Self-Rated Health in Middle Age and Risk of Hospitalizations and Death: Recurrent Event Analysis of the ARIC Study.

BACKGROUND: Self-rated health is a simple measure that may identify individuals who are at a higher risk for hospitalization or death. OBJECTIVE: To quantify the association between a single measure of self-rated health and future risk of recurrent hospitalizations or death. PARTICIPANTS: Atherosclerosis Risk in Communities (ARIC) study, a community-based prospective cohort study of middle-aged men and women with follow-up beginning from 1987 to 1989. MAIN MEASURES: We quantified the associations between initial self-rated health with risk of recurrent hospitalizations and of death using a recurrent events survival model that allowed for dependency between the rates of hospitalization and hazards of death, adjusted for demographic and clinical factors. KEY RESULTS: Of the 14,937 ARIC cohort individuals with available self-rated health and covariate information, 34% of individuals reported "excellent" health, 47% "good," 16% "fair," and 3% "poor" at study baseline. After a median follow-up of 27.7 years, 1955 (39%), 3569 (51%), 1626 (67%), and 402 (83%) individuals with "excellent," "good," "fair," and "poor" health, respectively, had died. After adjusting for demographic factors and medical history, a less favorable self-rated health status was associated with increased rates of hospitalization and death. As compared to those reporting "excellent" health, adults with "good," "fair," and "poor" health had 1.22 (1.07 to 1.40), 2.01 (1.63 to 2.47), and 3.13 (2.39 to 4.09) times the rate of hospitalizations, respectively. The hazards of death also increased with worsening categories of self-rated health, with "good," "fair," and "poor" health individuals experiencing 1.30 (1.12 to 1.51), 2.15 (1.71 to 2.69), and 3.40 (2.54 to 4.56) times the hazard of death compared to "excellent," respectively. CONCLUSIONS: Even after adjusting for demographic and clinical factors, having a less favorable response on a single measure of self-rated health taken in middle age is a potent marker of future hospitalizations and death.

Cardiovascular health assessment in routine cancer follow-up in community settings: survivor risk awareness and perspectives.

BACKGROUND: Guidelines recommend cardiovascular risk assessment and counseling for cancer survivors. For effective implementation, it is critical to understand survivor cardiovascular health (CVH) profiles and perspectives in community settings. We aimed to (1) Assess survivor CVH profiles, (2) compare self-reported and EHR-based categorization of CVH factors, and (3) describe perceptions regarding addressing CVH during oncology encounters. METHODS: This cross-sectional analysis utilized data from an ongoing NCI Community Oncology Research Program trial of an EHR heart health tool for cancer survivors (WF-1804CD). Survivors presenting for routine care after potentially curative treatment recruited from 8 oncology practices completed a pre-visit survey, including American Heart Association Simple 7 CVH factors (classified as ideal, intermediate, or poor). Medical record abstraction ascertained CVD risk factors and cancer characteristics. Likert-type questions assessed desired discussion during oncology care. RESULTS: Of 502 enrolled survivors (95.6% female; mean time since diagnosis = 4.2 years), most had breast cancer (79.7%). Many survivors had common cardiovascular comorbidities, including high cholesterol (48.3%), hypertension or high BP (47.8%) obesity (33.1%), and diabetes (20.5%); 30.5% of survivors received high cardiotoxicity potential cancer treatment. Less than half had ideal/non-missing levels for physical activity (48.0%), BMI (18.9%), cholesterol (17.9%), blood pressure (14.1%), healthy diet (11.0%), and glucose/ HbA1c (6.0%). While > 50% of survivors had concordant EHR-self-report categorization for smoking, BMI, and blood pressure; cholesterol, glucose, and A1C were unknown by survivors and/or missing in the EHR for most. Most survivors agreed oncology providers should talk about heart health (78.9%). CONCLUSIONS: Tools to promote CVH discussion can fill gaps in CVH knowledge and are likely to be well-received by survivors in community settings. TRIAL REGISTRATION: NCT03935282, Registered 10/01/2020.

Segregated Patterns of Hospital Care Delivery and Health Outcomes.

