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Pediatric positive health refers to children's assessments of their well-being. The purpose of this study was to contrast positive health for children aged 8 to 17 years with and without chronic physical and mental health conditions.Data were drawn from the National Institutes of Health Environmental influences on Child Health Outcomes (ECHO) research program. Participants included 1764 children ages 8 to 17 years from 13 ECHO cohorts. We measured positive health using the Patient-Reported Outcomes Measurement Information System (PROMIS) Pediatric Global Health and Life Satisfaction patient-reported outcome (PRO) measures. We used multiple regression to examine cross-sectional associations between the PROs and parent-reported health conditions and sociodemographic variables. We defined a meaningful difference in average scores as a PROMIS T-score difference of3.The sample included 45% 13 to 17-year-olds, 50% females, 8% Latinx, and 23% Black/African-American. Fifty-four percent had a chronic health condition. Of the 16 chronic conditions included in the study, only chronic pain (β = -3.5; 95% CI: -5.2 to -1.9) and depression (β = -6.6; 95% CI: -8.5 to -4.6) were associated with scoring3 points lower on global health. Only depression was associated with3 points lower on life satisfaction (β = -6.2; 95% CI: -8.1 to -4.3). Among those with depression, 95% also had another chronic condition.Many children with chronic conditions have similar levels of positive health as counterparts without chronic conditions. The study results suggest that negative associations between chronic conditions and positive health may be primarily attributable to presence or co-occurrence of depression.

BACKGROUND AND OBJECTIVES: Performing adequately powered clinical trials in pediatric diseases, such as SLE, is challenging. Improved recruitment strategies are needed for identifying patients. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS: Electronic health record algorithms were developed and tested to identify children with SLE both with and without lupus nephritis. We used single-center electronic health record data to develop computable phenotypes composed of diagnosis, medication, procedure, and utilization codes. These were evaluated iteratively against a manually assembled database of patients with SLE. The highest-performing phenotypes were then evaluated across institutions in PEDSnet, a national health care systems network of >6.7 million children. Reviewers blinded to case status used standardized forms to review random samples of cases (n=350) and noncases (n=350). RESULTS: Final algorithms consisted of both utilization and diagnostic criteria. For both, utilization criteria included two or more in-person visits with nephrology or rheumatology and ≥60 days follow-up. SLE diagnostic criteria included absence of neonatal lupus, one or more hydroxychloroquine exposures, and either three or more qualifying diagnosis codes separated by ≥30 days or one or more diagnosis codes and one or more kidney biopsy procedure codes. Sensitivity was 100% (95% confidence interval [95% CI], 99 to 100), specificity was 92% (95% CI, 88 to 94), positive predictive value was 91% (95% CI, 87 to 94), and negative predictive value was 100% (95% CI, 99 to 100). Lupus nephritis diagnostic criteria included either three or more qualifying lupus nephritis diagnosis codes (or SLE codes on the same day as glomerular/kidney codes) separated by ≥30 days or one or more SLE diagnosis codes and one or more kidney biopsy procedure codes. Sensitivity was 90% (95% CI, 85 to 94), specificity was 93% (95% CI, 89 to 97), positive predictive value was 94% (95% CI, 89 to 97), and negative predictive value was 90% (95% CI, 84 to 94). Algorithms identified 1508 children with SLE at PEDSnet institutions (537 with lupus nephritis), 809 of whom were seen in the past 12 months. CONCLUSIONS: Electronic health record–based algorithms for SLE and lupus nephritis demonstrated excellent classification accuracy across PEDSnet institutions.

Background The HERO registry was established to support research on the impact of the COVID-19 pandemic on US healthcare workers. Objective Describe the COVID-19 pandemic experiences of and effects on individuals participating in the HERO registry. Design Cross-sectional, self-administered registry enrollment survey conducted from April 10 to July 31, 2020. Setting Participants worked in hospitals (74.4%), outpatient clinics (7.4%), and other settings (18.2%) located throughout the nation. Participants A total of 14,600 healthcare workers. Main Measures COVID-19 exposure, viral and antibody testing, diagnosis of COVID-19, job burnout, and physical and emotional distress. Key Results Mean age was 42.0 years, 76.4% were female, 78.9% were White, 33.2% were nurses, 18.4% were physicians, and 30.3% worked in settings at high risk for COVID-19 exposure (e.g., ICUs, EDs, COVID-19 units). Overall, 43.7% reported a COVID-19 exposure and 91.3% were exposed at work. Just 3.8% in both high- and low-risk settings experienced COVID-19 illness. In regression analyses controlling for demographics, professional role, and work setting, the risk of COVID-19 illness was higher for Black/African-Americans (aOR 2.32, 99% CI 1.45, 3.70, p < 0.01) and Hispanic/Latinos (aOR 2.19, 99% CI 1.55, 3.08, p < 0.01) compared with Whites. Overall, 41% responded that they were experiencing job burnout. Responding about the day before they completed the survey, 53% of participants reported feeling tired a lot of the day, 51% stress, 41% trouble sleeping, 38% worry, 21% sadness, 19% physical pain, and 15% anger. On average, healthcare workers reported experiencing 2.4 of these 7 distress feelings a lot of the day. Conclusions Healthcare workers are at high risk for COVID-19 exposure, but rates of COVID-19 illness were low. The greater risk of COVID-19 infection among race/ethnicity minorities reported in the general population is also seen in healthcare workers. The HERO registry will continue to monitor changes in healthcare worker well-being during the pandemic. Trial Registration ClinicalTrials.gov identifier NCT04342806 Supplementary Information The online version contains supplementary material available at 10.1007/s11606-020-06529-z.

