Early childhood (1-5 years) obesity prevention: A systematic review of family-based multicomponent behavioral interventions.

INTRODUCTION: Globally 38.9 million children under age 5 have overweight or obesity, leading to type 2 diabetes, cardiovascular complications, depression, and poor educational outcomes. Obesity is difficult to reverse and lifestyle behaviors (healthy or unhealthy) can persist from 1.5 years of age. Targeting caregivers to help address modifiable behaviors may offer a viable solution. OBJECTIVE: Evaluate the impact of multicomponent family interventions on weight-based outcomes in early childhood and explore related secondary behavior outcomes. METHODS: Four databases were searched (1/2017-6/2022) for randomized controlled trials (RCTs) of obesity-prevention interventions for children (1-5 years). Eligible studies included an objectively measured weight-based outcome, family interventions targeting the caregiver or family, and interventions including at least two behavioral components of nutrition, physical activity, or sleep. RESULTS: Eleven interventions were identified consisting of four delivery modes: self-guided (n = 3), face-to-face group instruction (n = 3), face-to-face home visits (n = 2), and multiple levels of influence (n = 3). The reviewed studies reported almost no significant effects on child weight-based outcomes. Only two studies (one was an underpowered pilot study) resulted in significant positive child weight-management outcomes. Seven of the interventions significantly improved children's dietary intake. CONCLUSION: Except for one, the reviewed studies reported that family based interventions had no significant effects on child weight-based outcomes. Future studies of this type should include measurements of age and sex-based body mass index (BMI) and trajectories, and also examine other important benefits to the children and families.

Emergency Department Discharge Teaching Interventions: A Scoping Review.

INTRODUCTION: Emergency department discharge education is intended to provide patients with information to self-manage their condition or injury, identify potential complications, and follow-up or referral. However, most patients cannot recall the discharge information provided, leading to adverse clinical outcomes, return visits, and higher costs. A scoping review was undertaken to explore discharge education interventions that have been studied in the emergency department setting and outcomes that have been used to evaluate the effectiveness of the interventions. METHODS: A literature review was conducted using the databases PubMed/Medline, Cumulative Index to Nursing and Allied Health Literature, and Education Resources Information Center, with search terms focused on emergency nursing and patient discharge education interventions. RESULTS: Of the publications identified, 18 studies met the inclusion criteria. There was variation among studies on the conditions/injuries and populations of focus for the intervention. The interventions were categorized by learning styles, including auditory (n=10), kinesthetic (n=1), visual (n=15), reading/writing (n=1), and multimodal (n=7). Outcomes evaluated included those that were patient-specific (education, self-management, clinical, and adherence) and metrics of the health system and public health. DISCUSSION: Multimodal discharge education that addresses various learning styles and levels of health literacy improved patient education, self-management, and clinical outcomes. Additional support and reminders improved patient adherence. Identified gaps included limited kinesthetic interventions and culturally tailored education. Translational science for advancing sustainable interventions in clinical practice is needed to enhance the emergency department discharge process and patient, system, and public health outcomes.

Examining Care Planning Efficiency and Clinical Decision Support Adoption in a System Tailoring to Nurses' Graph Literacy: National, Web-Based Randomized Controlled Trial.