Importance: Residential segregation has been shown to be a root cause of racial inequities in health outcomes, yet little is known about current patterns of racial segregation in where patients receive hospital care or whether hospital segregation is associated with health outcomes. Filling this knowledge gap is critical to implementing policies that improve racial equity in health care. Objective: To characterize contemporary patterns of racial segregation in hospital care delivery, identify market-level correlates, and determine the association between hospital segregation and health outcomes. Design, Setting, and Participants: This cross-sectional study of US hospital referral regions (HRRs) used 2018 Medicare claims, American Community Survey, and Agency for Healthcare Research and Quality Social Determinants of Health data. Hospitalization patterns for all non-Hispanic Black or non-Hispanic White Medicare fee-for-service beneficiaries with at least 1 inpatient hospitalization in an eligible hospital were evaluated for hospital segregation and associated health outcomes at the HRR level. The data analysis was performed between August 10, 2022, and September 6, 2023. Exposures: Dissimilarity index and isolation index for HRRs. Main Outcomes and Measures: Health outcomes were measured using Prevention Quality Indicator (PQI) acute and chronic composites per 100 000 Medicare beneficiaries, and total deaths related to heart disease and stroke per 100 000 residents were calculated for individuals aged 74 years or younger. Correlation coefficients were used to compare residential and hospital dissimilarity and residential and hospital isolation. Linear regression was used to examine the association between hospital segregation and health outcomes. Results: This study included 280 HRRs containing data for 4386 short-term acute care and critical access hospitals. Black and White patients tended to receive care at different hospitals, with a mean (SD) dissimilarity index of 23 (11) and mean (SD) isolation index of 13 (13), indicating substantial variation in segregation across HRRs. Hospital segregation was correlated with residential segregation (correlation coefficients, 0.58 and 0.90 for dissimilarity and isolation, respectively). For Black patients, a 1-SD increase in the hospital isolation index was associated with 204 (95% CI, 154-254) more acute PQI hospitalizations per 100 000 Medicare beneficiaries (28% increase from the median), 684 (95% CI, 488-880) more chronic PQI hospitalizations per 100 000 Medicare beneficiaries (15% increase), and 6 (95% CI, 2-9) additional deaths per 100 000 residents (6% increase) compared with 68 (95% CI, 24-113; 6% increase), 202 (95% CI, 131-274; 8% increase), and 2 (95% CI, 0 to 4; 3% increase), respectively, for White patients. Conclusions and Relevance: This cross-sectional study found that higher segregation of hospital care was associated with poorer health outcomes for both Black and White Medicare beneficiaries, with significantly greater negative health outcomes for Black populations, supporting racial segregation as a root cause of health disparities. Policymakers and clinical leaders could address this important public health issue through payment reform efforts and expansion of health insurance coverage, in addition to supporting upstream efforts to reduce racial segregation in hospital care and residential settings.

Incidence of and Factors Associated With Recurrent Firearm Injury Among Patients Presenting to St. Louis Trauma Centers, 2010 to 2019 : A Cohort Study.

BACKGROUND: Firearm injuries are a public health crisis in the United States. OBJECTIVE: To examine the incidence and factors associated with recurrent firearm injuries and death among patients presenting with an acute (index), nonfatal firearm injury. DESIGN: Multicenter, observational, cohort study. SETTING: Four adult and pediatric level I trauma hospitals in St. Louis, Missouri, 2010 to 2019. PARTICIPANTS: Consecutive adult and pediatric patients (n = 9553) presenting to a participating hospital with a nonfatal acute firearm injury. MEASUREMENTS: Data on firearm-injured patient demographics, hospital and diagnostic information, health insurance status, and death were collected from the St. Louis Region-Wide Hospital-Based Violence Intervention Program Data Repository. The Centers for Disease Control and Prevention (CDC) Social Vulnerability Index was used to characterize the social vulnerability of the census tracts of patients' residences. Analysis included descriptive statistics and time-to-event analyses estimating the probability of experiencing a recurrent firearm injury. RESULTS: We identified 10 293 acutely firearm-injured patients of whom 9553 survived the injury and comprised the analytic sample. Over a median follow-up of 3.5 years (IQR, 1.5 to 6.4 years), 1155 patients experienced a recurrent firearm injury including 5 firearm suicides and 149 fatal firearm injuries. Persons experiencing recurrent firearm injury were young (25.3 ± 9.5 years), predominantly male (93%), Black (96%), and uninsured (50%), and resided in high social vulnerability regions (65%). The estimated risk for firearm reinjury was 7% at 1 year and 17% at 8 years. LIMITATIONS: Limited data on comorbidities and patient-level social determinants of health. Inability to account for recurrent injuries presenting to nonstudy hospitals. CONCLUSION: Recurrent injury and death are frequent among survivors of firearm injury, particularly among patients from socially vulnerable areas. Our findings highlight the need for interventions to prevent recurrence. PRIMARY FUNDING SOURCE: Emergency Medicine Foundation-AFFIRM and Missouri Foundation for Health.

