Travel Distance Between Participants in US Telemedicine Sessions With Estimates of Emissions Savings: Observational Study.

BACKGROUND: Digital health and telemedicine are potentially important strategies to decrease health care's environmental impact and contribution to climate change by reducing transportation-related air pollution and greenhouse gas emissions. However, we currently lack robust national estimates of emissions savings attributable to telemedicine. OBJECTIVE: This study aimed to (1) determine the travel distance between participants in US telemedicine sessions and (2) estimate the net reduction in carbon dioxide (CO2) emissions attributable to telemedicine in the United States, based on national observational data describing the geographical characteristics of telemedicine session participants. METHODS: We conducted a retrospective observational study of telemedicine sessions in the United States between January 1, 2022, and February 21, 2023, on the doxy.me platform. Using Google Distance Matrix, we determined the median travel distance between participating providers and patients for a proportional sample of sessions. Further, based on the best available public data, we estimated the total annual emissions costs and savings attributable to telemedicine in the United States. RESULTS: The median round trip travel distance between patients and providers was 49 (IQR 21-145) miles. The median CO2 emissions savings per telemedicine session was 20 (IQR 8-59) kg CO2). Accounting for the energy costs of telemedicine and US transportation patterns, among other factors, we estimate that the use of telemedicine in the United States during the years 2021-2022 resulted in approximate annual CO2 emissions savings of 1,443,800 metric tons. CONCLUSIONS: These estimates of travel distance and telemedicine-associated CO2 emissions costs and savings, based on national data, indicate that telemedicine may be an important strategy in reducing the health care sector's carbon footprint.

Telemedicine from Home or the Office: Perceptions of Mental Health Providers.

Introduction: The COVID-19 pandemic led to a rapid transition to telemedicine for mental health care and redefined many providers' work environments and practices. The purpose of the study was to investigate the impact of work location on telemental health (TMH) benefits, disruptions, and concerns to further understand the rapid implementation of telemedicine for mental health treatment. Methods: A sample of 175 practicing TMH providers completed an online survey between July and August 2020. Providers answered questions about personal demographics and practice characteristics. Next, they answered questions about benefits, disruptions, and concerns regarding the use of telemedicine in their practice. Chi-square and independent samples t-test were conducted to identify work location differences for personal demographics and clinical practice characteristics. Three multivariate analyses of covariance were conducted to examine overall differences in perceptions of telemedicine benefits, concerns, and disruptions based on work location while covarying for provider race, ethnicity, percentage of caseload seen through telemedicine, practice type, specialty, and primary method of reimbursement. Results: TMH providers who primarily work from an office reported more benefit of reduced costs/overhead (ηp2 = 0.039), less benefit of limiting the spread of the virus (ηp2 = 0.028), and more concern about reimbursement (ηp2 = 0.046) than those who primarily work from home. We observed no difference in disruptions, patient access to care, quality of care, and work-life balance. Discussion: Exploration into work location of TMH providers aids in understanding of clinical workflows and provider wellbeing. Our findings suggest that telemedicine may be easily integrated into different types of clinical workflows and work locations.

An overview and policy implications of national nurse identifier systems: A call for unity and integration.

There is a clear and growing need to be able record and track the contributions of individual registered nurses (RNs) to patient care and patient care outcomes in the US and also understand the state of the nursing workforce. The National Academies of Sciences, Engineering, and Medicine report, The Future of Nursing 2020-2030: Charting a Path to Achieve Health Equity (2021), identified the need to track nurses' collective and individual contributions to patient care outcomes. This capability depends upon the adoption of a unique nurse identifier and its implementation within electronic health records. Additionally, there is a need to understand the nature and characteristics of the overall nursing workforce including supply and demand, turnover, attrition, credentialing, and geographic areas of practice. This need for data to support workforce studies and planning is dependent upon comprehensive databases describing the nursing workforce, with unique nurse identification to support linkage across data sources. There are two existing national nurse identifiers- the National Provider Identifier and the National Council of State Boards of Nursing Identifier. This article provides an overview of these two national nurse identifiers; reviews three databases that are not nurse specific to understand lessons learned in the development of those databases; and discusses the ethical, legal, social, diversity, equity, and inclusion implications of a unique nurse identifier.

Hospital acquired pressure injury prediction in surgical critical care patients.