BACKGROUND: The proliferation of health care data in electronic health records (EHRs) is fueling the need for clinical decision support (CDS) that ensures accuracy and reduces cognitive processing and documentation burden. The CDS format can play a key role in achieving the desired outcomes. Building on our laboratory-based pilot study with 60 registered nurses (RNs) from 1 Midwest US metropolitan area indicating the importance of graph literacy (GL), we conducted a fully powered, innovative, national, and web-based randomized controlled trial with 203 RNs. OBJECTIVE: This study aimed to compare care planning time (CPT) and the adoption of evidence-based CDS recommendations by RNs randomly assigned to 1 of 4 CDS format groups: text only (TO), text+table (TT), text+graph (TG), and tailored (based on the RN's GL score). We hypothesized that the tailored CDS group will have faster CPT (primary) and higher adoption rates (secondary) than the 3 nontailored CDS groups. METHODS: Eligible RNs employed in an adult hospital unit within the past 2 years were recruited randomly from 10 State Board of Nursing lists representing the 5 regions of the United States (Northeast, Southeast, Midwest, Southwest, and West) to participate in a randomized controlled trial. RNs were randomly assigned to 1 of 4 CDS format groups-TO, TT, TG, and tailored (based on the RN's GL score)-and interacted with the intervention on their PCs. Regression analysis was performed to estimate the effect of tailoring and the association between CPT and RN characteristics. RESULTS: The differences between the tailored (n=46) and nontailored (TO, n=55; TT, n=54; and TG, n=48) CDS groups were not significant for either the CPT or the CDS adoption rate. RNs with low GL had longer CPT interacting with the TG CDS format than the TO CDS format (P=.01). The CPT in the TG CDS format was associated with age (P=.02), GL (P=.02), and comfort with EHRs (P=.047). Comfort with EHRs was also associated with CPT in the TT CDS format (P<.001). CONCLUSIONS: Although tailoring based on GL did not improve CPT or adoption, the study reinforced previous pilot findings that low GL is associated with longer CPT when graphs were included in care planning CDS. Higher GL, younger age, and comfort with EHRs were associated with shorter CPT. These findings are robust based on our new innovative testing strategy in which a diverse national sample of RN participants (randomly derived from 10 State Board of Nursing lists) interacted on the web with the intervention on their PCs. Future studies applying our innovative methodology are recommended to cost-effectively enhance the understanding of how the RN's GL, combined with additional factors, can inform the development of efficient CDS for care planning and other EHR components before use in practice.

Efficacy, Use, and Usability of the VIP-HANA App for Symptom Self-management in PLWH with HANA Conditions.

The purpose of this study was to evaluate the efficacy of the VIP-HANA application (app) for improving symptom burden in a randomized control trial of 100 people living with HIV (PLWH) who have non-AIDS conditions associated with HIV. The intervention group received the VIP-HANA app which allowed them to report their symptoms every week and receive self-management strategies tailored to their symptoms. The control arm received an app to report their symptoms every week but did not receive any strategies. The results of our study suggest that symptom burden improved in the participants of both study arms. Although these findings do not support the efficacy of VIP-HANA in improving symptom burden in PLWH who have HIV-associated non-AIDS (HANA) conditions, this could be a function of the study design. Findings suggest that PLWH are interested in monitoring their symptoms, which could have implications for the wider use of digital health for patient surveillance.

RESUMEN: El propósito de este estudio fue evaluar la eficacia de la aplicación VIP-HANA para mejorar la carga de síntomas en una prueba controlada aleatorizada de 100 personas que viven con VIH con condiciones no de SIDA asociadas al VIH. El grupo de intervención recibió la aplicación VIP-HANA que les permitió reportar sus síntomas cada semana y recibir estrategias de autogestión personalizadas. El brazo de control recibió una aplicación para reportar sus síntomas cada semana, pero no recibió ninguna estrategia. Los resultados de nuestro estudio sugieren que la carga general de los síntomas mejoro entre los participantes en ambos brazos del estudio. Aunque estos hallazgos no apoyan la eficacia de la aplicación VIP-HANA para mejorar la carga de síntomas en PVVS con condiciones de HANA, esto puede ser una función del diseño del estudio. Estos hallazgos sugieren que PVVS están interesados en monitorear sus síntomas, lo que puede tener implicaciones para el uso más amplio de salud digital para la vigilancia de pacientes.

Factors Related to Biological Sex Differences in Engagement with Healthcare Providers in Persons Living with HIV.