How decisions are made: Antibiotic stewardship in dentistry.

BACKGROUND: We performed a preimplementation assessment of workflows, resources, needs, and antibiotic prescribing practices of trainees and practicing dentists to inform the development of an antibiotic-stewardship clinical decision-support tool (CDST) for dentists. METHODS: We used a technology implementation framework to conduct the preimplementation assessment via surveys and focus groups of students, residents, and faculty members. Using Likert scales, the survey assessed baseline knowledge and confidence in dental providers' antibiotic prescribing. The focus groups gathered information on existing workflows, resources, and needs for end users for our CDST. RESULTS: Of 355 dental providers recruited to take the survey, 213 (60%) responded: 151 students, 27 residents, and 35 faculty. The average confidence in antibiotic prescribing decisions was 3.2 ± 1.0 on a scale of 1 to 5 (ie, moderate). Dental students were less confident about prescribing antibiotics than residents and faculty (P < .01). However, antibiotic prescribing knowledge was no different between dental students, residents, and faculty. The mean likelihood of prescribing an antibiotic when it was not needed was 2.7 ± 0.6 on a scale of 1 to 5 (unlikely to maybe) and was not meaningfully different across subgroups (P = .10). We had 10 participants across 3 focus groups: 7 students, 2 residents, and 1 faculty member. Four major themes emerged, which indicated that dentists: (1) make antibiotic prescribing decisions based on anecdotal experiences; (2) defer to physicians' recommendations; (3) have limited access to evidence-based resources; and (4) want CDST for antibiotic prescribing. CONCLUSIONS: Dentists' confidence in antibiotic prescribing increased by training level, but knowledge did not. Trainees and practicing dentists would benefit from a CDST to improve appropriateness of antibiotic prescribing.

Implementing a hospital-based violence intervention program for assault-injured youth: implications for social work practice.

Youth in the U.S. experience a high rate of assault-related injuries resulting in physical, psychological and social sequelae that require a wide range of services after discharge from the hospital. Hospital-based violence intervention programs (HVIP's) have been developed to engage youth in services designed to reduce the incidence of violent injury in young people. HVIP's combine the efforts of medical staff with community-based partners to provide trauma-informed care to violently-injured people and have been found to be a cost-effective means to reduce re-injury rates and improve social and behavioral health outcomes. Few studies have explored the organizational and community level factors that impact implementation of these important and complex interventions. The objective of this study was to develop an in-depth understanding of the factors that impact HVIP implementation from the perspectives of 41 stakeholders through qualitative interviews. Thematic analysis generated three themes that included the importance of integrated, collaborative care, the need for providers who can perform multiple service roles and deploy a range of skills, and the importance of engaging clients through extended contact. In this article we explore these themes and their implications for healthcare social work.

Endometrial cancer survivors' perceptions of their cardiovascular disease risk (results from WF-1804CD AH-HA).

OBJECTIVE: Despite considerable burden of cardiovascular disease (CVD), data on endometrial cancer survivors' CVD perceptions are lacking. We assessed survivors' perspectives on addressing CVD risk during oncology care. METHODS: This cross-sectional analysis utilized data from an ongoing trial of an EHR heart health tool (R01CA226078 & UG1CA189824) conducted through the NCI Community Oncology Research Program (NCORP, WF-1804CD). Endometrial cancer survivors post-potentially curative treatment were recruited from community practices and completed a pre-visit baseline survey, including American Heart Association Simple 7 CVD factors. Likert-type questions assessed confidence in understanding CVD risk, CVD risk perception, and desired discussion during oncology care. Medical record abstraction ascertained data on CVD and cancer characteristics. RESULTS: Survivors (N = 55, median age = 62; 62% 0-2 years post-diagnosis) were predominately white, non-Hispanic (87%). Most agreed/strongly agreed heart disease poses a risk to their health (87%) and oncology providers should talk to patients about heart health (76%). Few survivors reported smoking (12%) but many had poor/intermediate values for blood pressure (95%), body mass index (93%), fasting glucose/A1c (60%), diet (60%), exercise (47%) and total cholesterol (53%). 16% had not seen a PCP in the last year; these survivors were more likely to report financial hardship (22% vs 0%; p = 0.02). Most reported readiness to take steps to maintain or improve heart health (84%). CONCLUSIONS: Discussions of CVD risk during routine oncology care are likely to be well received by endometrial cancer survivors. Strategies are needed to implement CVD risk assessment guidelines and to enhance communication and referrals with primary care. Clinical Trials #: NCT03935282.