BACKGROUND Children belonging to the same birth cohort (i.e., born in the same year) experience shared exposure to a common obesity-related milieu during the critical early years of development-e.g., secular beliefs and feeding practices, adverse chemical exposures, food access and nutrition assistance policies-that set the stage for a shared trajectory of obesity as they mature. Fundamental cause theory suggests that inequitable distribution of recent efforts to stem the rise in child obesity may exacerbate cohort-based disparities over time. METHODS Data were from electronic health records spanning 2007-2016 linked to birth records for children ages 2-19 years. We used hierarchical age-period-cohort models to investigate cohort effects on disparities in obesity related to maternal education. We hypothesized that maternal education-based disparities in prevalence of obesity would be larger among more recent birth cohorts. RESULTS Sex-stratified models adjusted for race/ethnicity showed substantial obesity disparities by maternal education that were evident even at young ages: prevalence among children with maternal education

Cardiac complications, particularly myocarditis and pericarditis, have been associated with SARS-CoV-2 (the virus that causes COVID-19) infection (1-3) and mRNA COVID-19 vaccination (2-5). Multisystem inflammatory syndrome (MIS) is a rare but serious complication of SARS-CoV-2 infection with frequent cardiac involvement (6). Using electronic health record (EHR) data from 40 U.S. health care systems during January 1, 2021-January 31, 2022, investigators calculated incidences of cardiac outcomes (myocarditis; myocarditis or pericarditis; and myocarditis, pericarditis, or MIS) among persons aged ≥5 years who had SARS-CoV-2 infection, stratified by sex (male or female) and age group (5-11, 12-17, 18-29, and ≥30 years). Incidences of myocarditis and myocarditis or pericarditis were calculated after first, second, unspecified, or any (first, second, or unspecified) dose of mRNA COVID-19 (BNT162b2 [Pfizer-BioNTech] or mRNA-1273 [Moderna]) vaccines, stratified by sex and age group. Risk ratios (RR) were calculated to compare risk for cardiac outcomes after SARS-CoV-2 infection to that after mRNA COVID-19 vaccination. The incidence of cardiac outcomes after mRNA COVID-19 vaccination was highest for males aged 12-17 years after the second vaccine dose; however, within this demographic group, the risk for cardiac outcomes was 1.8-5.6 times as high after SARS-CoV-2 infection than after the second vaccine dose. The risk for cardiac outcomes was likewise significantly higher after SARS-CoV-2 infection than after first, second, or unspecified dose of mRNA COVID-19 vaccination for all other groups by sex and age (RR 2.2-115.2). These findings support continued use of mRNA COVID-19 vaccines among all eligible persons aged ≥5 years.

PURPOSE: This study’s aim was to use a representative sample of the US pediatric population to estimate percentiles for several PROMIS pediatric measures: Anger, Anxiety, Depressive Symptoms, Family Relationships, Fatigue, Global Health, Life Satisfaction, Meaning and Purpose, Pain Behavior, Pain Interference, Physical Activity, Physical Function Mobility, Physical Function Upper Extremity, Physical Stress Experiences, Positive Affect, Psychological Stress Experiences, Sleep Disturbance, Sleep Impairment, and Peer Relationships. METHODS: We used two separate, nationally representative samples of parents and children aged 5–17 years drawn in different years from the GfK Knowledge Panel, a dual-frame online probability panel. RESULTS: All measures that were developed using a representative sample had a median at or near the expected value of 50. For the other measures, the 50th percentile was often 10 points or more from 50. Several domains had high floors or low ceilings. No domain’s percentiles completely corresponded to the percentiles associated with a normal distribution with a mean of 50 and standard deviation of 10. CONCLUSIONS: This work allows users to interpret a child’s self-reported quality of life relative to children in the US general population. When attempting to evaluate whether a child falls above or below other children in the US, one should use the values presented in this study. In addition, we recommend that users should focus on whether a child’s score falls into one of a few broad severity groups rather than on specific percentile scores.