Little is known about how engagement with healthcare providers mediates the relationship between psychosocial factors (anxiety, depression, stigma) and medication adherence among persons living with HIV (PLWH). Moreover, little research has investigated potential biological sex differences in this relationship. We conducted a secondary analysis of data collected from four projects (N = 281) focused on improving health outcomes in PLWH. Males displayed (a) negative association between depression and engagement with healthcare providers (ß = - 0.02, z = - 3.20, p = 0.001) and (b) positive association between engagement with healthcare providers and medication adherence (ß = 0.55, OR = 1.73, z = 2.62, p = 0.009). Females showed no association between any of these factors. Anxiety and stigma were not significantly associated with medication adherence. Path analysis modeling for males had a very good fit (CFI = 1, TLI = 1, RMSEA = 0); none of the regression coefficients was significant for females. The significant relationship between depression and medication adherence among males was fully mediated by engagement with healthcare providers. Findings suggest that adherence interventions for PLWH should be tailored by biological sex.

Usability of a Consumer Health Informatics Tool Following Completion of a Clinical Trial: Focus Group Study.

BACKGROUND: Mobile health (mHealth) apps have the potential to be effective tools for encouraging patients with chronic diseases to self-manage their health. The success of mHealth apps is related to technology acceptance and its subsequent use by intended consumers. Therefore, it is essential to gain insights from consumers' perspectives about their use of mHealth apps in daily life. OBJECTIVE: The purpose of this work was to understand consumers' perspectives on use of a self-management app following completion of a clinical trial that tested the efficacy of the app for improving health outcomes. METHODS: We conducted five focus groups with paricipants of a clinical trial (NCT03182738) who were randomized to use the video information provider (VIP) for HIV-associated nonAIDS (HANA) conditions app (VIP-HANA) or an attention control app. Thematic analysis was conducted, and the themes were organized according to the two key constructs of the technology acceptance model framework: perceived usefulness and perceived ease of use. RESULTS: Thirty-nine people living with HIV (20 from the intervention group and 19 from the control group) participated in the focus group sessions. Of the eight themes identified from focus group data, the five themes related to perceived usefulness were: (1) self-monitoring HIV-related symptoms of HANA conditions, (2) enhanced relationship with clinical providers, (3) improvement in physical and emotional health, (4) long-term impact of self-care strategies on improvement in symptoms of HANA conditions, and (5) inspired lifestyle changes to manage symptoms. The three themes related to perceived ease of use were: (1) easy to navigate, (2) avatar personalization, and (3) privacy/confidentiality maintained even when changing the location of app use. CONCLUSIONS: Perceived ease of use was similar in both study groups but perceived usefulness differed between study groups. Participants in both study groups found the VIP-HANA app to be useful in monitoring their symptoms and enhancing communication with their clinical care providers. However, only intervention group participants perceived the app to be useful in improving overall health and long-term symptom management. Findings from this study highlight factors that are essential to ensure the usefulness of self-management apps and facilitate sustained use of mHealth apps for people living with chronic illnesses.

Nurse practitioner-physician comanagement of primary care patients: The promise of a new delivery care model to improve quality of care.

BACKGROUND: The U.S. primary care system is under tremendous strain to deliver care to an increased volume of patients with a concurrent primary care physician shortage. Nurse practitioner (NP)-physician comanagement of primary care patients has been proposed by some policy makers to help alleviate this strain. To date, no collective evidence demonstrates the effects of NP-physician comanagement in primary care. PURPOSE: This is the first review to synthesize all available studies that compare the effects of NP-physician comanagement to an individual physician managing primary care. METHODS: The PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-analyses) framework guided the conduct of this systematic review. Five electronic databases were searched. Titles, abstracts, and full texts were reviewed, and inclusion/exclusion criteria were applied to narrow search results to eligible studies. Quality appraisal was performed using Downs and Black's quality checklist for randomized and nonrandomized studies. RESULTS: Six studies were identified for synthesis. Three outcome categories emerged: (a) primary care provider adherence to recommended care guidelines, (b) empirical changes in clinical patient outcomes, and (c) patient/caregiver quality of life. Significantly more recommended care guidelines were completed with NP-physician comanagement. There was variability of clinical patient outcomes with some findings favoring the comanagement model. Limited differences in patient quality of life were found. Across all studies, the NP-physician comanagementcare delivery model was determined to produce no detrimental effect on measured outcomes and, in some cases, was more beneficial in reaching practice and clinical targets. PRACTICE IMPLICATIONS: The use of NP-physician comanagement of primary care patients is a promising delivery care model to improve the quality of care delivery and alleviate organizational strain given the current demands of increased patient panel sizes and primary care physician shortages. Future research should focus on NP-physician interactions and processes to isolate the attributes of a successful NP-physician comanagement model.

