system independently and at home to operate laptop computers for various instrumental activities of daily living. A Food and Drug Administration-approved trial of the endovascular brain-computer interface in the United States is in progress. Future development of the system will provide recipients with continuous autonomy through digital access with minimal caregiver assistance. Physiatrists and occupational therapists will have a vital role in helping people with paralysis achieve the potential of implantable brain-computer interfaces. [ABSTRACT FROM AUTHOR]

The present study aims to explore the global landscape of neurotechnology research and investigate the factors that influence its citation impact. The data for the study were extracted from the Web of Science Core Collection database, resulting in a total of 1,473 articles related to neurotechnology. The study identified a notable increase in neurotechnology research over time, peaking at 37.20% from 2020 to 2023, with Scientific Reports as the leading journal. Collaborative efforts with two to four authors constituted 42.90% of the total articles. The United States led country-level contributions (29.26%). The University of California secured the top rank with 4.48% of the total publications. The United States Department of Health and Human Services remains at the top by contributing funding to 7.46% of research papers in the field of Neurotechnology research. Statistical tests confirmed significant correlations between research funding, collaboration, and research availability mode with citation impact. Positive correlations were identified between research funding and collaboration, while open access availability showed a negative correlation with citation impact. These findings deepen our understanding of neurotechnology research dynamics, providing insights for researchers, institutions, and policymakers. [ABSTRACT FROM AUTHOR]

The article discusses how forming partnerships with social media influencers offers a novel strategy for supporting cancer care delivery, with the potential for equitable improving adolescents and young adult (AYA) cancer outcomes. Topics include cancer care delivery needs and prior social media approaches for AYAs with cancer, how forming partnerships with cancer influencers has implications for improving AYA cancer care, and examples of social media approaches for addressing AYA disparities.

Dry eye disease (DED) can arise from a variety of factors, including inflammation, meibomian gland dysfunction (MGD), and neurosensory abnormalities. Individuals with DED may exhibit a range of clinical signs, including tear instability, reduced tear production, and epithelial disruption, that are driven by different pathophysiological contributors. Those affected often report a spectrum of pain and visual symptoms that can impact physical and mental aspects of health, placing an overall burden on an individual's well-being. This cumulative impact of DED on an individual's activities and on society underscores the importance of finding diverse and effective management strategies. Such management strategies necessitate an understanding of the underlying pathophysiological mechanisms that contribute to DED in the individual patient. Presently, the majority of approved therapies for DED address T cell-mediated inflammation, with their tolerability and effectiveness varying across different studies. However, there is an emergence of treatments that target additional aspects of the disease, including novel inflammatory pathways, abnormalities of the eyelid margin, and neuronal function. These developments may allow for a more nuanced and precise management strategy for DED. This review highlights the recent pharmacological advancements in DED therapy in the United States. It discusses the mechanisms of action of these new treatments, presents key findings from clinical trials, discusses their current stage of development, and explores their potential applicability to different sub-types of DED. By providing a comprehensive overview of products in development, this review aims to contribute valuable insights to the ongoing efforts in enhancing the therapeutic options available to individuals suffering from DED. [ABSTRACT FROM AUTHOR]

Objectives: This research aims to present and assess the Primary Functions of autoinjectors introduced in ISO 11608-1:2022. Investigate the risks in current autoinjector technology, identify and assess risks and benefits associated with Artificial Intelligence (AI) powered autoinjectors, and propose a framework for mitigating these risks. ISO 11608-1:2022 is a standard that specifies requirements and test methods for needle-based injection systems intended to deliver drugs, focusing on design and function to ensure patient safety and product effectiveness. 'KZH' is an FDA product code used to classify autoinjectors, for regulatory purposes, ensuring they meet defined safety and efficacy standards before being marketed. Method: A comprehensive analysis of autoinjectors problems is conducted using data from the United States Food and Drug Administration (FDA) database. This database records medical device reporting events, including those related to autoinjectors, reported by various sources. The analysis focuses on events associated with the product code KZH, covering data from January 1, 2008, to September 30, 2023. This research employs statistical frequency analysis and incorporates pertinent the FDA, United Kingdom, European Commission regulations, and ISO standards. Results: 500 medical device reporting events are assessed for autoinjectors under the KZH code. Ultimately, 188 of these events are confirmed to be associated with autoinjectors, all 500 medical devices were seen to lack AI capabilities. An analysis of these events for traditional mechanical autoinjectors revealed a predominant occurrence of malfunctions (72%) and injuries (26%) among event types. Device problems, such as breakage, defects, jams, and others, accounted for 45% of incidents, while 10% are attributed to patient problems, particularly missed and underdoses. Conclusion: Traditional autoinjectors are designed to assist patients in medication administration, underscoring the need for quality control, reliability, and design enhancements. AI autoinjectors, sharing this goal, bring additional cybersecurity and software risks, requiring a comprehensive risk management framework that includes standards, tools, training, and ongoing monitoring. The integration of AI promises to improve functionality, enable real-time monitoring, and facilitate remote clinical trials, timely interventions, and tailored medical treatments. [ABSTRACT FROM AUTHOR]