OBJECTIVES: Our objectives were to (1) quantify the frequency of wheezing episodes and asthma diagnosis in young children in a large pediatric primary care network and (2) assess the variability in practice-level asthma diagnosis, accounting for common asthma risk factors and comorbidities. We hypothesized that significant variability in practice-level asthma diagnosis rates would remain after adjusting for associated predictors. METHODS: We generated a retrospective longitudinal birth cohort of children who visited one of 31 pediatric primary care practices within the first 6 months of life from 1/2005-12/2016. Children were observed for up to 8 years or until the end of the observation window. We used multivariable discrete time survival models to evaluate predictors of asthma diagnosis by 3-month age intervals. We compared unadjusted and adjusted proportions of children diagnosed with asthma by practice. RESULTS: Of the 161,502 children in the cohort, 34,578 children (21%) received at least one asthma diagnosis. In multivariable modeling, male gender, minority race/ethnicity, gestational age

Objectives Evidence suggests that spatial accessibility to primary care is a contributing factor to appropriate health care utilization, with limited primary care access resulting in avoidable hospitalizations and emergency department visits which are burdensome on individuals and our healthcare system. Limited research, however, has examined the effects on children. Methods We evaluated associations of spatial accessibility to primary care on health care utilization among a sample of 16,709 children aged 0-3 years in Philadelphia who were primarily non-White and publicly insured. Log-Poisson models with generalized estimating equations were used to estimate incidence rate ratios (RR) and 95% confidence intervals (CI) while accounting for three levels of clustering (within individual, within primary care practice, within neighborhood). Results In age-adjusted models, the lowest level of spatial accessibility was associated with 7% fewer primary care visits (RR 0.93, 95% CI 0.91, 0.95), 15% more emergency department (ED) visits (RR 1.15, 95% CI 1.09, 1.22), and 18% more avoidable hospitalizations (RR 1.18, 95% CI 1.01, 1.37). After adjustment for individual- (race/ethnicity, sex, number of chronic conditions, insurance status) and neighborhood-level (racial composition and proportion of housing units with no vehicle), spatial accessibility was not significantly associated with rate of health care utilization. Conclusions Individual-level predisposing factors, such as age, race, and need, attenuate the association between accessibility to primary care and use of primary care, emergency department visits, and avoidable hospitalization. Given the possibility of modifying access to primary care unlike immutable individual factors, a focus on spatial accessibility to primary care may promote appropriate health care utilization.

PURPOSE: To assess the association between children’s sleep quality and life satisfaction; and to evaluate the underlying mechanisms of this relationship. METHODS: Three pediatric cohorts in the National Institutes of Health (NIH) Environmental influences on Child Health (ECHO) Research Program administered Patient Reported Outcome Measurement Information System (PROMIS®) parent-proxy measures to caregivers (n=1111) who reported on their 5–9-year-old children’s (n=1251) sleep quality, psychological stress, general health, and life satisfaction; extant sociodemographic data was harmonized across cohorts. Bootstrapped path modeling of individual patient data meta-analysis was used to determine whether and to what extent stress and general health mediate the relationship between children’s sleep quality and life satisfaction. RESULTS: Nonparametric bootstrapped path analyses with 1000 replications suggested children’s sleep quality was associated with lower levels of stress and better general health, which, in turn, predicted higher levels of life satisfaction. Family environmental factors (i.e., income and maternal mental health) moderated these relationships. CONCLUSION: Children who sleep well have happier lives than those with more disturbed sleep. Given the modifiable nature of children’s sleep quality, this study offers evidence to inform future interventional studies on specific mechanisms to improve children’s well-being.

BACKGROUND Privacy-protecting analytic approaches without centralized pooling of individual-level data, such as distributed regression, are particularly important for vulnerable populations, such as children, but these methods have not yet been tested in multi-center pediatric studies. METHODS Using the electronic health data from 34 healthcare institutions in the National Patient-Centered Clinical Research Network (PCORnet), we fit 12 multivariable-adjusted linear regression models to assess the associations of antibiotic use