Toward rational use of repeat imaging in children with mild traumatic brain injuries and intracranial injuries.

OBJECTIVE: Limited evidence exists on the utility of repeat neuroimaging in children with mild traumatic brain injuries (mTBIs) and intracranial injuries (ICIs). Here, the authors identified factors associated with repeat neuroimaging and predictors of hemorrhage progression and/or neurosurgical intervention. METHODS: The authors performed a multicenter, retrospective cohort study of children at four centers of the Pediatric TBI Research Consortium. All patients were ≤ 18 years and presented within 24 hours of injury with a Glasgow Coma Scale score of 13-15 and evidence of ICI on neuroimaging. The outcomes of interest were 1) whether patients underwent repeat neuroimaging during index admission, and 2) a composite outcome of progression of previously identified hemorrhage ≥ 25% and/or repeat imaging as an indication for subsequent neurosurgical intervention. The authors performed multivariable logistic regression and report odds ratios and 95% confidence intervals. RESULTS: A total of 1324 patients met inclusion criteria; 41.3% of patients underwent repeat imaging. Repeat imaging was associated with clinical change in 4.8% of patients; the remainder of the imaging tests were for routine surveillance (90.9%) or of unclear prompting (4.4%). In 2.6% of patients, repeat imaging findings were reported as an indication for neurosurgical intervention. While many factors were associated with repeat neuroimaging, only epidural hematoma (OR 3.99, 95% CI 2.22-7.15), posttraumatic seizures (OR 2.95, 95% CI 1.22-7.41), and age ≥ 2 years (OR 2.25, 95% CI 1.16-4.36) were significant predictors of hemorrhage progression and/or neurosurgery. Of patients without any of these risk factors, none underwent neurosurgical intervention. CONCLUSIONS: Repeat neuroimaging was commonly used but uncommonly associated with clinical deterioration. Although several factors were associated with repeat neuroimaging, only posttraumatic seizures, age ≥ 2 years, and epidural hematoma were significant predictors of hemorrhage progression and/or neurosurgery. These results provide the foundation for evidence-based repeat neuroimaging practices in children with mTBI and ICI.

A Regional Approach to Hospital-Based Violence Intervention Programs Through LOV.

CONTEXT: Community violence is an underaddressed public health threat. Hospital-based violence intervention programs (HVIPs) have been used to address the root causes of violence and prevent reinjury. OBJECTIVE: In this article, we describe the methodology of the St Louis Region-wide HVIP, Life Outside Violence (LOV) program, and provide preliminary process outcomes. DESIGN: Life Outside Violence mentors intervene following a violent injury to decrease risk of subsequent victimization and achieve goals unique to each participant by providing therapeutic counseling and case management services to patients and their families. PARTICIPANTS AND SETTING: Eligible patients are victims of violent injury between the ages of 8 and 24 years, who are residents of St Louis, Missouri, and present for care at a LOV partner adult or pediatric level I trauma hospital. INTERVENTION: Enrolled participants receive program services for 6 to 12 months and complete an individual treatment plan. MAIN OUTCOME MEASURES: In this article, we report LOV operational methodology, as well as process metrics, including program enrollment, graduation, and qualitative data on program implementation. RESULTS: From August 15, 2018, through April 30, 2022, 1750 LOV-eligible violently injured patients presented to a partner hospital, 349 were approached for program enrollment, and 206 consented to enroll in the program. During this pilot phase, 91 participants graduated from the LOV program and have process output data available for analysis. CONCLUSIONS: Life Outside Violence has been implemented into clinical practice as the first HVIP to influence across an entire region through partnership with multiple university and hospital systems. It is our hope that methods shared in this article will serve as a primer for organizations hoping to implement and expand HVIPs to interrupt community violence at the regional level.

A systematic review of recurrent firearm injury rates in the United States.