Aims: To share lessons learned from an evidence-based practice (EBP) initiative that implemented near-infrared (NIR) technology in a large US hospital system. A Clinical Technology Implementation Model (CTIM©) that can be adapted for use in other health institutions is presented. Background: EBP implementation, including the adoption of new cutting-edge technologies, is crucial to improving patient care. Yet there are significant delays in changes to clinical practice, often due to organisational challenges that stifle the implementation process. The evidence−practice gap is increasingly evident in peripheral intravenous access (PIV). Implementation science offers new insights into the challenges of updating clinical practice, which can support EBP implementation. Evaluation: Recent literature on implementation science, change theory, PIV access, NIR technology, and patient outcomes were reviewed. A model that can help nurse managers implement technology that aligns with EBP is presented, drawing on experience from the adoption of NIR vein visualisation to enhance PIV access in a large US hospital system. Key issue: A pervasive hesitancy in healthcare to embrace technology, coupled with the challenges of implementing a change to practice, has led to limited application of EBP PIV access guidelines and a stagnant standard of care. Conclusion: This article provides nurse managers with the tools necessary to successfully implement EBP, drawing on the experience from implementing NIR in a large US hospital. Nurse managers are uniquely positioned to lead the way in embracing technology to improve care and reduce the evidence−practice gap. [ABSTRACT FROM AUTHOR]

In response to the COVID-19 pandemic, emergency medical services (EMS) and hospitals recognized the need for innovative programs addressing 9-1-1 utilization and ambulance transport to provide patient-centered, safe, cost-effective care. The ET3 (Emergency Triage, Treatment, and Transport) model provides flexibility and new payments to ambulance care teams for Medicare beneficiaries for alternate strategies of care. This includes providing treatment in place through telehealth after a 9-1-1 call and ambulance response. Our objective is to evaluate the implementation barriers of a telemedicine service to 9-1-1 responding ambulances providing treatment in place for low-acuity conditions. The TeleEMS program was piloted in a large, urban fire-based EMS system with eight ambulances geographically surrounding one hospital. Paramedics received training on the telemedicine software and screening criteria, which were age 1–70 and vital sign parameters. Pregnant, combative, and patients with no clear need for emergency department transport were excluded. Three emergency physicians with additional training in EMS provided the TeleEMS service from 8am to 6 pm on Monday - Friday. The telemedicine software was application-based and provided HIPAA-compliant two-way, real-time audio and video communication through the 4G network on a tablet. The TeleEMS physicians had access to a database of clinics and hospitals that coordinate health care. The TeleEMS physician contacted the patient within 24–72 hours after the encounter for follow-up. The TeleEMS pilot program ran for 12 weeks from April – June 2021. During this time, there were seven completed consults with treatment in place, one completed consult with transport to an emergency department, and five consult attempts that failed due to technological issues with resultant transport. Each of the consults (13/13) met the TeleEMS screening criteria. Post-pilot focus group sessions were held to determine paramedic feedback. Barriers to an EMS telemedicine program include paramedic buy-in, patient expectations for emergency care, technology limitations, and qualified physician resources. An EMS telemedicine program can be successfully implemented in urban fire-based EMS systems for 9-1-1 responding ambulances. Barriers to implementation should be addressed at the paramedic, patient, technology, and program levels to improve success. [ABSTRACT FROM AUTHOR]

The article focuses on the T1D Exchange's efforts to advance outcomes in type 1 diabetes care through collaborative change. The topics includes the persistent disparities in diabetes technology use, the impact of regional and racial/ethnic variations, and initiatives to address inequities in diabetes technology utilization.

The American Diabetes Association's Standards of Care in Diabetes recommends the use of diabetes technology such as continuous glucose monitoring systems and insulin pumps for people living with type 1 diabetes. Unfortunately, there are multiple barriers to uptake of these devices, including local diabetes center practices. This study aimed to examine overall change and center-to-center variation in uptake of diabetes technology across 21 pediatric centers in the T1D Exchange Quality Improvement Collaborative. It found an overall increase in diabetes technology use for most centers from 2021 to 2022 with significant variation. [ABSTRACT FROM AUTHOR]

Adoption of health information technology (HIT) in nursing homes (NHs) improves quality of care. Although there is a robust body of research on HIT adoption, the closely related process of technology abandonment is not well understood. As NHs grow more reliant on HIT, problems of technology abandonment, defined as failure to scale up, spread, and sustain HIT need to be studied. Our objective is to describe HIT abandonment and its associations with organizational characteristics among a national sample of US NHs. Longitudinal, retrospective analysis of data from 2 sources: HIT Maturity Survey and Staging model and public data from the Care Compare database. Random sample of NHs (n = 299) representing each US state that completed the HIT maturity survey in 2 consecutive years: year 1 (Y1) was June 2019–August 2020 and year 2 (Y2) was June 2020–August 2021. The primary dependent variable was technology abandonment, operationalized by using total HIT maturity score, HIT maturity stage, and subscale scores within each dimension/domain. Independent variables were NH organizational characteristics including bed size, type of ownership, urbanicity, Centers for Medicare & Medicaid Services Five-Star Overall Rating and Staffing Rating. Over the 2-year period, HIT abandonment occurred in 28% (n = 85) of NHs compared with 44% (n = 133) that experienced growth in HIT systems. HIT capabilities in resident care were abandoned most frequently. Using multivariable multinomial logistic regression, we found that large NHs (bed size greater than 120) were more likely to experience technology abandonment in administrative activities. Technology abandonment can increase strain on scarce resources and may impact administrators' ability to oversee clinical operations, especially in large NHs. This study contributes to the limited understanding of technology abandonment and can serve as a building block for others working to ensure limited resources are used effectively to improve care for NH residents. [ABSTRACT FROM AUTHOR]