BACKGROUND: Hospital-acquired pressure injuries (HAPrIs) are areas of damage to the skin occurring among 5-10% of surgical intensive care unit (ICU) patients. HAPrIs are mostly preventable; however, prevention may require measures not feasible for every patient because of the cost or intensity of nursing care. Therefore, recommended standards of practice include HAPrI risk assessment at routine intervals. However, no HAPrI risk-prediction tools demonstrate adequate predictive validity in the ICU population. The purpose of the current study was to develop and compare models predicting HAPrIs among surgical ICU patients using electronic health record (EHR) data. METHODS: In this retrospective cohort study, we obtained data for patients admitted to the surgical ICU or cardiovascular surgical ICU between 2014 and 2018 via query of our institution's EHR. We developed predictive models utilizing three sets of variables: (1) variables obtained during routine care + the Braden Scale (a pressure-injury risk-assessment scale); (2) routine care only; and (3) a parsimonious set of five routine-care variables chosen based on availability from an EHR and data warehouse perspective. Aiming to select the best model for predicting HAPrIs, we split each data set into standard 80:20 train:test sets and applied five classification algorithms. We performed this process on each of the three data sets, evaluating model performance based on continuous performance on the receiver operating characteristic curve and the F1 score. RESULTS: Among 5,101 patients included in analysis, 333 (6.5%) developed a HAPrI. F1 scores of the five classification algorithms proved to be a valuable evaluation metric for model performance considering the class imbalance. Models developed with the parsimonious data set had comparable F1 scores to those developed with the larger set of predictor variables. CONCLUSIONS: Results from this study show the feasibility of using EHR data for accurately predicting HAPrIs and that good performance can be found with a small group of easily accessible predictor variables. Future study is needed to test the models in an external sample.

Predicting Falls Among Community-Dwelling Older Adults: A Demonstration of Applied Machine Learning.

Data science skills are increasingly needed by informatics nurses and nurse scientists, but techniques such as machine learning can be daunting for those with clinical, rather than computer science or technical, backgrounds. With the increasing quantity of publicly available population-level datasets, identification of factors that predict clinical outcomes is possible using machine learning algorithms. This study demonstrates how to apply a machine learning approach to nursing-relevant questions, specifically an approach to predict falls among community-dwelling older adults, based on data from the 2014 Behavioral Risk Factor Surveillance System. A random forest algorithm, a common approach to machine learning, was compared to a logistic regression model. Explanations of how to interpret the models and their associated performance characteristics are included to serve as a tutorial to readers. Machine learning methods constitute an increasingly important approach for nursing as population-level data are increasingly being made available to the public.

Value-Based Payment: What Does It Mean for Nurses?

Among the many lessons that have been reinforced by the SARS-COVID-19 pandemic is the failure of our current fee-for-service health care system to either adequately respond to patient needs or offer financial sustainability. This has enhanced bipartisan interest in moving forward with value-based payment reforms. Nurses have a rich history of innovative care models that speak to their potential centrality in delivery system reforms. However, deficits in terms of educational preparation, and in some cases resistance, to considering cost alongside quality, has hindered the profession's contribution to the conversation about value-based payments and their implications for system change. Addressing this deficit will allow nurses to more fully engage in redesigning health care to better serve the physical, emotional, and economic well-being of this nation. It also has the potential to unleash nurses from the tethers of a fee-for-service system where they have been relegated to a labor cost and firmly locate nurses in a value-generating role. Nurse administrators and educators bear the responsibility for preparing nurses for this next chapter of nursing.

Hospital-Acquired Pressure Injury Development Among Surgical Critical Care Patients Admitted With Community-Acquired Pressure Injury: A Retrospective Cohort Study.