Mobile Health Technology for Improving Symptom Management in Low Income Persons Living with HIV.

Persons living with HIV (PLWH) are living longer but experiencing more adverse symptoms associated with the disease and its treatment. This study aimed to examine the impact of a mHealth application (app) comprised of evidence-based self-care strategies on the symptom experience of PLWH. We conducted a 12-week feasibility study with 80 PLWH who were randomized (1:1) to a mHealth app, mobile Video Information Provider (mVIP), with self-care strategies for improving 13 commonly experienced symptoms in PLWH or to a control app. Intervention group participants showed a significantly greater improvement than the control group in 5 symptoms: anxiety (p = 0.001), depression (p = 0.001), neuropathy (p = 0.002), fever/chills/sweat (p = 0.037), and weight loss/wasting (p = 0.020). Participants in the intervention group showed greater improvement in adherence to their antiretroviral medications (p = 0.017) as compared to those in the control group. In this 12-week trial, mVIP was associated with improved symptom burden and increased medication adherence in PLWH.

A multi-level usability evaluation of mobile health applications: A case study.

OBJECTIVE: To report a methodological approach for the development of a usable mHealth application (app). MATERIALS AND METHODS: This work was guided by a 3-level stratified view of health information technology (IT) usability evaluation framework. We first describe a number of methodologies for operationalizing each level of the framework. Following the description of each methodology, we present a case study which illustrates the use of our preferred methodologies for the development of a mHealth app. At level 1 (user-task), we applied a card sorting technique to guide the information architecture of a mobile HIV symptom self-management app, entitled mVIP. At level 2 (user-task-system), we conducted a usability evaluation of mVIP in a laboratory setting through end-user usability testing and heuristic evaluation with informatics experts. At level 3 (user-task-system-environment), usability of mVIP was evaluated in a real-world setting following the use of the app during a 3-month trial. RESULTS: The 3-level usability evaluation guided our work exploring in-depth interactions between the user, task, system, and environment. Integral to the findings from the 3-level usability evaluation, we iteratively refined the app's content, functionality, and interface to meet the needs of our intended end-users. DISCUSSION AND CONCLUSION: The stratified view of the health IT usability evaluation framework is a useful methodological approach for the design, development, and evaluation of mHealth apps. The methodological recommendations for using the theoretical framework can inform future usability studies of mHealth apps.

Introduction of a bacterial acetyl-CoA synthesis pathway improves lactic acid production in Saccharomyces cerevisiae.

Acid-tolerant Saccharomyces cerevisiae was engineered to produce lactic acid by expressing heterologous lactate dehydrogenase (LDH) genes, while attenuating several key pathway genes, including glycerol-3-phosphate dehydrogenase1 (GPD1) and cytochrome-c oxidoreductase2 (CYB2). In order to increase the yield of lactic acid further, the ethanol production pathway was attenuated by disrupting the pyruvate decarboxylase1 (PDC1) and alcohol dehydrogenase1 (ADH1) genes. Despite an increase in lactic acid yield, severe reduction of the growth rate and glucose consumption rate owing to the absence of ADH1 caused a considerable decrease in the overall productivity. In Δadh1 cells, the levels of acetyl-CoA, a key precursor for biologically applicable components, could be insufficient for normal cell growth. To increase the cellular supply of acetyl-CoA, we introduced bacterial acetylating acetaldehyde dehydrogenase (A-ALD) enzyme (EC 1.2.1.10) genes into the lactic acid-producing S. cerevisiae. Escherichia coli-derived A-ALD genes, mhpF and eutE, were expressed and effectively complemented the attenuated acetaldehyde dehydrogenase (ALD)/acetyl-CoA synthetase (ACS) pathway in the yeast. The engineered strain, possessing a heterologous acetyl-CoA synthetic pathway, showed an increased glucose consumption rate and higher productivity of lactic acid fermentation. The production of lactic acid was reached at 142g/L with production yield of 0.89g/g and productivity of 3.55gL(-1)h(-1) under fed-batch fermentation in bioreactor. This study demonstrates a novel approach that improves productivity of lactic acid by metabolic engineering of the acetyl-CoA biosynthetic pathway in yeast.