Background: Heart rate variability (HRV) biofeedback is often performed with structured education, laboratory-based assessments, and practice sessions. It has been shown to improve psychological and physiological function across populations. However, a means to remotely use and monitor this approach would allow for wider use of this technique. Advancements in wearable and digital technology present an opportunity for the widespread application of this approach. Objective: The primary aim of the study was to determine the feasibility of fully remote, self-administered short sessions of HRV-directed biofeedback in a diverse population of health care workers (HCWs). The secondary aim was to determine whether a fully remote, HRV-directed biofeedback intervention significantly alters longitudinal HRV over the intervention period, as monitored by wearable devices. The tertiary aim was to estimate the impact of this intervention on metrics of psychological well-being. Methods: To determine whether remotely implemented short sessions of HRV biofeedback can improve autonomic metrics and psychological well-being, we enrolled HCWs across 7 hospitals in New York City in the United States. They downloaded our study app, watched brief educational videos about HRV biofeedback, and used a well-studied HRV biofeedback program remotely through their smartphone. HRV biofeedback sessions were used for 5 minutes per day for 5 weeks. HCWs were then followed for 12 weeks after the intervention period. Psychological measures were obtained over the study period, and they wore an Apple Watch for at least 7 weeks to monitor the circadian features of HRV. Results: In total, 127 HCWs were enrolled in the study. Overall, only 21 (16.5%) were at least 50% compliant with the HRV biofeedback intervention, representing a small portion of the total sample. This demonstrates that this study design does not feasibly result in adequate rates of compliance with the intervention. Numerical improvement in psychological metrics was observed over the 17-week study period, although it did not reach statistical significance (all P>.05). Using a mixed effect cosinor model, the mean midline-estimating statistic of rhythm (MESOR) of the circadian pattern of the SD of the interbeat interval of normal sinus beats (SDNN), an HRV metric, was observed to increase over the first 4 weeks of the biofeedback intervention in HCWs who were at least 50% compliant. Conclusions: In conclusion, we found that using brief remote HRV biofeedback sessions and monitoring its physiological effect using wearable devices, in the manner that the study was conducted, was not feasible. This is considering the low compliance rates with the study intervention. We found that remote short sessions of HRV biofeedback demonstrate potential promise in improving autonomic nervous function and warrant further study. Wearable devices can monitor the physiological effects of psychological interventions. [ABSTRACT FROM AUTHOR]

Through narrative, the subjective experience of illness offers a corrective to biomedicine's interpretive grip. Narrative is both process and product and illness narratives, in particular, are examples of embodied research. This ecopathography – drawing upon embodied experiences of treatment and recovery from late stage Non-Hodgkin's lymphoma – enlists Haraway's cyborg and Lupton's digital assemblage in an effort to make broader claims about patient care in the United States, and specifically, the role of technology in healthcare and in the construction of patient identity. A surgically implanted port (facilitating blood draws and the delivery of chemotherapy) and the patient portal (representing the results of those blood draws as well as a medium for communication) provide a foundation for how cyborgian assemblages both assist and trouble the cancer experience. At stake is the fluidity and ambiguity of boundaries (human/machine, human/animal, and physical/virtual) and the management of those boundaries with regard to patient care. [ABSTRACT FROM AUTHOR]

Technological developments in laboratory and epidemiologic methods, combined with increasing computing power, have synergistically increased our understanding of the epidemiology of infectious disease. Using historical examples from the first 100 years of the American Journal of Epidemiology , we illustrate how these developments provided the foundation for the rapid detection of the agent causing coronavirus disease 2019 (COVID-19), severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), from its transmission efficiency and modalities, risk factors, and natural history to the evaluation of new vaccines and treatments to control its spread and impact. Comparisons with timelines for elucidation of the epidemiology, natural history, and control of other infectious diseases, including viral hepatitis, humbly remind us of how much past discoveries have paved the way for more rapid discovery of and response to new pathogens. We close with some comments on a potential future role of the Journal in infectious disease epidemiology. [ABSTRACT FROM AUTHOR]

