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Background: The concept of health equity by design encompasses a multifaceted approach that integrates actions aimed at eliminating biased, unjust, and correctable differences among groups of people as a fundamental element in the design of algorithms. As algorithmic tools are increasingly integrated into clinical practice at multiple levels, nurses are uniquely positioned to address challenges posed by the historical marginalization of minority groups and its intersections with the use of "big data" in healthcare settings; however, a coherent framework is needed to ensure that nurses receive appropriate training in these domains and are equipped to act effectively., Purpose: We introduce the Bias Elimination for Fair AI in Healthcare (BE FAIR) framework, a comprehensive strategic approach that incorporates principles of health equity by design, for nurses to employ when seeking to mitigate bias and prevent discriminatory practices arising from the use of clinical algorithms in healthcare. By using examples from a "real-world" AI governance framework, we aim to initiate a wider discourse on equipping nurses with the skills needed to champion the BE FAIR initiative., Methods: Drawing on principles recently articulated by the Office of the National Coordinator for Health Information Technology, we conducted a critical examination of the concept of health equity by design. We also reviewed recent literature describing the risks of artificial intelligence (AI) technologies in healthcare as well as their potential for advancing health equity. Building on this context, we describe the BE FAIR framework, which has the potential to enable nurses to take a leadership role within health systems by implementing a governance structure to oversee the fairness and quality of clinical algorithms. We then examine leading frameworks for promoting health equity to inform the operationalization of BE FAIR within a local AI governance framework., Results: The application of the BE FAIR framework within the context of a working governance system for clinical AI technologies demonstrates how nurses can leverage their expertise to support the development and deployment of clinical algorithms, mitigating risks such as bias and promoting ethical, high-quality care powered by big data and AI technologies., Conclusion and Relevance: As health systems learn how well-intentioned clinical algorithms can potentially perpetuate health disparities, we have an opportunity and an obligation to do better. New efforts empowering nurses to advocate for BE FAIR, involving them in AI governance, data collection methods, and the evaluation of tools intended to reduce bias, mark important steps in achieving equitable healthcare for all., (© 2024 The Author(s). Journal of Nursing Scholarship published by Wiley Periodicals LLC on behalf of Sigma Theta Tau International.)

We aimed to understand nursing informaticists' perspectives on key challenges, questions, and opportunities for the nursing profession as it prepares for an era of healthcare delivery enriched by artificial intelligence (AI). We found that nursing practice is currently, and will continue to be, directly influenced by AI in healthcare. Educating and training nurses so that they may safely and effectively use AI in their clinical practice and engage in implementation planning and evaluation will help overcome predicted challenges. Defining the key tenets of AI literacy for nurses and re-envisioning nursing models of care in the context of AI-enriched healthcare are important next steps for nursing informaticists. If embraced, AI has the potential to support the existing nursing workforce in the context of major shortages and augment the safe and high-quality care that nurses can deliver.

Circadian rhythm (CR) dysregulation negatively impacts health and contributes to mental disorders. The role of melatonin, a hormone intricately linked to CR, is still a subject of active study. The enzyme arylalkylamine N-acetyltransferase (AANAT) is responsible for melatonin synthesis, and it is a potential target for disorders that involve abnormally high melatonin levels, such as seasonal affective disorder (SAD). Current AANAT inhibitors suffer from poor cell permeability, selectivity, and/or potency. To address the latter, we have employed an X-ray crystal-based model to guide the modification of a previously described AANAT inhibitor, containing a rhodanine-indolinone core. We made various structural modifications to the core structure, including testing the importance of a carboxylic acid group thought to bind in the CoA site, and we evaluated these changes using MD simulations in conjunction with enzymatic assay data. Additionally, we tested three AANAT inhibitors in a zebrafish locomotion model to determine their effects in vivo. Key discoveries were that potency could be modestly improved by replacing a 5-carbon alkyl chain with rings and that the central rhodanine ring could be replaced by other heterocycles and maintain potency., (© 2023 Wiley-VCH GmbH.)