PURPOSE: Community-acquired pressure injuries (CAPIs) are present among approximately 3% to 8% of patients admitted to acute care hospitals. In the critical care population, little is known about hospital-acquired pressure injury (HAPI) development among patients with CAPIs because most studies exclude patients with CAPIs. The purpose of our study was to determine the incidence of HAPI development and the associated risk factors among surgical critical care patients with CAPIs. DESIGN: Retrospective cohort study. SUBJECTS AND SETTING: We used electronic health record data from adult critical care patients admitted to the surgical and cardiovascular surgical intensive care units (ICUs) at a level 1 trauma center and academic medical center between 2014 and 2018. METHODS: Univariate analysis was used to compare patients with CAPIs who developed a HAPI and those who did not, as well as logistic regression analysis to identify independent risk factors for HAPIs among patients with CAPIs. RESULTS: Among 5101 patients admitted to 2 surgical critical care units, 167 (3%) patients were admitted with CAPIs. Hospital-acquired pressure injuries were 4 times more common among patients with CAPIs compared to patients without CAPIs. Among the 167 patients with CAPIs, 47 patients (28%) went on to also develop a HAPI, whereas in the 4934 patients without CAPIs, 352 patients (7%) went on to develop a HAPI. Findings from the multivariate logistic regression analysis (n = 151) showed that decreased serum albumin (odds ratio [OR] = 0.47; 95% confidence interval [CI], 0.25-0.85; P = .02) and excessively dry skin (OR = 2.6; 95% CI, 1.1-6.22; P = .03) were independent predictors of HAPI development among patients admitted with CAPIs. CONCLUSIONS: Results from our study show that patients with CAPIs are at high risk for developing a HAPI, particularly among patients with decreased serum albumin or excessively dry skin. Patients with excessively dry skin may benefit from the application of skin moisturizers.

Midrange Braden Subscale Scores Are Associated With Increased Risk for Pressure Injury Development Among Critical Care Patients.

PURPOSE: The purpose of the current study was to examine the relationship between pressure injury development and the Braden Scale for Pressure Sore Risk subscale scores in a surgical intensive care unit (ICU) population and to ascertain whether the risk represented by the subscale scores is different between older and younger patients. DESIGN: Retrospective review of electronic medical records. SUBJECTS AND SETTING: The sample comprised patients admitted to the ICU at an academic medical center in the Western United States (Utah) and Level 1 trauma center between January 1, 2008 and May 1, 2013. Analysis is based on data from 6377 patients. METHODS: Retrospective chart review was used to determine Braden Scale total and subscale scores, age, and incidence of pressure injury development. We used survival analysis to determine the hazards of developing a pressure injury associated with each subscale of the Braden Scale, with the lowest-risk category as a reference. In addition, we used time-dependent Cox regression with natural cubic splines to model the interaction between age and Braden Scale scores and subscale scores in pressure injury risk. RESULTS: Of the 6377 ICU patients, 214 (4%) developed a pressure injury (stages 2-4, deep tissue injury, or unstageable) and 516 (8%) developed a hospital-acquired pressure injury of any stage. With the exception of the friction and shear subscales, regardless of age, individuals with scores in the intermediate-risk levels had the highest likelihood of developing pressure injury. CONCLUSION: The relationship between age, Braden Scale subscale scores, and pressure injury development varied among subscales. Maximal preventive efforts should be extended to include individuals with intermediate Braden Scale subscale scores, and age should be considered along with the subscale scores as a factor in care planning.

Exploring nurses' emotional reactions to and reporting of patient-on-nurse workplace violence: A mixed-methods study.

BACKGROUND: Workplace violence, including violent, intimidating, and disruptive acts, commonly occurs in healthcare settings. Type 2 workplace violence in nursing refers to patient/visitor behaviors directed toward clinicians, contributing to physical and psychological harm. Nurse victims often do not report these events to employers or law enforcement, making it challenging to address workplace violence. OBJECTIVES: Our research examined nurse reactions to Type 2 workplace violence by identifying what behaviors they perceived as aggressive and reportable. Specific aims included: 1) developing and testing video vignettes to portray realistic patient aggression scenarios; 2) identifying nurse understandings of aggressive events that prompt affective reactions, and; 3) examining clinical characteristics related to the nurse victim's likelihood to report. DESIGN: Through a sequential mixed-methods design, we qualitatively developed novel video vignettes portraying Type 2 workplace violence to experimentally examine how nurses interpreted them within a quantitative repeated measures survey. METHODS: Two expert nurse research panels (n = 10) created five vignettes, from which nurses (n = 282) completed a survey with 1382 unique responses. Analyses included descriptive statistics and repeated measures ANOVA/regression models. RESULTS: Video vignettes realistically portrayed workplace violence events, eliciting negative emotional responses among nurses that increased in magnitude with statistical significance as the level of displayed aggression escalated. Statistically significant factors influencing nurse reporting of workplace violence included; 1) the level of aggression displayed by the patient; 2) the level of harm received by the nurse; 3) whether the nurse felt the patient's actions were intentional, and; 4) the nurse's perceived frequency of exposure to workplace violence. CONCLUSIONS: Results suggested that nurse victims of Type 2 workplace violence experience depression, anger, fear, and anxiety, which may contribute to long-term mental health consequences. Findings also identified factors related to nurse reporting behaviors, which may help mitigate workplace violence in healthcare settings by informing research and promoting workplace practices that encourage reporting and safety. REGISTRATION: Not registered. TWEETABLE ABSTRACT: Nurse reactions to workplace violence: Video vignettes reveal escalating aggression's impact on reporting. #EndNurseAbuse #WorkplaceViolence.

