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.

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.

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.

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.

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.

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.

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.

Achieving Optimal Population Cardiovascular Health Requires an Interdisciplinary Team and a Learning Healthcare System: A Scientific Statement From the American Heart Association.

Population cardiovascular health, or improving cardiovascular health among patients and the population at large, requires a redoubling of primordial and primary prevention efforts as declines in cardiovascular disease mortality have decelerated over the past decade. Great potential exists for healthcare systems-based approaches to aid in reversing these trends. A learning healthcare system, in which population cardiovascular health metrics are measured, evaluated, intervened on, and re-evaluated, can serve as a model for developing the evidence base for developing, deploying, and disseminating interventions. This scientific statement on optimizing population cardiovascular health summarizes the current evidence for such an approach; reviews contemporary sources for relevant performance and clinical metrics; highlights the role of implementation science strategies; and advocates for an interdisciplinary team approach to enhance the impact of this work.

The impact of neighborhood socioeconomic status on retention in care and viral suppression among people living with HIV.

Our study combined publicly available neighborhood socioeconomic status (nSES) data from the U.S. Census and clinical data to investigate the relationships between nSES, retention in care (RIC) and viral suppression (VS). Data from 2275 patients were extracted from 2009 to 2015 from a midwestern infectious diseases clinic. RIC was defined as patients who kept ≥ 3 visits and VS as an average viral load <200 copies/mL during their index year of study. Logistic regression models provided estimates for neighborhood-level and patient-level variables. In multivariable models, patients living in zip codes with low disability rates (1.50, 1.30-1.70), who wereolder (1.02, 1.01-1.03), and receiving antiretroviral therapy (ART; 3.81, 3.56-4.05) were more likely to have RIC, while those who were unemployed (0.72, 0.45-0.98) and self-reported as BIPOC (0.79, 0.64-0.97) were less likely to have RIC. None of the nSES variables were significantly associated with VS in multivariable models, yet older age (1.05, 1.04-1.05) and self-reported as BIPOC (1.68, 1.36-2.09) were modestly associated with VS, and receiving ART (6.14, 5.86-6.42) was a strong predictor of VS. In multivariable models, nSES variables were independently predictive more than of patient-level variables, for RIC but not VS.

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.

Predicting cardiovascular health trajectories in time-series electronic health records with LSTM models.

BACKGROUND: Cardiovascular disease (CVD) is the leading cause of death in the United States (US). Better cardiovascular health (CVH) is associated with CVD prevention. Predicting future CVH levels may help providers better manage patients' CVH. We hypothesized that CVH measures can be predicted based on previous measurements from longitudinal electronic health record (EHR) data. METHODS: The Guideline Advantage (TGA) dataset was used and contained EHR data from 70 outpatient clinics across the United States (US). We studied predictions of 5 CVH submetrics: smoking status (SMK), body mass index (BMI), blood pressure (BP), hemoglobin A1c (A1C), and low-density lipoprotein (LDL). We applied embedding techniques and long short-term memory (LSTM) networks - to predict future CVH category levels from all the previous CVH measurements of 216,445 unique patients for each CVH submetric. RESULTS: The LSTM model performance was evaluated by the area under the receiver operator curve (AUROC): the micro-average AUROC was 0.99 for SMK prediction; 0.97 for BMI; 0.84 for BP; 0.91 for A1C; and 0.93 for LDL prediction. Model performance was not improved by using all 5 submetric measures compared with using single submetric measures. CONCLUSIONS: We suggest that future CVH levels can be predicted using previous CVH measurements for each submetric, which has implications for population cardiovascular health management. Predicting patients' future CVH levels might directly increase patient CVH health and thus quality of life, while also indirectly decreasing the burden and cost for clinical health system caused by CVD and cancers.

Women and ethnoracial minorities with poor cardiovascular health measures associated with a higher risk of developing mood disorder.

BACKGROUND: Mood disorders (MDS) are a type of mental health illness that effects millions of people in the United States. Early prediction of MDS can give providers greater opportunity to treat these disorders. We hypothesized that longitudinal cardiovascular health (CVH) measurements would be informative for MDS prediction. METHODS: To test this hypothesis, the American Heart Association's Guideline Advantage (TGA) dataset was used, which contained longitudinal EHR from 70 outpatient clinics. The statistical analysis and machine learning models were employed to identify the associations of the MDS and the longitudinal CVH metrics and other confounding factors. RESULTS: Patients diagnosed with MDS consistently had a higher proportion of poor CVH compared to patients without MDS, with the largest difference between groups for Body mass index (BMI) and Smoking. Race and gender were associated with status of CVH metrics. Approximate 46% female patients with MDS had a poor hemoglobin A1C compared to 44% of those without MDS; 62% of those with MDS had poor BMI compared to 47% of those without MDS; 59% of those with MDS had poor blood pressure (BP) compared to 43% of those without MDS; and 43% of those with MDS were current smokers compared to 17% of those without MDS. CONCLUSIONS: Women and ethnoracial minorities with poor cardiovascular health measures were associated with a higher risk of development of MDS, which indicated the high utility for using routine medical records data collected in care to improve detection and treatment for MDS among patients with poor CVH.