Background: Papillary thyroid cancer (PTC) is the most common endocrine malignancy worldwide. The treatment of PTC has attracted extensive attention and discussion from the public and scholars. However, no article has systematically assessed the related literature. Therefore, we conducted a bibliometric and knowledge map analysis to reveal the dynamic scientific developments in the PTC therapy field. Methods: We retrieved publications related to PTC therapy from the Web of Scientific Core Collection (WoSCC) on May 1, 2023. The bibliometric package in R software, VOSviewer and CiteSpace software were used to analyze countries/ regions, institutions, journals, authors, references, and keywords. Then, we systematized and summarized the research landscape, global trends and hot topics of research. Results: This bibliometric analysis spanned from 2012 to 2022 and involved 18,501 authors affiliated with 3,426 institutions across 87 countries/regions, resulting in the publication of 3,954 papers in 860 academic journals. Notably, the number of publications and citations related to PTC therapy research has exhibited a steady increase over the past decade. China and the United States have emerged as leading contributors in terms of publication count, with the United States also being the most cited country. Furthermore, among the top 10 institutions with the highest number of published papers, half were located in China. Among the journals, Thyroid is ranked first in terms of total publications and citations. The most productive individual author was Miyauchi Akira. While previous research primarily focused on surgery and radioactive iodine therapy, the increasing emphasis on health awareness and advancements in medical technology have led to the emergence of active surveillance, thermal ablation, and genomic analysis as prominent areas of research. Conclusion: In conclusion, this comprehensive and quantitative bibliometric analysis elucidates the research trends and hotspots within PTC therapy, drawing rom a substantial body of publications. This study provides valuable insights into the historical and current landscape of PTC therapy research while also offering guidance for future research directions. This study serves as a valuable resource for researchers and practitioners seeking new avenues of exploration in the field. [ABSTRACT FROM AUTHOR]

The rapid development of sophisticated artificial intelligence ("AI") tools in healthcare presents new possibilities for improving medical treatment and general health. Currently, such AI tools can perform a wide range of healthrelated tasks, from specialized autonomous systems that diagnose diabetic retinopathy to general-use generative models like ChatGPT that answer users' health-related questions. On the other hand, significant liability concerns arise as medical professionals and consumers increasingly turn to AI for health information. This is particularly true for black-box AI because while potentially enhancing the AI's capability and accuracy, these systems also operate without transparency, making it difficult or even impossible to understand how they arrive at a particular result. The current liability framework is not fully equipped to address the unique challenges posed by black-box AI's lack of transparency, leaving patients, consumers, healthcare providers, AI manufacturers, and policymakers unsure about who will be responsible for AI-caused medical injuries. Of course, the United States is not the only jurisdiction faced with a liability framework that is out of tune with the current realities of black-box AI technology in the health domain. The European Union has also been grappling with the challenges that black-box AI poses to traditional liability frameworks and recently proposed new liability Directives to overcome some of these challenges. As the first to analyze and compare the liability frameworks governing medical injuries caused by black-box AI in the United States and European Union, this Article demystifies the structure and relevance of foreign law in this area to provide practical guidance to courts, litigators, and other stakeholders seeking to understand the application and limitations of current and newly proposed liability law in this domain. We reveal that remarkably similar principles will operate to govern liability for medical injuries caused by black-box AI and that, as a result, both jurisdictions face similar liability challenges. These similarities offer an opportunity for the United States to learn from the European Union's newly developed approach to governing liability for AI-caused injuries. In particular, we identify four valuable lessons from the European Union's approach. First, a broad approach to AI liability fails to provide solutions to some challenges posed by black-box AI in healthcare. Second, traditional concepts of human fault pose significant challenges in cases involving black-box AI. Third, product liability frameworks must consider the unique features of black-box AI. Fourth, evidentiary rules should address the difficulties that claimants will face in cases involving medical injuries caused by black-box AI. [ABSTRACT FROM AUTHOR]

MATCH (Motivating Adolescents with Technology to CHOOSE Health) is an online, interdisciplinary wellness program targeted at improving adolescent nutrition that teachers can easily incorporate into existing curricula. The shift from childhood to adolescence is characterized by rapid increases in autonomy of nutritional intake. Given that dietary habits established in adolescence often persist into adulthood, effective nutrition education programs during this period are of particular relevance. Although there are a vast number of existing nutrition education programs aimed at adolescents, we explain why MATCH and similar programs should be expanded across the United States to improve adolescent health outcomes including obesity prevention. [ABSTRACT FROM AUTHOR]

Background Pressure injury (PI) development is multifactorial. In patients with dark skin tones, identifying impending PIs by visual skin assessment can be especially challenging. The need for improved skin assessment techniques, especially for persons with dark skin tones, continues to increase. Similarly, greater awareness of the need for inclusivity with regard to representation of diverse skin colours/tones in education materials has been apparent in recent years. Objective To provide current perspectives from the literature surrounding skin assessment and PI development in patients with dark skin tones. Methods The following elements will be discussed through the lens of skin tone: 1) historical perspectives of PI staging from the National Pressure Injury Advisory Panel, 2) epidemiology of PI, 3) anatomy and physiology of the skin, 3) skin tone assessment and measurement, 4) augmented visual assessment modalities, 5) PI prevention, 6) PI healing, 7) social determinants of health, and 8) gaps in clinician education. Conclusions This review highlights the gap in our clinical knowledge regarding PIs in patients with dark skin tones. Racial disparities with regard to PI development and healing are especially highlighted among patients with dark skin tones. Skin tone colour assessment must be standardised and quantifiable in clinical education, practice, and research. This work is urgently needed, and support from private and governmental agencies is essential. [ABSTRACT FROM AUTHOR]

The article offers a review of U.S. Pharmacopeia (USP) chapters relating to the stability, efficacy and safety of messenger RNA (mRNA)-based lipid nanoparticle (LNP)-based COVID-19 vaccines. Topics discussed include the control of particulate matter in injections, particle size distribution (PSD) in lipid injectable emulsions, and technology for quantifying the critical large-diameter tail (LDT) region in PSD.