OBJECTIVES: To conduct a systematic review of methodologies, data sources, and best practices for identifying, calculating, and reporting recurrent firearm injury rates in the United States. METHODS: In accordance with PRISMA guidelines, we searched seven electronic databases on December 16, 2021, for peer-reviewed articles that calculated recurrent firearm injury in generalizable populations. Two reviewers independently assessed the risk of bias, screened the studies, extracted data, and a third resolved conflicts. FINDINGS: Of the 918 unique articles identified, 14 met our inclusion criteria and reported recurrent firearm injury rates from 1% to 9.5%. We observed heterogeneity in study methodologies, including data sources utilized, identification of subsequent injury, follow-up times, and the types of firearm injuries studied. Data sources ranged from single-site hospital medical records to comprehensive statewide records comprising medical, law enforcement, and social security death index data. Some studies applied machine learning to electronic health records to differentiate subsequent new firearm injuries from the index injury, while others classified all repeat firearm-related hospital admissions after variably defined cut-off times as a new injury. Some studies required a minimum follow-up observation period after the index injury while others did not. Four studies conducted survival analyses, albeit using different methodologies. CONCLUSIONS: Variability in both the data sources and methods used to evaluate and report recurrent firearm injury limits individual study generalizability of individual and societal factors that influence recurrent firearm injury. Our systematic review highlights the need for development, dissemination, and implementation of standard practices for calculating and reporting recurrent firearm injury.

Leveraging Artificial Intelligence and Synthetic Data Derivatives for Spine Surgery Research.

STUDY DESIGN: Retrospective cohort study. OBJECTIVES: Leveraging electronic health records (EHRs) for spine surgery research is impeded by concerns regarding patient privacy and data ownership. Synthetic data derivatives may help overcome these limitations. This study's objective was to validate the use of synthetic data for spine surgery research. METHODS: Data came from the EHR from 15 hospitals. Patients that underwent anterior cervical or posterior lumbar fusion (2010-2020) were included. Real data were obtained from the EHR. Synthetic data was generated to simulate the properties of the real data, without maintaining a one-to-one correspondence with real patients. Within each cohort, ability to predict 30-day readmissions and 30-day complications was evaluated using logistic regression and extreme gradient boosting machines (XGBoost). RESULTS: We identified 9,072 real and 9,088 synthetic cervical fusion patients. Descriptive characteristics were nearly identical between the 2 datasets. When predicting readmission, models built using real and synthetic data both had c-statistics of .69-.71 using logistic regression and XGBoost. Among 12,111 real and 12,126 synthetic lumbar fusion patients, descriptive characteristics were nearly the same for most variables. Using logistic regression and XGBoost to predict readmission, discrimination was similar with models built using real and synthetic data (c-statistics .66-.69). When predicting complications, models derived using real and synthetic data showed similar discrimination in both cohorts. Despite some differences, the most influential predictors were similar in the real and synthetic datasets. CONCLUSION: Synthetic data replicate most descriptive and predictive properties of real data, and therefore may expand EHR research in spine surgery.

An exploration of factors impacting implementation of a multisystem hospital-based violence intervention program.

Community violence, particularly gun violence, is a leading cause of morbidity and mortality in young people in the United States. Because persons experiencing violence-related injuries are likely to receive medical care through emergency departments, hospitals are increasingly seen as primary locations for violence intervention services. Currently, there is little research on how best to implement hospital-based violence intervention programs (HVIPs) across large hospital systems. This study explored the factors influencing the implementation of a multi-site HVIP using qualitative interviews with a purposive sample of 20 multidisciplinary stakeholders. Thematic analysis was used to generate several themes that included: (1) reframing gun violence as a public health issue; (2) developing networks of community-hospital-university partners; (3) demonstrating effectiveness and community benefit; and (4) establishing patient engagement pathways. Effective implementation and sustainment of HVIPs requires robust and sustained multidisciplinary partnerships within and across hospital systems and the establishment of HVIPs as a standard of care.

Estrogen hormone is an essential sex factor inhibiting inflammation and immune response in COVID-19.

Although vaccines have been evaluated and approved for SARS-CoV-2 infection prevention, there remains a lack of effective treatments to reduce the mortality of COVID-19 patients already infected with SARS-CoV-2. The global data on COVID-19 showed that men have a higher mortality rate than women. We further observed that the proportion of mortality of females increases starting from around the age of 55 significantly. Thus, sex is an essential factor associated with COVID-19 mortality, and sex related genetic factors could be interesting mechanisms and targets for COVID-19 treatment. However, the associated sex factors and signaling pathways remain unclear. Here, we propose to uncover the potential sex associated factors using systematic and integrative network analysis. The unique results indicated that estrogens, e.g., estrone and estriol, (1) interacting with ESR1/2 receptors, (2) can inhibit SARS-CoV-2 caused inflammation and immune response signaling in host cells; and (3) estrogens are associated with the distinct fatality rates between male and female COVID-19 patients. Specifically, a high level of estradiol protects young female COVID-19 patients, and estrogens drop to an extremely low level in females after about 55 years of age causing the increased fatality rate of women. In conclusion, estrogen, interacting with ESR1/2 receptors, is an essential sex factor that protects COVID-19 patients from death by inhibiting inflammation and immune response caused by SARS-CoV-2 infection. Moreover, medications boosting the down-stream signaling of ESR1/ESR2, or inhibiting the inflammation and immune-associated targets on the signaling network can be potentially effective or synergistic combined with other existing drugs for COVID-19 treatment.