Artificial intelligence/machine learning models are being rapidly developed and used in clinical practice. However, many models are deployed without a clear understanding of clinical or operational impact and frequently lack monitoring plans that can detect potential safety signals. There is a lack of consensus in establishing governance to deploy, pilot, and monitor algorithms within operational healthcare delivery workflows. Here, we describe a governance framework that combines current regulatory best practices and lifecycle management of predictive models being used for clinical care. Since January 2021, we have successfully added models to our governance portfolio and are currently managing 52 models., (© The Author(s) 2022. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

Background: Documentation burden associated with electronic health records (EHR) is well documented in the literature. Usability and functionality of the EHR are considered fragmented and disorganized making it difficult to synthesize clinical information. Few best practices are reported in the literature to support streamlining the configuration of documentation fields to align clinical workflow with EHR data entry elements., Objective: The primary objective was to improve performance, reduce duplication, and remove nonvalue-added tasks by redesigning the patient assessment template in the EHR using best practice approaches., Methods: A quality improvement approach and pre-/postdesign was used to implement and evaluate best approaches to redesign standardized flowsheet documentation workflow. We implemented standards for usability modifications targeting efficiency, reducing redundancy, and improving workflow navigation. The assessment type row was removed; a reassessment section was added to the first three flowsheet rows and documentation practices were revised to document changes from the initial assessment by selecting the corresponding body system from the dropdown menu. Vendor-supplied timestamp data were used to evaluate documentation times. Video motion-time recording was used to capture click and scroll burden, defined as steps in documentation, and was analyzed using the Keystrok Level Model., Results: This study's results included an 18.5% decreased time in the EHR; decrease of 7 to 12% of total time in flowsheets; time savings of 1.5 to 6.5 minutes per reassessment per patient; and a decrease of 88 to 97% in number of steps to perform reassessment documentation., Conclusion: Workflow redesign to improve the usability and functionality decreased documentation time, redundancy, and click burden resulting in improved productivity. The time savings correlate to several hours per 12-hour shift which could be reallocated to value-added patient care activities. Revising documentation practices in alignment with redesign benefits staff by decreasing workload, improving quality, and satisfaction., Competing Interests: None declared., (Thieme. All rights reserved.)

The role of adipose tissue (AT) inflammation in AT function in humans is unclear. We tested whether AT macrophage (ATM) content, cytokine gene expression, and senescent cell burden (markers of AT inflammation) predict AT insulin resistance measured as the insulin concentration that suppresses lipolysis by 50% (IC50). We studied 86 volunteers with normal weight or obesity at baseline and a subgroup of 25 volunteers with obesity before and after weight loss. There was a strong positive relationship between IC50 and abdominal subcutaneous and femoral fat cell size (FCS). The positive, univariate relationships between IC50 and abdominal AT inflammatory markers CD68, CD14, CD206 ATM/100 adipocytes, senescent cells, IL-6, and TNF-α mRNA were not significant after adjustment for FCS. A 10% weight loss significantly reduced IC50; however, there was no reduction in adipose ATM content, senescent cells, or cytokine gene expression. Our study suggests that commonly used markers of AT inflammation are not causally linked to AT insulin resistance, whereas FCS is a strong predictor of AT insulin resistance with respect to lipolysis., (© 2022 by the American Diabetes Association.)

One photon up-conversion photoluminescence is an optical phenomenon whereby the thermal energy of a fluorescent material increases the energy of an emitted photon compared with the energy of the photon that was absorbed. When this occurs with near unity efficiency, the emitting material undergoes a net decrease in temperature, so-called optical cooling. Because the up-conversion mechanism is thermally activated, the yield of up-converted photoluminescence is also a reporter of the temperature of the emitter. Taking advantage of this optical signature, cesium lead trihalide nanocrystals are shown to cool during the up-conversion of 532 nm CW laser excitation. Raman thermometric analysis of a substrate on which the nanocrystals were deposited further verifies the decrease in the local environmental temperature by as much as 25 °C during optical pumping. This is the first demonstration of optical cooling driven by colloidal semiconductor nanocrystal up-conversion.