Rationale Obesity in children increases the risk for new asthma. How age, sex, race/ethnicity, and allergy status affect the relationship between obesity and asthma is unclear. This study describes the relationship between high body mass index (BMI) and incident asthma. Methods We conducted a retrospective cohort study to compare asthma incidence among normal weight, overweight, and obese 2 to 6, 7 to 11, and 12 to 17 year olds to define the effects of sex, race/ethnicity, and allergy status. Weight status was determined at baseline and asthma incidence was defined as ≥2 asthma encounters and ≥1 asthma prescriptions. We used multivariable Poisson regression to estimate adjusted incident asthma rates and risk ratios. Results Data from 192 843 2 to 6 year olds, 157 284 7 to 11 year olds, and 157 369 12 to 17 year olds were included. The relative risks (95% confidence interval [CI]) of new asthma among obese children in 2 to 6 year olds, 7 to 11 year olds, and 12 to 17 year olds were 1.25 (1.15, 1.37), 1.49 (1.32, 1.69) and 1.40 (1.21, 1.63), respectively. Among children with underlying allergic rhinitis, obesity did not increase the risk of new asthma. In children without allergic rhinitis, the risk for obesity-related asthma was highest in 7 to 11 year olds (risk ratio = 1.50 95% CI, 1.33, 1.60). Before age 12, females had a higher risk for obesity-related asthma; but after age 12, obese males had a higher asthma risk (interaction P-value Conclusion Obesity is a major preventable risk factor for pediatric asthma that appears to vary along the pediatric age continuum and depends on sex, race/ethnicity and atopy status.

Objective To describe the development of the Patient-Reported Outcome Measurement Information System (PROMIS) Pediatric Meaning and Purpose item banks, child-report and parent-proxy editions. Methods Data were collected from two samples. The first comprised 1,895 children (8–17 years old) and 927 parents of children 5–17 years old recruited from an Internet panel, medical clinics, and schools. The second comprised a nationally representative sample of 990 children 8–17 years old and 1,292 parents of children 5–17 years old recruited from a different Internet panel. Item pool evaluation was done with Sample 1 and analyses were used to support decisions about item retention. The combined sample was used for item response theory (IRT) calibration of the item bank. Both samples were used in validation studies. Results Eleven items were deleted from the item pool because of poor psychometric performance. The final versions of the scales showed excellent reliability (>0.90). Short form scales (4 or 8 items) had a high degree of precision across over 4 SD units of the latent variable. The item bank positively correlated with extant measures of positive psychological functioning, and negatively correlated with measures of emotional distress, pessimism, and pain. Lower meaning and purpose scores were associated with adolescence and presence of a special healthcare need. Conclusion The PROMIS Pediatric Meaning and Purpose item banks and their short forms are ready for use in clinical research and practice. They are measures of children’s eudaimonic well-being and indicative of children’s hopefulness, optimism, goal-directedness, and feelings that life is worth living.

OBJECTIVES: To identify pediatric patient-reported outcomes (PROs) that are associated with chronic conditions and to evaluate the effects of chronic disease activity on PROs. STUDY DESIGN: Participants 8–24 years-old and their parents were enrolled into 14 studies that evaluated PROMIS® PROs across 10 chronic conditions--asthma, atopic dermatitis, cancer, cancer survivors, chronic kidney disease, Crohn’s disease, juvenile idiopathic arthritis, lupus, sickle cell disease, and type 1 diabetes mellitus. PRO scores were contrasted with the United States general population of children using nationally representative percentiles. PRO-specific coefficients of variation were computed to illustrate the degree of variation in scores within versus between conditions. Condition-specific measures of disease severity and Cohens d effect sizes were used to examine PRO scores by disease activity. RESULTS: Participants included 2,975 child respondents and 2,392 parent respondents who provided data for 3,409 unique children: 52% were 5–12 years-old, 52% female, 25% African-American/Black, and 14% Hispanic. Across all 10 chronic conditions, children reported more anxiety, fatigue, pain, and mobility restrictions than the general pediatric population. Variation in PRO scores within chronic disease cohorts was equivalent to variation within the general population, exceeding between-cohort variation by factors of 1.9 (mobility) to 5.7 (anxiety). Disease activity was consistently associated with poorer self-reported health, and these effects were weakest for peer relationships. CONCLUSIONS: Chronic conditions are associated with symptoms and functional status in children and adolescents across 10 different disorders. These findings highlight the need to complement conventional clinical evaluations with those obtained directly from patients themselves using PROs.

BACKGROUND AND OBJECTIVES: Metabolic monitoring is important for children taking antipsychotic medication, given the risk for increased BMI, impaired glucose metabolism, and hyperlipidemia. The purpose was to examine the influence of provider specialty on the receipt of metabolic monitoring. Specifically, differences in the receipt of recommended care when a child receives outpatient care from a primary care provider (PCP), a mental health provider with prescribing privileges, or both was examined. METHODS: Medicaid enrollment and health care and pharmacy claims data from 2 states were used in the analyses. Providers were assigned to specialties by using a crosswalk of the National Provider Identifier numbers to specialty type. A total of 41 078 children were included. RESULTS: For both states, 61% of children saw ≥1 provider type and had adjusted odds ratios for receiving metabolic monitoring that were significantly higher than those of children seeing PCPs only. For example, children seeing a PCP and a mental health provider with prescribing privileges during the year had adjusted odds of receiving metabolic monitoring that were 42% higher than those seeing a PCP alone (P < .001). CONCLUSIONS: Shared care arrangements significantly increased the chances that metabolic monitoring would be done. For states, health plans, and clinicians to develop meaningful quality improvement strategies, identifying the multiple providers caring for the children and potentially responsible for ordering tests consistent with evidence-based care is essential. Provider attribution in the context of shared care arrangements plays a critical role in driving quality improvement efforts.