Will the United States pass on telemedicine progress?

Background: During the COVID-19 pandemic, federal and state health policies allowed temporary flexibilities for Medicare and Medicaid beneficiaries, leading to a sharp increase in telemedicine use. However, many of the flexibilities that enabled innovation and growth in telemedicine continue temporarily since the federal emergency declaration ended in May 2023, and the United States has not made permanent decisions about telemedicine policy. Analysts have raised concerns about increased spending, program integrity, safety, and equity, and recommend strengthening oversight. Methods: Here, we argue that we must continue the flexibilities to better understand telemedicine's quality, safety, and outcomes, and until the United States can develop an evidence-based digital health strategy. A premature regression to pre-pandemic telemedicine policies risks unintended consequences. Conclusion: We must continue the current policy flexibilities, safeguard against fraud and abuse, and immediately prioritize research and evaluation of telemedicine's quality, safety, and outcomes, to avoid unintended consequences and support more permanent policy decision-making.

User Preferences and Needs for Health Data Collection Using Research Electronic Data Capture: Survey Study.

BACKGROUND: Self-administered web-based questionnaires are widely used to collect health data from patients and clinical research participants. REDCap (Research Electronic Data Capture; Vanderbilt University) is a global, secure web application for building and managing electronic data capture. Unfortunately, stakeholder needs and preferences of electronic data collection via REDCap have rarely been studied. OBJECTIVE: This study aims to survey REDCap researchers and administrators to assess their experience with REDCap, especially their perspectives on the advantages, challenges, and suggestions for the enhancement of REDCap as a data collection tool. METHODS: We conducted a web-based survey with representatives of REDCap member organizations in the United States. The survey captured information on respondent demographics, quality of patient-reported data collected via REDCap, patient experience of data collection with REDCap, and open-ended questions focusing on the advantages, challenges, and suggestions to enhance REDCap's data collection experience. Descriptive and inferential analysis measures were used to analyze quantitative data. Thematic analysis was used to analyze open-ended responses focusing on the advantages, disadvantages, and enhancements in data collection experience. RESULTS: A total of 207 respondents completed the survey. Respondents strongly agreed or agreed that the data collected via REDCap are accurate (188/207, 90.8%), reliable (182/207, 87.9%), and complete (166/207, 80.2%). More than half of respondents strongly agreed or agreed that patients find REDCap easy to use (165/207, 79.7%), could successfully complete tasks without help (151/207, 72.9%), and could do so in a timely manner (163/207, 78.7%). Thematic analysis of open-ended responses yielded 8 major themes: survey development, user experience, survey distribution, survey results, training and support, technology, security, and platform features. The user experience category included more than half of the advantage codes (307/594, 51.7% of codes); meanwhile, respondents reported higher challenges in survey development (169/516, 32.8% of codes), also suggesting the highest enhancement suggestions for the category (162/439, 36.9% of codes). CONCLUSIONS: Respondents indicated that REDCap is a valued, low-cost, secure resource for clinical research data collection. REDCap's data collection experience was generally positive among clinical research and care staff members and patients. However, with the advancements in data collection technologies and the availability of modern, intuitive, and mobile-friendly data collection interfaces, there is a critical opportunity to enhance the REDCap experience to meet the needs of researchers and patients.

Narrative review of telemedicine applications in decentralized research.

Telemedicine enables critical human communication and interaction between researchers and participants in decentralized research studies. There is a need to better understand the overall scope of telemedicine applications in clinical research as the basis for further research. This narrative, nonsystematic review of the literature sought to review and discuss applications of telemedicine, in the form of synchronous videoconferencing, in clinical research. We searched PubMed to identify relevant literature published between January 1, 2013, and June 30, 2023. Two independent screeners assessed titles and abstracts for inclusion, followed by single-reviewer full-text screening, and we organized the literature into core themes through consensus discussion. We screened 1044 publications for inclusion. Forty-eight publications met our inclusion and exclusion criteria. We identified six core themes to serve as the structure for the narrative review: infrastructure and training, recruitment, informed consent, assessment, monitoring, and engagement. Telemedicine applications span all stages of clinical research from initial planning and recruitment to informed consent and data collection. While the evidence base for using telemedicine in clinical research is not well-developed, existing evidence suggests that telemedicine is a potentially powerful tool in clinical research.