BACKGROUND After a hospital stay, many older adults rely on their caregivers for assistance at home. Empirical evidence demonstrates that caregiver support programs in hospital-to-home transitions are associated with favorable caregiver and patient outcomes. We tested the feasibility of implementing the Duke Elder Family/Caregiver Training (DEFT) program in an academic medical center. METHODS: We recruited adult caregivers of homebound patients who were aged 55 years or older from Duke University Hospital in Durham, North Carolina. Caregivers attended a face-to-face caregiver training and received two telephone checks after hospital discharge with DEFT services ending at 14 days of hospital discharge. We used a one-item survey to measure overall DEFT satisfaction. We also monitored 30-day readmissions of patients whose caregivers completed the DEFT program. RESULTS: The DEFT Center received 104 consult orders in six months. Of these, 61 agreed to participate but nine caregivers were unable to schedule the DEFT training and three decided to eventually withdraw from participation. Forty-nine caregivers received the DEFT training, 12 of whom were ineligible to continue because of change in patients' disposition plan. Of the remaining 37 caregivers, 15 completed the full program and reported high satisfaction; one patient was readmitted within 30 days of discharge. LIMITATIONS: The DEFT implementation was based on academic-medical partnership and relied on electronic medical records for consult and documentation. Replicability and generalizability of findings are limited to settings with similar capabilities and resources. CONCLUSION: The implementation of a caregiver training and support program in an academic medical center was feasible and was associated with favorable preliminary outcomes., (©2020 by the North Carolina Institute of Medicine and The Duke Endowment. All rights reserved.)

Background: Secondary use of electronic health record (EHR) data can reduce costs of research and quality reporting. However, EHR data must be consistent within and across organizations. Flowsheet data provide a rich source of interprofessional data and represents a high volume of documentation; however, content is not standardized. Health care organizations design and implement customized content for different care areas creating duplicative data that is noncomparable. In a prior study, 10 information models (IMs) were derived from an EHR that included 2.4 million patients. There was a need to evaluate the generalizability of the models across organizations. The pain IM was selected for evaluation and refinement because pain is a commonly occurring problem associated with high costs for pain management., Objective: The purpose of our study was to validate and further refine a pain IM from EHR flowsheet data that standardizes pain concepts, definitions, and associated value sets for assessments, goals, interventions, and outcomes., Methods: A retrospective observational study was conducted using an iterative consensus-based approach to map, analyze, and evaluate data from 10 organizations., Results: The aggregated metadata from the EHRs of 8 large health care organizations and the design build in 2 additional organizations represented flowsheet data from 6.6 million patients, 27 million encounters, and 683 million observations. The final pain IM has 30 concepts, 4 panels (classes), and 396 value set items. Results are built on Logical Observation Identifiers Names and Codes (LOINC) pain assessment terms and extend the need for additional terms to support interoperability., Conclusion: The resulting pain IM is a consensus model based on actual EHR documentation in the participating health systems. The IM captures the most important concepts related to pain., Competing Interests: None., (Schattauer GmbH Stuttgart.)

Colorectal cancer is the third most common cancer worldwide, with 1.2 million patients diagnosed annually. In late-stage colorectal cancer, the most commonly used targeted therapies are the monoclonal antibodies cetuximab and panitumumab, which prevent epidermal growth factor receptor (EGFR) activation. Recent studies have identified alterations in KRAS and other genes as likely mechanisms of primary and secondary resistance to anti-EGFR antibody therapy. Despite these efforts, additional mechanisms of resistance to EGFR blockade are thought to be present in colorectal cancer and little is known about determinants of sensitivity to this therapy. To examine the effect of somatic genetic changes in colorectal cancer on response to anti-EGFR antibody therapy, here we perform complete exome sequence and copy number analyses of 129 patient-derived tumour grafts and targeted genomic analyses of 55 patient tumours, all of which were KRAS wild-type. We analysed the response of tumours to anti-EGFR antibody blockade in tumour graft models and in clinical settings and functionally linked therapeutic responses to mutational data. In addition to previously identified genes, we detected mutations in ERBB2, EGFR, FGFR1, PDGFRA, and MAP2K1 as potential mechanisms of primary resistance to this therapy. Novel alterations in the ectodomain of EGFR were identified in patients with acquired resistance to EGFR blockade. Amplifications and sequence changes in the tyrosine kinase receptor adaptor gene IRS2 were identified in tumours with increased sensitivity to anti-EGFR therapy. Therapeutic resistance to EGFR blockade could be overcome in tumour graft models through combinatorial therapies targeting actionable genes. These analyses provide a systematic approach to evaluating response to targeted therapies in human cancer, highlight new mechanisms of responsiveness to anti-EGFR therapies, and delineate new avenues for intervention in managing colorectal cancer.