Pollen from trees, grasses, and weeds can trigger asthma exacerbation in sensitized individuals. However, there are gaps in knowledge about the effects, such as the relative risks from different plant taxa and threshold levels of effect. We aimed to describe the local association between pollen and asthma exacerbation among children in the City of Philadelphia, and to evaluate whether effects are modified by children’s characteristics and clinical factors (e.g., child’s age, race/ethnicity, comorbidities). We conducted a time-stratified case-crossover study of pediatric (age

Background Rates of sleep disturbances vary widely across pediatric cancer studies, partly due to differences in measurement tools. Patient-reported outcomes measurement information system (PROMIS) offers a rigorously developed, well-validated pair of pediatric sleep health instruments needed to advance sleep research and clinical practice in pediatric cancer. The current study evaluated the clinical validity of PROMIS pediatric sleep scales (sleep disturbances [SD] and sleep-related impairment [SRI]) among children in active cancer treatment. Procedure Caregiver-patient dyads were enrolled during cancer treatment in 2-12 months after diagnosis: 45 children (ages 8-17 years) and 102 caregivers of children (ages 5-17 years) completed PROMIS SD and SRI 8-item short form self-report or caregiver-proxy scales, and caregivers reported the prior week's cancer treatments and blood counts. Results Both scales demonstrated strong internal consistency reliability across reporters. SD and SRI were higher than the PROMIS general population calibration sample for caregivers and patients. Oncology caregivers reported lower SD and SRI than sleep clinic caregivers, but oncology patients were similar to sleep clinic patients. Convergent validity was evidenced through moderate correlations between scales by reporter and both scales being significantly higher in patients taking medications for sleep. There were no significant differences in SD or SRI by diagnostic group, receiving radiation, or having low blood counts. Conclusion The PROMIS SD and SRI short forms are promising measures for pediatric oncology, demonstrating strong internal consistency reliability and multiple indications of clinical validity. Although groups did not differ based on treatment variables, results suggest the need for universal screening for sleep problems during pediatric cancer treatment.

Objective We developed and evaluated a privacy-preserving One-shot Distributed Algorithm to fit a multicenter Cox proportional hazards model (ODAC) without sharing patient-level information across sites. Materials and Methods Using patient-level data from a single site combined with only aggregated information from other sites, we constructed a surrogate likelihood function, approximating the Cox partial likelihood function obtained using patient-level data from all sites. By maximizing the surrogate likelihood function, each site obtained a local estimate of the model parameter, and the ODAC estimator was constructed as a weighted average of all the local estimates. We evaluated the performance of ODAC with (1) a simulation study and (2) a real-world use case study using 4 datasets from the Observational Health Data Sciences and Informatics network. Results On the one hand, our simulation study showed that ODAC provided estimates nearly the same as the estimator obtained by analyzing, in a single dataset, the combined patient-level data from all sites (ie, the pooled estimator). The relative bias was Conclusions ODAC is a privacy-preserving and noniterative method for implementing time-to-event analyses across multiple sites. It provides estimates on par with the pooled estimator and substantially outperforms the meta-analysis estimator when the event is uncommon, making it extremely suitable for studying rare events and diseases in a distributed manner.

Objective The purpose of this study was to develop self-report and parent-proxy measures of children’s physical activity for clinical research and practice and to demonstrate a valid and reliable instrument of children’s lived experience of physical activity as reported by the children themselves or their parent proxies. Methods This study involved qualitative development of item pools followed by 2 cross-sectional validity and reliability studies. The National Institutes of Health Patient Reported Outcome Measurement Information System (PROMIS) instrument development standards were applied to create child self-report and parent-proxy physical activity instruments from previously developed, content-valid pools of physical activity items. Each item used a 7-day recall period and had 5 response options. Item bank calibration was based on national samples totaling 3033 children aged 8 to 17 years and 2336 parents of children aged 5 to 17 years. Quantitative analyses included reliability assessments, factor analyses, item response theory calibration, differential item functioning, and construct validation. Results The final item banks comprised 10 items each. The items were selected based on content and psychometric properties. The item banks appeared to be unidimensional and free from differential item functioning. They showed excellent reliability and a high degree of precision across the range of the latent variable. Child-report and parent-proxy 4- and 8-item fixed-length instruments were specified. The instruments showed moderate correlation with existing self-report measures of physical activity. Conclusion The PROMIS Pediatric Physical Activity instruments provide precise and valid measurement of children’s lived experiences of physical activity. Impact The availability of the PROMIS Pediatric Physical Activity instruments will support advances in clinical practice and research that require measurement of pediatric physical activity by self- and parent-proxy report.