Vaccine Effectiveness Against Long COVID in Children.

OBJECTIVES: Vaccination reduces the risk of acute coronavirus disease 2019 (COVID-19) in children, but it is less clear whether it protects against long COVID. We estimated vaccine effectiveness (VE) against long COVID in children aged 5 to 17 years. METHODS: This retrospective cohort study used data from 17 health systems in the RECOVER PCORnet electronic health record program for visits after vaccine availability. We examined both probable (symptom-based) and diagnosed long COVID after vaccination. RESULTS: The vaccination rate was 67% in the cohort of 1 037 936 children. The incidence of probable long COVID was 4.5% among patients with COVID-19, whereas diagnosed long COVID was 0.8%. Adjusted vaccine effectiveness within 12 months was 35.4% (95 CI 24.5-44.7) against probable long COVID and 41.7% (15.0-60.0) against diagnosed long COVID. VE was higher for adolescents (50.3% [36.6-61.0]) than children aged 5 to 11 (23.8% [4.9-39.0]). VE was higher at 6 months (61.4% [51.0-69.6]) but decreased to 10.6% (-26.8% to 37.0%) at 18-months. CONCLUSIONS: This large retrospective study shows moderate protective effect of severe acute respiratory coronavirus 2 vaccination against long COVID. The effect is stronger in adolescents, who have higher risk of long COVID, and wanes over time. Understanding VE mechanism against long COVID requires more study, including electronic health record sources and prospective data.

Therapist perspectives on telehealth-based virtual reality exposure therapy.

Virtual reality (VR) can enhance mental health care. In particular, the effectiveness of VR-based exposure therapy (VRET) has been well-demonstrated for treatment of anxiety disorders. However, most applications of VRET remain localized to clinic spaces. We aimed to explore mental health therapists' perceptions of telehealth-based VRET (tele-VRET) by conducting semi-structured, qualitative interviews with 18 telemental health therapists between October and December 2022. Interview topics included telehealth experiences, exposure therapy over telehealth, perceptions of VR in therapy, and perspectives on tele-VRET. Therapists described how telehealth reduced barriers (88.9%, 16/18), enhanced therapy (61.1%, 11/18), and improved access to clients (38.9%, 7/18), but entailed problems with technology (61.1%, 11/18), uncontrolled settings (55.6%, 10/18), and communication di culties (50%, 9/18). Therapists adapted exposure therapy to telehealth by using online resources (66.7%, 12/18), preparing client expectations (55.6%, 10/18), and adjusting workflows (27.8%, 5/18). Most therapists had used VR before (72.2%, 13/18) and had positive impressions (55.6%, 10/18), but none had used VR clinically. In response to tele-VRET, therapists requested interactive session activities (77.8%, 14/18) and customizable interventions components (55.6%, 10/18). Concerns about tele-VRET included risks with certain clients (77.8%, 14/18), costs (50%, 9/18), side effects and privacy (22.2%, 4/18), and inappropriateness for specific forms of exposure therapy (16.7%, 3/18). These results show how designing for telehealth may extend VRET and can help inform collaborative development of health technologies.

Consensus Guidelines for Teledermatology: Scoping Review.