In 2019, the National Health Interview survey found that nearly 59% of adults reported pain some, most, or every day in the past 3 months, with 39% reporting back pain, making back pain the most prevalent source of pain, and a significant issue among adults. Often, identifying a direct, treatable cause for back pain is challenging, especially as it is often attributed to complex, multifaceted issues involving biological, psychological, and social components. Due to the difficulty in treating the true cause of chronic low back pain (cLBP), an over-reliance on opioid pain medications among cLBP patients has developed, which is associated with increased prevalence of opioid use disorder and increased risk of death. To combat the rise of opioid-related deaths, the National Institutes of Health (NIH) initiated the Helping to End Addiction Long-TermSM (HEAL) initiative, whose goal is to address the causes and treatment of opioid use disorder while also seeking to better understand, diagnose, and treat chronic pain. The NIH Back Pain Consortium (BACPAC) Research Program, a network of 14 funded entities, was launched as a part of the HEAL initiative to help address limitations surrounding the diagnosis and treatment of cLBP. This paper provides an overview of the BACPAC research program's goals and overall structure, and describes the harmonization efforts across the consortium, define its research agenda, and develop a collaborative project which utilizes the strengths of the network. The purpose of this paper is to serve as a blueprint for other consortia tasked with the advancement of pain related science. [ABSTRACT FROM AUTHOR]

The Centers for Disease Control and Prevention Minority HIV Research Initiative (MARI) funded 8 investigators in 2016 to develop HIV prevention and treatment interventions in highly affected communities. We describe MARI studies who used community-based participatory research methods to inform the development of interventions in Black/African American and Hispanic/Latinx communities focused on sexual minority men (SMM) or heterosexual populations. Each study implemented best practice strategies for engaging with communities, informing recruitment strategies, navigating through the impacts of COVID-19, and disseminating findings. Best practice strategies common to all MARI studies included establishing community advisory boards, engaging community members in all stages of HIV research, and integrating technology to sustain interventions during the COVID-19 pandemic. Implementing community-informed approaches is crucial to intervention uptake and long-term sustainability in communities of color. MARI investigators' research studies provide a framework for developing effective programs tailored to reducing HIV-related racial/ethnic disparities. [ABSTRACT FROM AUTHOR]

Purpose: To evaluate how women of child-bearing age perceive the use of remote fetal ECG monitoring technologies. Telemedicine has advanced to the forefront of healthcare delivery, including maternal–fetal medicine. Smart wearable electrocardiogram (ECG) devices can enable pregnant women to monitor their health and that of their fetuses. Such technology would be a logical extension of the telemedicine ecosystem. Methods: We conducted an observational cross-sectional study via online surveying in the United States. Study participants were recruited using the SurveyMonkey Audience Polling system and responded virtually. In all, the sample consisted of 507 women, aged 18–45 from 45 states, who are expecting to become pregnant in the next five years. Women were asked to identify their willingness to use a wearable ECG device the size of a patch-sized large band-aid on their abdomen. Ten binary or multiple-choice questions were used to gauge population interest and related demographics toward the usage of a wearable ECG device. Results: Of the 507 participants, 461 (91%) women expressed an acceptance of wearable ECG technology throughout the pregnancy as a mechanism for increased frequency of monitoring of maternal and fetal health outside the hospital. 395 (78%) women demonstrated a willingness to wear devices day and night or at least during sleep and 213 (42%) of the women would spend up to $200 on such a device. Conclusion: Even though conducted prior to the COVID-19 pandemic, this study clearly indicates a high degree of readiness of prospective pregnant women for telemedicine with continuous health monitoring of the mother-fetus dyad. [ABSTRACT FROM AUTHOR]

Social network analysis has created a productive framework for the analysis of the histories of patient-physician interactions and physician collaboration. Notable is the construction of networks based on the data of “referral paths” – sequences of patient-specific temporally linked physician visits – in this case, culled from a large set of Medicare claims data in the United States. Network constructions depend on a range of choices regarding the underlying data. In this paper we introduce the use of a five-factor experiment that produces 80 distinct projections of the bipartite patient-physician mixing matrix to a unipartite physician network derived from the referral path data, which is further analyzed at the level of the 2,219 hospitals in the final analytic sample. We summarize the networks of physicians within a given hospital using a range of directed and undirected network features (quantities that summarize structural properties of the network such as its size, density, and reciprocity). The different projections and their underlying factors are evaluated in terms of the heterogeneity of the network features across the hospitals. We also evaluate the projections relative to their ability to improve the predictive accuracy of a model estimating a hospital’s adoption of implantable cardiac defibrillators, a novel cardiac intervention. Because it optimizes the knowledge learned about the overall and interactive effects of the factors, we anticipate that the factorial design setting for network analysis may be useful more generally as a methodological advance in network analysis. [ABSTRACT FROM AUTHOR]