Use of Electronic Health Records and Documentation Burden Among Nurses in Acute and Critical Care.

Nurses who provide the majority of hands-on care for hospitalized patients are disproportionately affected by the current state of electronic health records (EHRs), and little is known about their lived perception of EHR use. Using a mixed-methods research design, we conducted an in-depth analysis and synthesis of data from EHR usage log files, interviews, and surveys and assessed factors contributing to the nurse documentation burden in acute and critical at a large academic medical center. There remain substantial spaces where we can develop viable solutions for enhancing the usability of multi-component EHR systems.

Demographics, Trends, and Clinical Characteristics of HIV Pre-Exposure Prophylaxis Recipients and People Newly Diagnosed with HIV from Large Electronic Health Records in Florida.

Florida is one of the HIV epicenters with high incidence and marked sociodemographic disparities. We analyzed a decade of statewide electronic health record/claims data-OneFlorida+-to identify and characterize pre-exposure prophylaxis (PrEP) recipients and newly diagnosed HIV cases in Florida. Refined computable phenotype algorithms were applied and a total of 2186 PrEP recipients and 7305 new HIV diagnoses were identified between January 2013 and April 2021. We examined patients' sociodemographic characteristics, stratified by self-reported sex, along with both frequency-driven and expert-selected descriptions of clinical conditions documented within 12 months before the first PrEP use or HIV diagnosis. PrEP utilization rate increased in both sexes; higher rates were observed among males with sex differences widening in recent years. HIV incidence peaked in 2016 and then decreased with minimal sex differences observed. Clinical characteristics were similar between the PrEP and new HIV diagnosis cohorts, characterized by a low prevalence of sexually transmitted infections (STIs) and a high prevalence of mental health and substance use conditions. Study limitations include the overrepresentation of Medicaid recipients, with over 96% of female PrEP users on Medicaid, and the inclusion of those engaged in regular health care. Although PrEP uptake increased in Florida, and HIV incidence decreased, sex disparity among PrEP recipients remained. Screening efforts beyond individuals with documented prior STI and high-risk behavior, especially for females, including integration of mental health care with HIV counseling and testing, are crucial to further equalize PrEP access and improve HIV prevention programs.

The use of artificial intelligence for graduate nursing education: An educational evaluation.

ABSTRACT: 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.

A rapid review on current and potential uses of large language models in nursing.

BACKGROUND: The application of large language models across commercial and consumer contexts has grown exponentially in recent years. However, a gap exists in the literature on how large language models can support nursing practice, education, and research. This study aimed to synthesize the existing literature on current and potential uses of large language models across the nursing profession. METHODS: A rapid review of the literature, guided by Cochrane rapid review methodology and PRISMA reporting standards, was conducted. An expert health librarian assisted in developing broad inclusion criteria to account for the emerging nature of literature related to large language models. Three electronic databases (i.e., PubMed, CINAHL, and Embase) were searched to identify relevant literature in August 2023. Articles that discussed the development, use, and application of large language models within nursing were included for analysis. RESULTS: The literature search identified a total of 2028 articles that met the inclusion criteria. After systematically reviewing abstracts, titles, and full texts, 30 articles were included in the final analysis. Nearly all (93 %; n = 28) of the included articles used ChatGPT as an example, and subsequently discussed the use and value of large language models in nursing education (47 %; n = 14), clinical practice (40 %; n = 12), and research (10 %; n = 3). While the most common assessment of large language models was conducted by human evaluation (26.7 %; n = 8), this analysis also identified common limitations of large language models in nursing, including lack of systematic evaluation, as well as other ethical and legal considerations. DISCUSSION: This is the first review to summarize contemporary literature on current and potential uses of large language models in nursing practice, education, and research. Although there are significant opportunities to apply large language models, the use and adoption of these models within nursing have elicited a series of challenges, such as ethical issues related to bias, misuse, and plagiarism. CONCLUSION: Given the relative novelty of large language models, ongoing efforts to develop and implement meaningful assessments, evaluations, standards, and guidelines for applying large language models in nursing are recommended to ensure appropriate, accurate, and safe use. Future research along with clinical and educational partnerships is needed to enhance understanding and application of large language models in nursing and healthcare.