BACKGROUND: Consensus guidelines and recommendations play an important role in fostering quality, safety, and best practices, as they represent an expert interpretation of the biomedical literature and its application to practice. However, it is unclear whether the recent collective experience of implementing telemedicine and the concurrent growth in the evidence base for teledermatology have resulted in more robust guidance. OBJECTIVE: The objective of this review was to describe the extent and nature of currently available guidance, defined as consensus guidelines and recommendations available for telemedicine in dermatology, with guidance defined as consensus or evidence-based guidelines, protocols, or recommendations. METHODS: We conducted a single-reviewer scoping review of the literature to assess the extent and nature of available guidance, consensus guidelines, or recommendations related to teledermatology. We limited the review to published material in English since 2013, reflecting approximately the past 10 years. We conducted the review in November and December of the year 2022. RESULTS: We identified 839 potentially eligible publications, with 9 additional records identified through organizational websites. A total of 15 publications met the inclusion and exclusion criteria. The guidelines focused on varied topics and populations about dermatology and skin diseases. However, the most frequent focus was general dermatology (8/15, 53%). Approximately half of the telemedicine guidance described in the publications was specific to dermatology practice in the context of the COVID-19 pandemic. The publications were largely published in or after the year 2020 (13/15, 87%). Geographical origin spanned several different nations, including Australia, the United States, European countries, and India. CONCLUSIONS: We found an increase in COVID-19-specific teledermatology guidance during 2020, in addition to general teledermatology guidance during the period of the study. Primary sources of general teledermatology guidance reported in the biomedical literature are the University of Queensland's Centre for Online Health and Australasian College of Dermatologists E-Health Committee, and the American Telemedicine Association. There is strong evidence of international engagement and interest. Despite the recent increase in research reports related to telemedicine, there is a relative lack of new guidance based on COVID-19 lessons and innovations. There is a need to review recent evidence and update existing recommendations. Additionally, there is a need for guidance that addresses emerging technologies.

Decentralized research technology use in multicenter clinical research studies based at U.S. academic research centers.

Introduction: During the COVID-19 pandemic, research organizations accelerated adoption of technologies that enable remote participation. Now, there's a pressing need to evaluate current decentralization practices and develop appropriate research, education, and operations infrastructure. The purpose of this study was to examine current adoption of decentralization technologies in a sample of clinical research studies conducted by academic research organizations (AROs). Methods: The setting was three data coordinating centers in the U.S. These centers initiated coordination of 44 clinical research studies during or after 2020, with national recruitment and enrollment, and entailing coordination between one and one hundred sites. We determined the decentralization technologies used in these studies. Results: We obtained data for 44/44 (100%) trials coordinated by the three centers. Three technologies have been adopted across nearly all studies (98-100%): eIRB, eSource, and Clinical Trial Management Systems. Commonly used technologies included e-Signature (32/44, 73%), Online Payments Portals (26/44, 59%), ePROs (23/44, 53%), Interactive Response Technology (22/44, 50%), Telemedicine (19/44, 43%), and eConsent (18/44, 41%). Wearables (7/44,16%) and Online Recruitment Portals (5/44,11%) were less common. Rarely utilized technologies included Direct-to-Patient Portals (1/44, 2%) and Home Health Nurse Portals (1/44, 2%). Conclusions: All studies incorporated some type of decentralization technology, with more extensive adoption than found in previous research. However, adoption may be strongly influenced by institution-specific IT and informatics infrastructure and support. There are inherent needs, responsibilities, and challenges when incorporating decentralization technology into a research study, and AROs must ensure that infrastructure and informatics staff are adequate.

Vaccine Effectiveness Against Long COVID in Children: A Report from the RECOVER EHR Cohort.