Life's Essential 8: Updating and Enhancing the American Heart Association's Construct of Cardiovascular Health: A Presidential Advisory From the American Heart Association.

In 2010, the American Heart Association defined a novel construct of cardiovascular health to promote a paradigm shift from a focus solely on disease treatment to one inclusive of positive health promotion and preservation across the life course in populations and individuals. Extensive subsequent evidence has provided insights into strengths and limitations of the original approach to defining and quantifying cardiovascular health. In response, the American Heart Association convened a writing group to recommend enhancements and updates. The definition and quantification of each of the original metrics (Life's Simple 7) were evaluated for responsiveness to interindividual variation and intraindividual change. New metrics were considered, and the age spectrum was expanded to include the entire life course. The foundational contexts of social determinants of health and psychological health were addressed as crucial factors in optimizing and preserving cardiovascular health. This presidential advisory introduces an enhanced approach to assessing cardiovascular health: Life's Essential 8. The components of Life's Essential 8 include diet (updated), physical activity, nicotine exposure (updated), sleep health (new), body mass index, blood lipids (updated), blood glucose (updated), and blood pressure. Each metric has a new scoring algorithm ranging from 0 to 100 points, allowing generation of a new composite cardiovascular health score (the unweighted average of all components) that also varies from 0 to 100 points. Methods for implementing cardiovascular health assessment and longitudinal monitoring are discussed, as are potential data sources and tools to promote widespread adoption in policy, public health, clinical, institutional, and community settings.

Status of Cardiovascular Health in US Adults and Children Using the American Heart Association's New "Life's Essential 8" Metrics: Prevalence Estimates From the National Health and Nutrition Examination Survey (NHANES), 2013 Through 2018.

BACKGROUND: The American Heart Association recently published an updated algorithm for quantifying cardiovascular health (CVH)-the Life's Essential 8 score. We quantified US levels of CVH using the new score. METHODS: We included individuals ages 2 through 79 years (not pregnant or institutionalized) who were free of cardiovascular disease from the National Health and Nutrition Examination Surveys in 2013 through 2018. For all participants, we calculated the overall CVH score (range, 0 [lowest] to 100 [highest]), as well as the score for each component of diet, physical activity, nicotine exposure, sleep duration, body mass index, blood lipids, blood glucose, and blood pressure, using published American Heart Association definitions. Sample weights and design were incorporated in calculating prevalence estimates and standard errors using standard survey procedures. CVH scores were assessed across strata of age, sex, race and ethnicity, family income, and depression. RESULTS: There were 23 409 participants, representing 201 728 000 adults and 74 435 000 children. The overall mean CVH score was 64.7 (95% CI, 63.9-65.6) among adults using all 8 metrics and 65.5 (95% CI, 64.4-66.6) for the 3 metrics available (diet, physical activity, and body mass index) among children and adolescents ages 2 through 19 years. For adults, there were significant differences in mean overall CVH scores by sex (women, 67.0; men, 62.5), age (range of mean values, 62.2-68.7), and racial and ethnic group (range, 59.7-68.5). Mean scores were lowest for diet, physical activity, and body mass index metrics. There were large differences in mean scores across demographic groups for diet (range, 23.8-47.7), nicotine exposure (range, 63.1-85.0), blood glucose (range, 65.7-88.1), and blood pressure (range, 49.5-84.0). In children, diet scores were low (mean 40.6) and were progressively lower in higher age groups (from 61.1 at ages 2 through 5 to 28.5 at ages 12 through 19); large differences were also noted in mean physical activity (range, 63.1-88.3) and body mass index (range, 74.4-89.4) scores by sociodemographic group. CONCLUSIONS: The new Life's Essential 8 score helps identify large group and individual differences in CVH. Overall CVH in the US population remains well below optimal levels and there are both broad and targeted opportunities to monitor, preserve, and improve CVH across the life course in individuals and the population.

Individual-Level and Neighborhood-Level Factors Associated with Longitudinal Changes in Cardiometabolic Measures in Participants of a Clinic-Based Care Coordination Program: A Secondary Data Analysis.