Electronic clinical decision support for children with minor head trauma and intracranial injuries: a sociotechnical analysis.

BACKGROUND: Current management of children with minor head trauma (MHT) and intracranial injuries is not evidence-based and may place some children at risk of harm. Evidence-based electronic clinical decision support (CDS) for management of these children may improve patient safety and decrease resource use. To guide these efforts, we evaluated the sociotechnical environment impacting the implementation of electronic CDS, including workflow and communication, institutional culture, and hardware and software infrastructure, among other factors. METHODS: Between March and May, 2020 semi-structured qualitative focus group interviews were conducted to identify sociotechnical influences on CDS implementation. Physicians from neurosurgery, emergency medicine, critical care, and pediatric general surgery were included, along with information technology specialists. Participants were recruited from nine health centers in the United States. Focus group transcripts were coded and analyzed using thematic analysis. The final themes were then cross-referenced with previously defined sociotechnical dimensions. RESULTS: We included 28 physicians and four information technology specialists in seven focus groups (median five participants per group). Five physicians were trainees and 10 had administrative leadership positions. Through inductive thematic analysis, we identified five primary themes: (1) clinical impact; (2) stakeholders and users; (3) tool content; (4) clinical practice integration; and (5) post-implementation evaluation measures. Participants generally supported using CDS to determine an appropriate level-of-care for these children. However, some had mixed feelings regarding how the tool could best be used by different specialties (e.g. use by neurosurgeons versus non-neurosurgeons). Feedback from the interviews helped refine the tool content and also highlighted potential technical and workflow barriers to address prior to implementation. CONCLUSIONS: We identified key factors impacting the implementation of electronic CDS for children with MHT and intracranial injuries. These results have informed our implementation strategy and may also serve as a template for future efforts to implement health information technology in a multidisciplinary, emergency setting.

Mobile Health Applications, Cancer Survivors, and Lifestyle Modification: An Integrative Review.

Cancer survivors' well-being is threatened by the risk of cancer recurrence and the increased risk of chronic diseases resulting from cancer treatments. Improving lifestyle behaviors attenuates these risks. Traditional approaches to lifestyle modification (ie, counseling) are expensive, require significant human resources, and are difficult to scale. Mobile health interventions offer a novel alternative to traditional approaches. However, to date, systematic reviews have yet to examine the use of mobile health interventions for lifestyle behavior improvement among cancer survivors. The objectives of this integrative review were to synthesize research findings, critically appraise the scientific literature, examine the use of theory in intervention design, and identify survivors' preferences in using mobile health interventions for lifestyle improvement. Nineteen articles met eligibility requirements. Only two studies used quantitative methods. Study quality was low, and only one study reported the use of theory in app design. Unfortunately, the evidence has not yet sufficiently matured, in quality or in rigor, to make recommendations on how to improve health behaviors or outcomes. However, six themes emerged as important considerations for intervention development for cancer survivors (app features/functionality, social relationships/support, provider relationships/support, app content, app acceptability, and barriers to use). These findings underscored the need for rigorous, efficacy studies before the use of mobile health interventions can be safely recommended for cancer survivors.

A Randomized Controlled Trial Evaluating the BREASTChoice Tool for Personalized Decision Support About Breast Reconstruction After Mastectomy.

OBJECTIVE: To evaluate a web-based breast reconstruction decision aid, BREASTChoice. SUMMARY AND BACKGROUND DATA: Although postmastectomy breast reconstruction can restore quality of life and body image, its morbidity remains substantial. Many patients lack adequate knowledge to make informed choices. Decisions are often discordant with patients' preferences. METHODS: Adult women with stages 0-III breast cancer considering postmastectomy breast reconstruction with no previous reconstruction were randomized to BREASTChoice or enhanced usual care (EUC). RESULTS: Three hundred seventy-six patients were screened; 120 of 172 (69.8%) eligible patients enrolled. Mean age = 50.7 years (range 25-77). Most were Non-Hispanic White (86.3%) and had a college degree (64.3%). Controlling for health literacy and provider seen, BREASTChoice users had higher knowledge than those in EUC (84.6% vs. 58.2% questions correct; P < 0.001). Those using BREASTChoice were more likely to know that reconstruction typically requires more than 1 surgery, delayed reconstruction lowers one's risk, and implants may need replacement over time (all ps < 0.002). BREASTChoice compared to EUC participants also felt more confident understanding reconstruction information (P = 0.009). There were no differences between groups in decisional conflict, decision process quality, shared decision-making, quality of life, or preferences (all ps > 0.05). There were no differences in consultation length between BREASTChoice and EUC groups (mean = 29.7 vs. 30.0 minutes; P > 0.05). BREASTChoice had high usability (mean score = 6.3/7). Participants completed BREASTChoice in about 27 minutes. CONCLUSIONS: BREASTChoice can improve breast reconstruction decision quality by improving patients' knowledge and providing them with personalized risk estimates. More research is needed to facilitate point-of-care decision support and examine BREASTChoice's impact on patients' decisions over time.