Massively parallel sequencing approaches are beginning to be used clinically to characterize individual patient tumors and to select therapies based on the identified mutations. A major question in these analyses is the extent to which these methods identify clinically actionable alterations and whether the examination of the tumor tissue alone is sufficient or whether matched normal DNA should also be analyzed to accurately identify tumor-specific (somatic) alterations. To address these issues, we comprehensively evaluated 815 tumor-normal paired samples from patients of 15 tumor types. We identified genomic alterations using next-generation sequencing of whole exomes or 111 targeted genes that were validated with sensitivities >95% and >99%, respectively, and specificities >99.99%. These analyses revealed an average of 140 and 4.3 somatic mutations per exome and targeted analysis, respectively. More than 75% of cases had somatic alterations in genes associated with known therapies or current clinical trials. Analyses of matched normal DNA identified germline alterations in cancer-predisposing genes in 3% of patients with apparently sporadic cancers. In contrast, a tumor-only sequencing approach could not definitively identify germline changes in cancer-predisposing genes and led to additional false-positive findings comprising 31% and 65% of alterations identified in targeted and exome analyses, respectively, including in potentially actionable genes. These data suggest that matched tumor-normal sequencing analyses are essential for precise identification and interpretation of somatic and germline alterations and have important implications for the diagnostic and therapeutic management of cancer patients., (Copyright © 2015, American Association for the Advancement of Science.)

This study aims to explore mental health literacy, specifically focusing on depression, among Southeast Asian (SEA) elderly refugees residing in the Twin Cities of St. Paul and Minneapolis, Minnesota. Three focus groups were held with nine mental health professionals who work with SEA elders. Jorm's mental health literacy framework guided the study theoretically. For data analysis, grounded theory was employed by utilizing MAX QDA2. Four themes emerged from the analysis: 1) lack of knowledge about specific mental disorders, 2) culture-specific knowledge and beliefs on the causes of depression, 3) lack of awareness about professional help, and 4) cultural attitudes toward seeking mental health services. The findings indicated that cultural beliefs of SEA elders impact their ability to understand, recognize, and respond to depression. Barriers to treatment were identified and recommendations were made to reduce mental health disparity in this elderly population.

Traditional implementation of clinical information systems follows a predictable project management process. The selection, development, implementation, and evaluation of the system and the project management aspects of those phases require considerable time and effort. The purpose of this paper is to describe the beta site implementation of a knowledge-based clinical information system in a specialty area of a southeastern hospital that followed a less than traditional approach to implementation. Highlighted are brief descriptions of the hospital's traditional process, the nontraditional process, and key findings from the experience. Preliminary analysis suggests that selection of an implementation process is contextual. Selection of elements from each of these methods may provide a more useful process. The non-traditional process approached the elements of communication, areas of responsibility, training, follow-up and leadership differently. These elements are common to both processes and provide a focal point for future research.

This article describes a survey feedback intervention in which staff nurses were surveyed about various job characteristics, job satisfaction, and intent to remain in the organization. Nurse managers received the feedback through graphs and a workshop. A year later the same survey was conducted, and the results were compared with preintervention data. Of the 13 units surveyed, six showed significant improvement in one area and one showed significant improvement in 11. Nurse managers considered the survey feedback helpful, but the feedback alone was not sufficient for achieving broad changes in 1 year. However, the feedback is a useful component of continuous quality improvement efforts.

An unusual case of discontinuous hard tissue hyperostosis is described in a 25-30-year-old female dating between 4000 and 5500 BP from northern Chile. This specimen was one of 104 individuals examined from the Morro-1 site, which is known to represent the Chinchorro culture. The only other reported case from antiquity dates to 500 AD (Lester [1969] J. Bone Joint Surg. [Am.] 49:142-143). A review and comparison of this case to the medical literature supports a diagnosis of melorheostosis. Differential diagnosis is presented with the ruling out of nonspecific manifestations of osteomyelitis/periostitis as the most likely alternative diagnosis.