Objective: Vaccination reduces the risk of acute COVID-19 in children, but it is less clear whether it protects against long COVID. We estimated vaccine effectiveness (VE) against long COVID in children aged 5-17 years. Methods: This retrospective cohort study used data from 17 health systems in the RECOVER PCORnet electronic health record (EHR) Program for visits between vaccine availability, and October 29, 2022. Conditional logistic regression was used to estimate VE against long COVID with matching on age group (5-11, 12-17) and time period and adjustment for sex, ethnicity, health system, comorbidity burden, and pre-exposure health care utilization. We examined both probable (symptom-based) and diagnosed long COVID in the year following vaccination. Results: The vaccination rate was 56% in the cohort of 1,037,936 children. The incidence of probable long COVID was 4.5% among patients with COVID-19, while diagnosed long COVID was 0.7%. Adjusted vaccine effectiveness within 12 months was 35.4% (95 CI 24.5 - 44.5) against probable long COVID and 41.7% (15.0 - 60.0) against diagnosed long COVID. VE was higher for adolescents 50.3% [36.3 - 61.0]) than children aged 5-11 (23.8% [4.9 - 39.0]). VE was higher at 6 months (61.4% [51.0 - 69.6]) but decreased to 10.6% (-26.8 - 37.0%) at 18-months. Discussion: This large retrospective study shows a moderate protective effect of SARS-CoV-2 vaccination against long COVID. The effect is stronger in adolescents, who have higher risk of long COVID, and wanes over time. Understanding VE mechanism against long COVID requires more study, including EHR sources and prospective data. Article Summary: Vaccination against COVID-19 has a protective effect against long COVID in children and adolescents. The effect wanes over time but remains significant at 12 months. What's Known on This Subject: Vaccines reduce the risk and severity of COVID-19 in children. There is evidence for reduced long COVID risk in adults who are vaccinated, but little information about similar effects for children and adolescents, who have distinct forms of long COVID. What This Study Adds: Using electronic health records from US health systems, we examined large cohorts of vaccinated and unvaccinated patients <18 years old and show that vaccination against COVID-19 is associated with reduced risk of long COVID for at least 12 months. Contributors' Statement: Drs. Hanieh Razzaghi and Charles Bailey conceptualized and designed the study, supervised analyses, drafted the initial manuscript, and critically reviewed and revised the manuscript.Drs. Christopher Forrest and Yong Chen designed the study and critically reviewed and revised the manuscript.Ms. Kathryn Hirabayashi, Ms. Andrea Allen, and Dr. Qiong Wu conducted analyses, and critically reviewed and revised the manuscript.Drs. Suchitra Rao, H Timothy Bunnell, Elizabeth A. Chrischilles, Lindsay G. Cowell, Mollie R. Cummins, David A. Hanauer, Benjamin D. Horne, Carol R. Horowitz, Ravi Jhaveri, Susan Kim, Aaron Mishkin, Jennifer A. Muszynski, Susanna Nagie, Nathan M. Pajor, Anuradha Paranjape, Hayden T. Schwenk, Marion R. Sills, Yacob G. Tedla, David A. Williams, and Ms. Miranda Higginbotham critically reviewed and revised the manuscript.All authors approved the final manuscript as submitted and agree to be accountable for all aspects of the work. Authorship statement: Authorship has been determined according to ICMJE recommendations.

Research outcomes of linked prescription drug monitoring program data: a scoping review protocol.

INTRODUCTION: The objective of this scoping review is to describe the extent and nature of research studies based on linked prescription drug monitoring program (PDMP) data; defined as PDMP data linked to other clinical, administrative or public health data sets. The population is prescribed and dispensed controlled substances. The concept is analysis of linked PDMP data to other clinical, administrative or public health data sets. The context is the USA. METHODS AND ANALYSIS: The scoping review will be conducted with guidance from the latest version of the JBI Manual for Evidence Synthesis, using the framework as outlined by Arksey and O'Malley. Search strategies will be peer-reviewed according to the Peer Review of Electronic Search Strategies (PRESS) guidelines. For transparency and reproducibility, we will adhere to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews reporting guidelines in reporting results. Two reviewers will independently screen titles and abstracts, then independently review full text to select papers or studies for inclusion. When consensus cannot be reached with discussion, a third reviewer will resolve the conflicts. From our included studies, we will extract variables describing aspects of population, concept and context (USA). ETHICS AND DISSEMINATION: Ethical approval was not required for this review. This scoping review entails analysis of previously published, peer-reviewed research. We intend to publish findings in a peer-reviewed journal.

Interests and needs of eye care providers in clinical decision support for glaucoma.

OBJECTIVE: To study whether clinicians who treat glaucoma are interested in using clinical decision support (CDS) tools for glaucoma, what glaucoma clinical decisions they feel would benefit from CDS, and what characteristics of CDS design they feel would be important in glaucoma clinical practice. METHODS AND ANALYSIS: Working with the American Glaucoma Society, the Utah Ophthalmology Society and the Utah Optometric Association, we identified a group of clinicians who care for patients with glaucoma. We asked these clinicians about interest in CDS, what glaucoma clinical decisions would benefit from CDS, and what characteristics of CDS tool design would be important in glaucoma clinical practice. RESULTS: Of the 105 clinicians (31 optometrists, 10 general ophthalmologists and 64 glaucoma specialists), 93 (88.6%) were either 'definitely' or 'probably' interested in using CDS for glaucoma. There were no statistically significant differences in interest between clinical specialties (p=0.12), years in practice (p=0.85) or numbers of patients seen daily (p=0.99). Identifying progression of glaucoma was the clinical decision the largest number of clinicians felt would benefit from CDS (104/105, 99.1%). An easy to use interface was the CDS characteristic the largest number of clinicians felt would be 'very important' (93/105, 88.6%). CONCLUSION: Of this group of clinicians who treat glaucoma, 88.6% were interested in using CDS for glaucoma and 99.1% felt that identification of glaucomatous progression could benefit from CDS. This level of interest supports future work to develop CDS for glaucoma.