Background: Identifying individual and neighborhood-level factors associated with worsening cardiometabolic risks despite clinic-based care coordination may help identify candidates for supplementary team-based care. Methods: Secondary data analysis of data from a two-year nurse-led care coordination program cohort of Medicare, Medicaid, dual-eligible adults, Leveraging Information Technology to Guide High Tech, High Touch Care (LIGHT2), from ten Midwestern primary care clinics in the U.S. Outcome Measures: Hemoglobin A1C, low-density-lipoprotein (LDL) cholesterol, and blood pressure. Multivariable generalized linear regression models assessed individual and neighborhood-level factors associated with changes in outcome measures from before to after completion of the LIGHT2 program. Results: 6378 participants had pre-and post-intervention levels reported for at least one outcome measure. In adjusted models, higher pre-intervention cardiometabolic measures were associated with worsening of all cardiometabolic measures. Women had worsening LDL-cholesterol compared with men. Women with pre-intervention HbA1c > 6.8% and systolic blood pressure > 131 mm of Hg had worse post-intervention HbA1c and systolic blood pressure compared with men. Adding individual's neighborhood-level risks did not change effect sizes significantly. Conclusions: Increased cardiometabolic risks and gender were associated with worsening cardiometabolic outcomes. Understanding unresolved gender-specific needs and preferences of patients with increased cardiometabolic risks may aid in tailoring clinic-community-linked care planning.

Usability and Acceptability of Clinical Decision Support Based on the KIIDS-TBI Tool for Children with Mild Traumatic Brain Injuries and Intracranial Injuries.

BACKGROUND: The Kids Intracranial Injury Decision Support tool for Traumatic Brain Injury (KIIDS-TBI) tool is a validated risk prediction model for managing children with mild traumatic brain injuries (mTBI) and intracranial injuries. Electronic clinical decision support (CDS) may facilitate the clinical implementation of this evidence-based guidance. OBJECTIVE: Our objective was to evaluate the acceptability and usability of an electronic CDS tool for managing children with mTBI and intracranial injuries. METHODS: Emergency medicine and neurosurgery physicians (10 each) from 10 hospitals in the United States were recruited to participate in usability testing of a novel CDS prototype in a simulated electronic health record environment. Testing included a think-aloud protocol, an acceptability and usability survey, and a semi-structured interview. The prototype was updated twice during testing to reflect user feedback. Usability problems recorded in the videos were categorized using content analysis. Interview transcripts were analyzed using thematic analysis. RESULTS: Among the 20 participants, most worked at teaching hospitals (80%), freestanding children's hospitals (95%), and level-1 trauma centers (75%). During the two prototype updates, problems with clarity of terminology and navigating through the CDS interface were identified and corrected. Corresponding to these changes, the number of usability problems decreased from 35 in phase 1 to 8 in phase 3 and the number of mistakes made decreased from 18 (phase 1) to 2 (phase 3). Through the survey, participants found the tool easy to use (90%), useful for determining a patient's level of care (95%), and likely to improve resource use (90%) and patient safety (79%). Interview themes related to the CDS's ability to support evidence-based decision-making and improve clinical workflow proposed implementation strategies and potential pitfalls. CONCLUSION: After iterative evaluation and refinement, the KIIDS-TBI CDS tool was found to be highly usable and useful for aiding the management of children with mTBI and intracranial injuries.

Measures of Intracranial Injury Size Do Not Improve Clinical Decision Making for Children With Mild Traumatic Brain Injuries and Intracranial Injuries.

BACKGROUND: When evaluating children with mild traumatic brain injuries (mTBIs) and intracranial injuries (ICIs), neurosurgeons intuitively consider injury size. However, the extent to which such measures (eg, hematoma size) improve risk prediction compared with the kids intracranial injury decision support tool for traumatic brain injury (KIIDS-TBI) model, which only includes the presence/absence of imaging findings, remains unknown. OBJECTIVE: To determine the extent to which measures of injury size improve risk prediction for children with mild traumatic brain injuries and ICIs. METHODS: We included children ≤18 years who presented to 1 of the 5 centers within 24 hours of TBI, had Glasgow Coma Scale scores of 13 to 15, and had ICI on neuroimaging. The data set was split into training (n = 1126) and testing (n = 374) cohorts. We used generalized linear modeling (GLM) and recursive partitioning (RP) to predict the composite of neurosurgery, intubation >24 hours, or death because of TBI. Each model's sensitivity/specificity was compared with the validated KIIDS-TBI model across 3 decision-making risk cutoffs (<1%, <3%, and <5% predicted risk). RESULTS: The GLM and RP models included similar imaging variables (eg, epidural hematoma size) while the GLM model incorporated additional clinical predictors (eg, Glasgow Coma Scale score). The GLM (76%-90%) and RP (79%-87%) models showed similar specificity across all risk cutoffs, but the GLM model had higher sensitivity (89%-96% for GLM; 89% for RP). By comparison, the KIIDS-TBI model had slightly higher sensitivity (93%-100%) but lower specificity (27%-82%). CONCLUSION: Although measures of ICI size have clear intuitive value, the tradeoff between higher specificity and lower sensitivity does not support the addition of such information to the KIIDS-TBI model.