OBJECTIVE: To develop and evaluate the validity of a self-report measure of sleep practices for youth 8–17 years. METHODS: Following recommended guidelines for the development of patient reported outcomes (PROs), sleep practice concepts were identified through expert (n=8) and child (n=28) concept elicitation interviews and a systematic literature review. Items were developed based on these concepts and tested in cognitive interviews with children (n=32). Psychometric analyses were applied to item response data collected from a diverse sample of youth 8–17 years (n=307). Construct validity was evaluated through tests of associations between sleep practices and sleep disturbance and sleep-related impairment. Finally, clinical validity of the tool was assessed by comparing scores of youth with and without a parent-identified sleep problem. RESULTS: The final Pediatric Sleep Practices Questionnaire (PSPQ) included 15 items that were used to identify 5 sleep practices: sleep timing, sleep routines and consistency, technology use before bedtime, sleep environment, and the need for parental presence to fall asleep. A confirmatory factor analysis supported the hypothesized structure (all factor loadings ≥ 0.72) and PSPQ indices were significantly associated with self-reported sleep disturbances and sleep-related impairment. Finally, children with parent-reported sleep problems had shorter sleep opportunity, later bedtimes, greater need for parental presence, poorer bedtime routines, and more technology use than children without parent-reported sleep problems. CONCLUSIONS: The PSPQ was developed using best-practice PRO development methodology. The PSPQ can be used in clinical settings and for research assessment to capture modifiable sleep practices that may promote or interfere with healthy sleep.

To understand how parents and physicians make decisions regarding antibiotics and whether a potential associated risk of obesity would alter decisions, we conducted a qualitative study of parents and physicians who care for children. Parent focus groups and physician interviews used a guide focused on experience with antibiotics and perceptions of risks and benefits, including obesity. Content analysis was used to understand how a risk of obesity would influence antibiotic decisions. Most parents (n = 59) and physicians (n = 22) reported limited discussion about any risks at the time of antibiotic prescriptions. With an acute illness, most parents prioritized symptomatic improvement and chose to start antibiotics. Physicians’ treatment preferences were varied. An obesity risk did not change most parents’ or physicians’ preferences. Given that parent-physician discussion at the time of acute illness is unlikely to change preferences, public health messaging may be a more successful approach to counter obesity and antibiotics overuse.

OBJECTIVES: The National Patient-Centered Clinical Research Network (PCORnet) supports observational and clinical research using healthcare data. The PCORnet Antibiotics and Childhood Growth Study is one of PCORnet’s inaugural observational studies. The objectives of this manuscript are to describe (1) the processes used to integrate and analyze data from children across 36 participating institutions and (2) the cohort characteristics and prevalence of antibiotic use. METHODS: We included children in the cohort if they had at least one same-day height and weight measured in each of three age periods: 1) before 12 months, 2) 12 to 30 months, and 3) after 24 months. We distributed statistical queries that each institution ran on its local version of the PCORnet Common Data Model, with aggregate data returned for analysis. We defined overweight or obesity as age-sex-specific body mass index ≥ 85(th), obesity ≥95(th) percentile, and severe obesity ≥120% of the 95(th) percentile. RESULTS: 681,739 children met the cohort inclusion criteria and were racially/ethnically diverse (24.9% black, 17.5% Hispanic). Before 24 months, 55.2% of children received at least one antibiotic prescription; 21.3% received a single antibiotic prescription, 14.3% received four or more, and 33.3% received a broad spectrum antibiotic. Overweight and obesity prevalence was 27.6% at 4 to

Introduction It has been posited that policies to promote child health and prevent obesity should target neighborhood environments but evidence on the impact of neighborhoods on child weight is conflicting and longitudinal studies (which have benefits for causal inference) are scarce. Methods We used electronic health records (2007–2016) from an urban, pediatric integrated delivery system and linked children (N = 51,873, ages 6–19 years, 77% African American) to neighborhood-level data to investigate how changes in neighborhood environments relate to changes in body mass index (BMI). Measures of neighborhood environment were resources for healthy foods and physical activity (‘resources’), greenness, violent crime rate, perceived safety and social cohesion. Fixed effects models estimated associations between changes in neighborhood environment exposures and changes in BMI z-score and whether effects differed by sex, baseline age, neighborhood socioeconomic status and population density. Results Approximately 22% of the cohort was obese (BMI z-score ≥ 95th percentile). In adjusted models, increases in neighborhood greenness and perceived safety were associated with decreases in BMI z-score (mean change in BMI z-score for 1-SD increase for both: -0.012; 95% CI= (−0.018, −0.007)). Increases in neighborhood safety had a stronger effect in children ages 6–10 years than in older children. Increases in social cohesion were associated with increases in BMI z-score (mean change: 0.005 95% CI = (0.003, 0.008)) especially in boys. Increases in food and physical activity resources were not associated with changes in BMI. Conclusions This study suggests that increasing neighborhood greenness and safety are potential approaches to reduce children's BMI.