Navigating the Global Landscape of Nursing Informatics Research Collaboration: A Blueprint for Success.

International collaboration is crucial in the field of nursing informatics research to enhance our ability to conduct globally relevant research that informs policy and practice. In this case study we describe how we have established an international research collaboration to evaluate nurses' experiences of technology use during the pandemic. We firstly describe how the collaboration was created and the successes associated with our work, before highlighting the facilitators to make an international collaboration work. We also discuss the challenges we have encountered during this collaborative enterprise, to enable other researchers who wish to establish international collaborations and learn from our experiences.

Efficacy of an mHealth self-management intervention for persons living with HIV: the WiseApp randomized clinical trial.

IMPORTANCE: Progression of HIV disease, the transmission of the disease, and premature deaths among persons living with HIV (PLWH) have been attributed foremost to poor adherence to HIV medications. mHealth tools can be used to improve antiretroviral therapy (ART) adherence in PLWH and have the potential to improve therapeutic success. OBJECTIVE: To determine the efficacy of WiseApp, a user-centered design mHealth intervention to improve ART adherence and viral suppression in PLWH. DESIGN, SETTING, AND PARTICIPANTS: A randomized (1:1) controlled efficacy trial of the WiseApp intervention arm (n = 99) versus an attention control intervention arm (n = 101) among persons living with HIV who reported poor adherence to their treatment regimen and living in New York City. INTERVENTIONS: The WiseApp intervention includes the following components: testimonials of lived experiences, push-notification reminders, medication trackers, health surveys, chat rooms, and a "To-Do" list outlining tasks for the day. Both study arms also received the CleverCap pill bottle, with only the intervention group linking the pill bottle to WiseApp. RESULTS: We found a significant improvement in ART adherence in the intervention arm compared to the attention control arm from day 1 (69.7% vs 48.3%, OR = 2.5, 95% CI 1.4-3.5, P = .002) to day 59 (51.2% vs 37.2%, OR = 1.77, 95% CI 1.0-1.6, P = .05) of the study period. From day 60 to 120, the intervention arm had higher adherence rates, but the difference was not significant. In the secondary analyses, no difference in change from baseline to 3 or 6 months between the 2 arms was observed for all secondary outcomes. CONCLUSIONS: The WiseApp intervention initially improved ART adherence but did not have a sustained effect on outcomes.

Do Walk Step Reminders Improve Physical Activity in Persons Living With HIV in New York City?-Results From a Randomized Clinical Trial.

ABSTRACT: Supervised physical activity can increase functional capacity in persons with HIV (PWH); however, aerobic interventions have shown little improvement in overall physical activity in PWH. In response, we sought to assess the effect of wearing a fitness tracker (FitBit) paired with walk step reminders delivered through an mHealth application to improve physical activity and decreasing body mass index among PWH in New York City. There was no significant difference in the frequency of walk steps between participants in the control group and intervention group from baseline to 6-month follow-up. These findings show that walk step reminders alone were inadequate for sustained improvement of physical activity. This study highlights the need to develop and test the comparative efficacy of physical activity interventions that are tailored to the unique needs and capabilities of PWH. Future interventions should incorporate fitness tracking with tailored interventions focused on the promotion of physical activity.Clinical Trials.Gov Registration number: NCT03205982.