Demonstrating an approach for evaluating synthetic geospatial and temporal epidemiologic data utility: results from analyzing >1.8 million SARS-CoV-2 tests in the United States National COVID Cohort Collaborative (N3C).

OBJECTIVE: This study sought to evaluate whether synthetic data derived from a national coronavirus disease 2019 (COVID-19) dataset could be used for geospatial and temporal epidemic analyses. MATERIALS AND METHODS: Using an original dataset (n = 1 854 968 severe acute respiratory syndrome coronavirus 2 tests) and its synthetic derivative, we compared key indicators of COVID-19 community spread through analysis of aggregate and zip code-level epidemic curves, patient characteristics and outcomes, distribution of tests by zip code, and indicator counts stratified by month and zip code. Similarity between the data was statistically and qualitatively evaluated. RESULTS: In general, synthetic data closely matched original data for epidemic curves, patient characteristics, and outcomes. Synthetic data suppressed labels of zip codes with few total tests (mean = 2.9 ± 2.4; max = 16 tests; 66% reduction of unique zip codes). Epidemic curves and monthly indicator counts were similar between synthetic and original data in a random sample of the most tested (top 1%; n = 171) and for all unsuppressed zip codes (n = 5819), respectively. In small sample sizes, synthetic data utility was notably decreased. DISCUSSION: Analyses on the population-level and of densely tested zip codes (which contained most of the data) were similar between original and synthetically derived datasets. Analyses of sparsely tested populations were less similar and had more data suppression. CONCLUSION: In general, synthetic data were successfully used to analyze geospatial and temporal trends. Analyses using small sample sizes or populations were limited, in part due to purposeful data label suppression-an attribute disclosure countermeasure. Users should consider data fitness for use in these cases.

Linking out-of-hospital deaths with a regional hospital-based firearm injury database: a clinical researcher's guide to accessing data from the National Death Index.

IntroductionFirearm injuries are a public health crisis in the US. The National Death Index (NDI) is a well-established, comprehensive database managed by the National Center for Health Statistics at the CDC. In this methodology paper we describe our experience accessing and linking data from the NDI to our regional, hospital-based violent injury database to identify out-of-hospital deaths from firearms. METHODS: We outline the key steps of our submission to the NDI. Data were collected from research team meeting notes, team member emails with NDI staff, and information provided from the NDI website and supplementary guides. Few of our collaborators or university partner investigators had accessed or used data from the NDI. We discuss the online NDI Processing Portal data request, data preparation and receipt from the NDI, troubleshooting tips, and a timeline of events. RESULTS: Our query to the NDI returned 12 034 records of 12 219 firearm-injured patient records from 2010 and 2019. The record match rate was 98.5%. DISCUSSION: Linking hospital-based data sets with NDI data can provide valuable information on out-of-hospital deaths. This has the potential to improve the quality of longitudinal morbidity and mortality calculations in hospital-based patient cohorts. We encountered logistic and administrative challenges in completing the online NDI Processing Portal and in preparing and receiving data from the NDI. It is our hope that the lessons learnt presented herein will help facilitate easy and streamlined acquisition of valuable NDI data for other clinical researchers. WHAT THIS STUDY ADDS: - A step-by-step guide for clinical researchers of how to apply to access data from the National Death Index (NDI).- Advice and lessons learned on how to efficiently and effectively access data from the NDI.- A well-described methodology to improve the quality of longitudinal morbdity and mortality calculations in hospital-based cohorts of firearm injured patients.What is already known on this subject:- There is a need for robust, longitudinal data sources that reliably track morbidity and mortality among firearm injured patients in the United States.- The NDI is a well-established, comprehensive database that holds death records for all 50 states, which provides valuable mortality data to the public health and medical research community.