Key Points Question Is early antibiotic exposure associated with altered body mass index (BMI) trajectory milestone patterns in childhood? Findings This cohort study of 183 444 children identified small associations with age and magnitude of BMI at peak in infancy and rebound in early childhood after antibiotic exposure before 48 months of age. Meaning The findings of this study suggest these small associations with BMI trajectory milestones after early-life antibiotic exposure should not affect the individual decision to prescribe antibiotics., Importance Past studies have showed associations between antibiotic exposure and child weight outcomes. Few, however, have documented alterations to body mass index (BMI) (calculated as weight in kilograms divided by height in meters squared) trajectory milestone patterns during childhood after early-life antibiotic exposure. Objective To examine the association of antibiotic use during the first 48 months of life with BMI trajectory milestones during childhood in a large cohort of children. Design, Setting, and Participants This retrospective cohort study used electronic health record data from 26 institutions participating in the National Patient-Centered Clinical Research Network from January 1, 2009, to December 31, 2016. Participant inclusion required at least 1 valid set of same-day height and weight measurements at each of the following age periods: 0 to 5, 6 to 11, 12 to 23, 24 to 59, and 60 to 131 months (183 444 children). Data were analyzed from June 1, 2019, to June 30, 2020. Exposures Antibiotic use at 0 to 5, 6 to 11, 12 to 23, 24 to 35, and 36 to 47 months of age. Main Outcomes and Measures Age and magnitude of BMI peak and BMI rebound. Results Of 183 444 children in the study (mean age, 3.3 years [range, 0-10.9 years]; 95 228 [51.9%] were boys; 80 043 [43.6%] were White individuals), 78.1% received any antibiotic, 51.0% had at least 1 episode of broad-spectrum antibiotic exposure, and 65.0% had at least 1 episode of narrow-spectrum antibiotic exposure at any time before 48 months of age. Exposure to any antibiotics at 0 to 5 months of age (vs no exposure) was associated with later age (β coefficient, 0.05 months [95% CI, 0.02-0.08 months]) and higher BMI (β coefficient, 0.09 [95% CI, 0.07-0.11]) at peak. Exposure to any antibiotics at 0 to 47 months of age (vs no exposure) was associated with an earlier age (−0.60 months [95% CI, −0.81 to −0.39 months]) and higher BMI at rebound (β coefficient, 0.02 [95% CI, 0.01-0.03]). These associations were strongest for children with at least 4 episodes of antibiotic exposure. Effect estimates for associations with age at BMI rebound were larger for those exposed to antibiotics at 24 to 35 months of age (β coefficient, −0.63 [95% CI, −0.83 to −0.43] months) or 36 to 47 (β coefficient, −0.52 [95% CI, −0.72 to −0.31] months) than for those exposed at 0 to 5 months of age (β coefficient, 0.26 [95% CI, 0.01-0.51] months) or 6 to 11 (β coefficient, 0.00 [95% CI, −0.20 to 0.20] months). Conclusions and Relevance In this cohort study, antibiotic exposure was associated with statistically significant, but small, differences in BMI trajectory milestones in infancy and early childhood. The small risk of an altered BMI trajectory milestone pattern associated with early-life antibiotic exposure is unlikely to be a key factor during prescription decisions for children., This cohort study uses data from the National Patient-Centered Clinical Research Network (PCORnet) Antibiotics Childhood Growth Study to examine the association of antibiotic use during the first 4 years of life and body mass index trajectory milestones during childhood in a large cohort of children.

Objective This study compares seven machine learning models developed to predict childhood obesity from age > 2 to ≤ 7 years using Electronic Healthcare Record (EHR) data up to age 2 years. Materials and methods EHR data from of 860,510 patients with 11,194,579 healthcare encounters were obtained from the Children’s Hospital of Philadelphia. After applying stringent quality control to remove implausible growth values and including only individuals with all recommended wellness visits by age 7 years, 27,203 (50.78 % male) patients remained for model development. Seven machine learning models were developed to predict obesity incidence as defined by the Centers for Disease Control and Prevention (age/sex adjusted BMI>95th percentile). Model performance was evaluated by multiple standard classifier metrics and the differences among seven models were compared using the Cochran's Q test and post-hoc pairwise testing. Results XGBoost yielded 0.81 (0.001) AUC, which outperformed all other models. It also achieved statistically significant better performance than all other models on standard classifier metrics (sensitivity fixed at 80 %): precision 30.90 % (0.22 %), F1-socre 44.60 % (0.26 %), accuracy 66.14 % (0.41 %), and specificity 63.27 % (0.41 %). Discussion and conclusion Early childhood obesity prediction models were developed from the largest cohort reported to date. Relative to prior research, our models generalize to include males and females in a single model and extend the time frame for obesity incidence prediction to 7 years of age. The presented machine learning model development workflow can be adapted to various EHR-based studies and may be valuable for developing other clinical prediction models.