Background: Rapid advancements in research and development related to nanomedical technology raise various ethical and legal challenges in areas relevant to disease detection, diagnosis, and treatment. This study aims to outline the existing literature, covering issues associated with emerging nanomedicine and related clinical research, and identify implications for the responsible advancement and integration of nanomedicine and nanomedical technology throughout medical networks in the future. Methods: A scoping review, designed to cover scientific, ethical, and legal literature associated with nanomedical technology, was conducted, generating and analyzing 27 peer-reviewed articles published between 2007-2020. Results: Results indicate that articles referencing ethical and legal issues related to nanomedical technology were concerned with six key areas: 1) harm exposure and potential risks to health, 2) consent to nano-research, 3) privacy, 4) access to nanomedical technology and potential nanomedical therapies, 5) classification of nanomedical products in relation to the research and development of nanomedical technology, and 6) the precautionary principle as it relates to the research and development of nanomedical technology. Conclusion: This review of the literature suggests that few practical solutions are comprehensive enough to allay the ethical and legal concerns surrounding research and development in fields related to nanomedical technology, especially as it continues to evolve and contribute to future innovations in medicine. It is also clearly apparent that a more coordinated approach is required to ensure global standards of practice governing the study and development of nanomedical technology, especially as discussions surrounding the regulation of nanomedical research throughout the literature are mainly confined to systems of governance in the United States. [ABSTRACT FROM AUTHOR]

The article examines how medical technologies materialize oppression and offers taxonomy of the mechanisms of this materialization. Topics include examples that illustrate these mechanisms at work, focusing on medical data classification technologies and infrastructures, the "Reference Man" mechanism created to simplify experimental calculations of radiation exposure, and how medical technologies can materialize oppression through the biological essentialization of social differences.

It is well-known that racism is encoded into the social practices and institutions of medicine. Less well-known is that racism is encoded into the material artifacts of medicine. We argue that many medical devices are not merely biased, but materialize oppression. An oppressive device exhibits a harmful bias that reflects and perpetuates unjust power relations. Using pulse oximeters and spirometers as case studies, we show how medical devices can materialize oppression along various axes of social difference, including race, gender, class, and ability. Our account uses political philosophy and cognitive science to give a theoretical basis for understanding materialized oppression, explaining how artifacts encode and carry oppressive ideas from the past to the present and future. Oppressive medical devices present a moral aggregation problem. To remedy this problem, we suggest redundantly layered solutions that are coordinated to disrupt reciprocal causal connections between the attitudes, practices, and artifacts of oppressive systems. [ABSTRACT FROM AUTHOR]

COVID-19 pandemic brought up issues with healthcare costs, national economic development and welfare of the society in forefront. Nations across the globe followed different approaches to deal with COVID-19, such as zero tolerance, herd immunity, containment to build treatment capability. National healthcare became a contentious sociopolitical issue involving healthcare costs, technologies and societal health. In the United States even during the COVID-19 pandemic, the government approach was pursuing a sustainable improvement in patient care through adoption of medical and information technologies. The national healthcare policies are framed around technological interventions with the assumption that deployment of technologies could keep healthcare costs under control and at the same time improve health outcomes. However, evidences show that the healthcare costs are in the rise even with impressive progress in technological deployment. This article highlights some of the recent trends in healthcare costs, technological preparedness, medical technology developments in managing COVID-19 pandemic. The US government mandated electronic health record (EHR) systems implementation and assess its impact on healthcare costs and health outcomes. This article emphasizes the need for understanding the interconnectedness of costs, technology and societal health. [ABSTRACT FROM AUTHOR]

Objectives: The development of accelerated approval programs for high morbidity and unmet need conditions has driven the use of single-arm studies in drug development. Regulatory and health technology assessment (HTA) agencies are recognizing that high-quality external control arms (ECAs), built using real-world data, can reduce uncertainties arising from single-arm studies. This review compared 7 case studies of regulatory and HTA agencies' evaluations of oncology ECAs.Methods: Food and Drug Administration multidisciplinary reviews for oncology submissions from 2014 to 2021 were screened to identify 7 cases (2 blinatumomab indications, avelumab, and erdafitinib, entrectinib, trastuzumab deruxtecan, and idecabtagene vicleucel) with ECAs to support efficacy claims. Regulatory (Food and Drug Administration, European Medicines Agency, Health Canada) and HTA (pan-Canadian Oncology Drug Review, National Institute for Health and Care Excellence, Federal Joint Committee, Haute Autorité de Santé, and Pharmaceutical Benefits Advisory Committee) submissions for these cases were reviewed. The decision makers' ECA critiques and the level of influence on the decision were analyzed and categorized.Results: Across case studies, selection bias and confounding were the most common ECA critiques. Nevertheless, agreement in critiques between and among regulators and HTA bodies was low. ECA influence on agencies' decisions also varied.Conclusions: Evaluating the same ECA evidence, agencies focused on methodologic issues (ie, selection bias and confounding), but were often not aligned on their critiques. Further research is needed to fully characterize how agencies evaluate ECAs. This study is a first step in critically evaluating agencies' critiques of ECAs and highlights the need for future guidance development around ECA design and generation. [ABSTRACT FROM AUTHOR]