The relationship between electronic health records user interface features and data quality of patient clinical information: an integrative review.

OBJECTIVES: Electronic health records (EHRs) user interfaces (UI) designed for data entry can potentially impact the quality of patient information captured in the EHRs. This review identified and synthesized the literature evidence about the relationship of UI features in EHRs on data quality (DQ). MATERIALS AND METHODS: We performed an integrative review of research studies by conducting a structured search in 5 databases completed on October 10, 2022. We applied Whittemore & Knafl's methodology to identify literature, extract, and synthesize information, iteratively. We adapted Kmet et al appraisal tool for the quality assessment of the evidence. The research protocol was registered with PROSPERO (CRD42020203998). RESULTS: Eleven studies met the inclusion criteria. The relationship between 1 or more UI features and 1 or more DQ indicators was examined. UI features were classified into 4 categories: 3 types of data capture aids, and other methods of DQ assessment at the UI. The Weiskopf et al measures were used to assess DQ: completeness (n = 10), correctness (n = 10), and currency (n = 3). UI features such as mandatory fields, templates, and contextual autocomplete improved completeness or correctness or both. Measures of currency were scarce. DISCUSSION: The paucity of studies on UI features and DQ underscored the limited knowledge in this important area. The UI features examined had both positive and negative effects on DQ. Standardization of data entry and further development of automated algorithmic aids, including adaptive UIs, have great promise for improving DQ. Further research is essential to ensure data captured in our electronic systems are high quality and valid for use in clinical decision-making and other secondary analyses.

Representation of Environmental Concepts Associated with Health Impacts in Computer Standardized Clinical Terminologies.

OBJECTIVE: To evaluate the representation of environmental concepts associated with health impacts in standardized clinical terminologies. METHODS: This study used a descriptive approach with methods informed by a procedural framework for standardized clinical terminology mapping. The United Nations Global Indicator Framework for the Sustainable Development Goals and Targets was used as the source document for concept extraction. The target terminologies were the Systematized Nomenclature of Medicine Clinical Terms (SNOMED CT) and the International Classification for Nursing Practice (ICNP). Manual and automated mapping methods were utilized. The lists of candidate matches were reviewed and iterated until a final mapping match list was achieved. RESULTS: A total of 119 concepts with 133 mapping matches were added to the final SNOMED CT list. Fifty-three (39.8%) were direct matches, 37 (27.8%) were narrower than matches, 35 (26.3%) were broader than matches, and 8 (6%) had no matches. A total of 26 concepts with 27 matches were added to the final ICNP list. Eight (29.6%) were direct matches, 4 (14.8%) were narrower than, 7 (25.9%) were broader than, and 8 (29.6%) were no matches. CONCLUSION: Following this evaluation, both strengths and gaps were identified. Gaps in terminology representation included concepts related to cost expenditures, affordability, community engagement, water, air and sanitation. The inclusion of these concepts is necessary to advance the clinical reporting of these environmental and sustainability indicators. As environmental concepts encoded in standardized terminologies expand, additional insights into data and health conditions, research, education, and policy-level decision-making will be identified.

Application of Natural Language Processing to Learn Insights on the Clinician's Lived Experience of Electronic Health Records.

We interviewed six clinicians to learn about their lived experience using electronic health records (EHR, Allscripts users) using a semi-structured interview guide in an academic medical center in New York City from October to November 2016. Each participant interview lasted approximately one to two hours. We applied a clustering algorithm to the interview transcript to detect topics, applying natural language processing (NLP). We visualized eight themes using network diagrams (Louvain modularity 0.70). Novel findings include the need for a concise and organized display and data entry page, the user controlling functions for orders, medications, radiology reports, and missing signals of indentation or filtering functions in the order page and lab results. Application of topic modeling to qualitative interview data provides far-reaching research insights into the clinicians' lived experience of EHR and future optimal EHR design to address human-computer interaction issues in an acute care setting.