Coronary heart disease and mortality following a breast cancer diagnosis.

BACKGROUND: Coronary heart disease (CHD) is a leading cause of morbidity and mortality for breast cancer survivors, yet the joint effect of adverse cardiovascular health (CVH) and cardiotoxic cancer treatments on post-treatment CHD and death has not been quantified. METHODS: We conducted statistical and machine learning approaches to evaluate 10-year risk of these outcomes among 1934 women diagnosed with breast cancer during 2006 and 2007. Overall CVH scores were classified as poor, intermediate, or ideal for 5 factors, smoking, body mass index, blood pressure, glucose/hemoglobin A1c, and cholesterol from clinical data within 5 years prior to the breast cancer diagnosis. The receipt of potentially cardiotoxic breast cancer treatments was indicated if the patient received anthracyclines or hormone therapies. We modeled the outcomes of post-cancer diagnosis CHD and death, respectively. RESULTS: Results of these approaches indicated that the joint effect of poor CVH and receipt of cardiotoxic treatments on CHD (75.9%) and death (39.5%) was significantly higher than their independent effects [poor CVH (55.9%) and cardiotoxic treatments (43.6%) for CHD, and poor CVH (29.4%) and cardiotoxic treatments (35.8%) for death]. CONCLUSIONS: Better CVH appears to be protective against the development of CHD even among women who had received potentially cardiotoxic treatments. This study determined the extent to which attainment of ideal CVH is important not only for CHD and mortality outcomes among women diagnosed with breast cancer.

County socioeconomic characteristics and heart transplant outcomes in the United States.

BACKGROUND: Geographic disparities in survival after heart transplantation have received mixed support in prior studies, and specific geographic characteristics that might be responsible for these differences are unclear. We tested for differences in heart transplant outcomes across United States (US) counties after adjustment for individual-level covariates. Our secondary aim was to evaluate whether specific county-level socioeconomic characteristics explained geographic disparities in survival. METHODS: Data on patients aged ≥18 years undergoing a first-time heart transplant between July 2006 and December 2014 were obtained from the United Network for Organ Sharing. Residents of counties represented by <5 patients were excluded. Patient survival (censored in March 2016) was analyzed using multivariable Cox regression. Shared frailty models were used to test for residual differences in overall all-cause mortality across counties after adjusting for recipient and donor characteristics. Measures of county economic disadvantage, inequality, and racial segregation were obtained from US Census data and coded into quintiles. A likelihood ratio test determined whether adjusting for each county measure improved the fit of the Cox model. RESULTS: Multivariable analysis of 10,879 heart transplant recipients found that, adjusting for individual-level characteristics, there remained statistically significant variation in mortality hazard across US counties (P=.004). Adjusting for quintiles of community disadvantage, economic inequality, or racial segregation did not significantly improve model fit (likelihood ratio test P=.092, P=.273, and P=.107, respectively) and did not explain residual differences in patient survival across counties. CONCLUSIONS: Heart transplantation outcomes vary by county, but this difference is not attributable to county-level socioeconomic disadvantage.

Evaluation of the modified FINDRISC to identify individuals at high risk for diabetes among middle-aged white and black ARIC study participants.

OBJECTIVE: To evaluate a modified Finnish Diabetes Risk Score (FINDRISC) for predicting the risk of incident diabetes among white and black middle-aged participants from the Atherosclerosis Risk in Communities (ARIC) study. RESEARCH DESIGN AND METHODS: We assessed 9754 ARIC cohort participants who were free of diabetes at baseline. Logistic regression and receiver operator characteristic (ROC) curves were used to evaluate a modified FINDRISC for predicting incident diabetes after 9 years of follow-up, overall and by race/gender group. The modified FINDRISC used comprised age, body mass index, waist circumference, blood pressure medication and family history. RESULTS: The mean FINDRISC (range, 2 [lowest risk] to 17 [highest risk]) for black women was higher (9.9 ± 3.6) than that for black men (7.6 ± 3.9), white women (8.0 ± 3.6) and white men (7.6 ± 3.5). The incidence of diabetes increased generally across deciles of FINDRISC for all 4 race/gender groups. ROC curve statistics for the FINDRISC showed the highest area under the curve for white women (0.77) and the lowest for black men (0.70). CONCLUSIONS: We used a modified FINDRISC to predict the 9-year risk of incident diabetes in a biracial US population. The modified risk score can be useful for early screening of incident diabetes in biracial populations, which may be helpful for early interventions to delay or prevent diabetes.