Aim: Describe nurses' perceptions of the barriers and facilitators that influence acceptance and use of remote visual monitoring technology. Background: Research has shown remote visual monitoring to be a useful patient safety intervention, yet nurses underutilize the technology. Methods: Using a qualitative descriptive study design, we completed a conventional content analysis of focus group feedback from two nurse leader groups and two direct care nurse groups (n = 13 participants) to explore factors influencing nurses' perceptions and utilization of remote visual monitoring. Results: Five main themes were identified: (1) Contextual human factors that impact nurse acceptance; (2) facilitators and barriers related to remote visual monitoring's functionality; (3) nurse leaders' role in maintaining device availability and efficient use; (4) nurse leaders' role in promoting adoption of the technology; and (5) nurse leaders' role in valuing nursing professional judgement. Conclusion: Findings indicate that nurse leaders can play a crucial role in direct care nurses' acceptance and use of remote visual monitoring technology. Implications for Nursing Management: In an era of limited staffing resources, remote visual monitoring has the potential to increase patient safety and decrease workload demands. Nurse leaders should identify barriers and facilitators to their nursing team's use of remote visual monitoring to promote the acceptance and use of technology that increases patient safety and cost‐effectiveness of care. [ABSTRACT FROM AUTHOR]

In the science communication literature, we can easily notice the persistence of the knowledge-attitudes model (or the deficit model) that attributes the lack of public support to a lack of scientific knowledge. However, there has also been a continuing debate over the roles of scientific knowledge in explaining public attitudes towards specific controversial science and technologies. Using the data from an American nationwide survey, this study examined the variety of antecedents of the public acceptance of human gene editing (HGE), including scientific knowledge, attitudes towards science, risk-benefit perceptions of HGE, and belief in human evolution. Our findings illuminate how scientific knowledge indirectly influenced the public acceptance of HGE through a variety of mediating variables (such as attitudes towards science, risk perceptions of HGE, and benefit perceptions of HGE), though it did not directly influence this acceptance. The findings also reveal some moderating effects of belief in human evolution on the relationships among the above variables, serving as a 'perceptual filter' in the case of HGE. These findings revisit and extend the persistent but simplified knowledge-attitudes model and provide new insights into the complicated process of public attitude formation about such controversial technologies as HGE. [ABSTRACT FROM AUTHOR]

There is strong evidence that individuals and the public assign relatively greater value to health gains from relatively more severe health states. This preference is increasingly reflected in health technology assessment, with some consideration of severity incorporated by health technology assessment bodies in, among others, The Netherlands, England and Wales, Norway, Sweden, and the United States. If a societal "severity premium" is to be considered fairly and consistently, we argue that a more explicit and quantitative approach is needed. We highlight drawbacks of categorical approaches, especially discontinuities between severity categories that arguably violate concepts of vertical equity, and argue that a more continuous approach to understanding severity is needed. We also note challenges to more explicit approaches, including implications of a lower threshold for less severe conditions and the relative complexity of calculating a continuous severity adjustment. [ABSTRACT FROM AUTHOR]

This study explores privacy issues complicated by the commodification of consumer health data in the United States by looking into loyalty programs (LPs). Three LPs – those of Nike, Walgreens, and DICK'S Sporting Goods – are examined because their incorporation of health technology represents retail data practices unregulated by the U.S. Health Information Portability and Accountability Act (HIPAA). Applying the framework of contextual integrity (Nissenbaum, 2004, 2009), the research conducted discourse analysis on corporate communications to identify whether and how privacy conflicts arise in a data economy composed of multiple business entities that use LP member data. The major contributions of this study are a clarification of shortfalls in multi-organizational governance of health-related consumer data outside the HIPAA regulation in the United States, and a recognition that businesses may optimize this data without adequately informing consumers about the risks and providing meaningful redress mechanisms. The paper concludes by urging policy-makers to target networked business relationships and externalities that result from collective behavior of firms trading in consumer health data. • Consumer loyalty programs expand beyond one brand and one consumer in the digital age. • Loyalty programs are increasingly entangled with health technologies like wearables. • Discourse analysis shows how loyalty programs naturalize more parties to member data. • Brands unevenly communicate consumer benefits and privacy risks of loyalty programs. • Loyalty programs point to need for system-level policy approaches to data governance. [ABSTRACT FROM AUTHOR]

The article focuses on Vectorious Medical Technologies implantation of the V-LAP system in the U.S., which monitors Left Atrial Pressure (LAP) to aid in managing heart failure. Topics include the system's role in enabling patient self-management, the first U.S. implantation by Dr. Sitaramesh Emani, and the promising results from ongoing clinical trials showing improvements in patient outcomes and quality of life.

Objective  Pediatric inpatient bed availability is increasingly constrained by the prolonged hospitalizations of children with medical complexity. The sickest of these patients are chronic critically ill and often have protracted intensive care unit (ICU) stays. Numbers and characteristics of infants with chronic critical illness are unclear, which undermines resource planning in ICU's and general pediatric wards. The goal of this study was to describe infants with chronic critical illness at six academic institutions in the United States. Study Design  Infants admitted to six academic medical centers were screened for chronic, critical illness based on a combination of prolonged and repeated hospitalizations, use of medical technology, and chronic multiorgan involvement. Data regarding patient and hospitalization characteristics were collected. Results  Just over one-third (34.8%) of pediatric inpatients across the six centers who met eligibility criteria for chronic critical illness were <12 months of age. Almost all these infants received medical technology (97.8%) and had multiorgan involvement (94.8%). Eighty-six percent (115/134) had spent time in an ICU during the current hospitalization; 31% were currently in a neonatal ICU, 34% in a pediatric ICU, and 17% in a cardiac ICU. Among infants who had been previously discharged home (n  = 55), most had been discharged with medical technology (78.2%) and nearly all were still using that technology during the current readmission. Additional technologies were commonly added during the current hospitalization. Conclusion  Advanced strategies are needed to plan for hospital resource allocation for infants with chronic critical illness. These infants' prolonged hospitalizations begin in the neonatal ICU but often transition to other ICUs and general inpatient wards. They are commonly discharged with medical technology which is rarely weaned but often escalated during subsequent hospitalizations. Identification and tracking of these infants, beginning in the neonatal ICU, will help hospitals anticipate and strategize for inpatient bed management. Key Points 35% of inpatients with chronic critical illness are infants. Nearly 90% of these infants spend some time in an intensive care unit. 78% are discharged with medical technology. [ABSTRACT FROM AUTHOR]

The article highlights the critical role that the investigational drug services (IDS) pharmacist plays in ensuring safe medical practices for patients receiving investigational medications. Topics include current gaps in investigational drug practices, IDS work group recommendations, and IDS participation in use of interactive response technology (IRT).

Traumatic brain injury is a commonly diagnosed brain dysfunction in the United States. Although advancements in medical technology have improved diagnostic techniques, many cases of mild traumatic brain injuries (mTBI) remain undiagnosed. While medical imaging may provide researchers and medical professionals with evidence of secondary injuries, the only way to definitively diagnose mTBI is through post-mortem analysis. As interest regarding neural variations following mTBI increases, sport and blast-induced TBI have become the focal point of recent research. While these two forms of traumatic brain injury seem to differ, recent studies suggest sport-related TBI (sTBI) and blast-induced TBI (bTBI) share more commonalities than previously suspected. However, differing in pattern, neuropathological markers such as beta-amyloid (Aß) deposits and neurofibrillary tangles (NFTs) present in both sTBI and bTBI post-mortem samples. The neurocognitive deficits and long-term medical conditions associated with these two types of mTBI also appear to correspond. Primary differentiating factors of sport and blast-induced TBI include biomechanics. The addition of overpressure and neurochemical variations in bTBI cases may prove responsible for the presentation of PTSD in solely blast-induced cases. Although this meta-analysis suggests significant similarities between sport and blast-related mTBI, further advances in molecular and cellular neuroscience may introduce novel differentiating neuropathological markers. [ABSTRACT FROM AUTHOR]

Objectives: To enhance the generalizability of the evidence it reviews, the US Food and Drug Administration (FDA) has encouraged manufacturers to expand the submission of real-world evidence (RWE). The extent to which this evidence, which is generated outside of research settings, can support decision making remains unclear. We described the current use of RWE for medical devices, assessed manufacturers' challenges in generating and using it for regulatory and coverage decisions, and identified opportunities to expand its use.Methods: We conducted 27 solo and group interviews with FDA officials and representatives of device manufacturers, payers, and health technology assessment organizations. All interviews used a semistructured protocol and were transcribed to allow thematic analysis.Results: Accessing and linking real-world data sources, identifying unique devices, capturing longitudinal data, limited staff expertise, and uncertain return on investment have hampered efforts to use real-world data. Many companies in our sample were conducting research using real-world data, but none had submitted RWE as the primary evidence supporting a premarket approval. FDA guidance was helpful, but regulatory requirements remained ambiguous and examples of successful regulatory decisions based on RWE were limited. Payers mainly used RWE to supplement experimental evidence in coverage decisions, evaluated both types of evidence in similar ways, and had concerns about the rigor of RWE.Conclusions: Technical challenges may slow efforts to generate and use RWE in the near term. Additional regulatory guidance and examples, greater use of rigorous study designs and analytic methods, and continued stakeholder engagement could accelerate the use of RWE. [ABSTRACT FROM AUTHOR]