Introduction Clinicians require tools to rapidly identify individuals with significant childhood adversity as part of routine primary care. The goal of this study was to shorten the 11-item Behavioral Risk Factor Surveillance System Adverse Childhood Experiences (ACEs) measure and evaluate the feasibility and validity of this shortened measure as a screener to identify adults who have experienced significant childhood adversity. Methods Statistical analysis was conducted in 2015. ACE item responses obtained from 2011–2012 Behavioral Risk Factor Surveillance System data were combined to form a sample of 71,413 adults aged ≥18 years. The 11-item Behavioral Risk Factor Surveillance System ACE measure was subsequently reduced to a two-item screener by maintaining the two dimensions of abuse and household stressors and selecting the most prevalent item within each dimension. Results The screener included household alcohol and childhood emotional abuse items. Overall, 42% of respondents and at least 75% of the individuals with four or more ACEs endorsed one or both of these experiences. Using the 11-item ACE measure as the standard, a cut off of one or more ACEs yielded a sensitivity of 99%, but specificity was low (66%). Specificity improved to 94% when using a cut off of two ACEs, but sensitivity diminished (70%). There was no substantive difference between the 11-and two-item ACE measures in their strength of association with an array of health outcomes. Conclusions A two-item ACE screener appropriate for rapid identification of adults who have experienced significant childhood adversity was developed.

Objective To examine the clinical validity of the Patient Reported Outcome Measurement Information System (PROMIS) Pediatric Sleep Disturbance (SD) and Sleep-Related Impairment (SRI) short forms. Methods Youth (8–17 years) from clinical populations with known SDs (sleep clinic n = 126, autism n = 276, asthma n = 82, asthma + eczema n = 68) and the general population (n = 902) completed the PROMIS Pediatric SD and SRI 8-item short forms, along with established measures of sleep (Children’s Report of Sleep Patterns, Sleep Habits Survey), PROMIS Pediatric Fatigue, and parent-reported clinical indicators (does child have sleep problem, use melatonin, use prescription sleep medication). Results Confirmatory factor analyses demonstrated factorial invariance for all clinical groups. Significant differences between the general population and clinical groups were found for SD and SRI (medium to large effect sizes). Convergent validity was demonstrated through separate hierarchical regression models that showed significant associations between parent-reported clinical indicators and SD and SRI, above and beyond clinical group, as well as moderate to strong correlations between the PROMIS sleep measures and both established measures of sleep and fatigue. Conclusions The PROMIS Pediatric SD and SRI short forms provide clinicians and researchers a brief, accurate, and valid way to measure patient-reported sleep outcomes in pediatric populations.

Background: Pancreatic ductal adenocarcinoma (PDAC) is associated with high symptom burden. However, treatment decisions currently depend heavily on physician interpretation of clinical parameters and may not consider patients’ health preferences. The NIH Patient-Reported Outcomes Measurement Information System (PROMIS) initiative standardized a set of patient-reported outcomes for use in chronic diseases. This study identifies preference rankings among patients with PDAC and physicians for PROMIS domains and compares the priorities of patients and their providers. Methods: We condensed the 96 NIH PROMIS adult domains into 31 domains and created a Maximum Difference Scaling questionnaire. Domain preference scores were generated from the responses of patients with PDAC and physicians, which were compared using Maximum Difference Scaling software across demographic and clinical variables. Results: Participants included 135 patients with PDAC (53% male; median age, 68 years) and 54 physicians (76% male; median years of experience, 10). Patients selected physical functioning (PF) as their top priority, whereas physicians identified pain as most important. PF, ability to perform activities of daily living, and symptom management were within the top 5 domains for both patients and physicians, and varied only slightly across age, sex, and ethnicity. However, several domains were ranked significantly higher by patients than by physicians, including but not limited to PF; ability to do things for yourself, family, and friends; ability to interact with others to obtain help; and sleep quality. Physicians ranked pain, anxiety, and depression higher than patients did. Conclusions: Our findings suggest that patients with PDAC value PF and engaging in daily and social activities the most, whereas physicians prioritize symptoms such as pain. Patient-reported outcomes need to become more integrated into PDAC care and research to better identify unmet patient needs, inform treatment decisions, and develop therapies that address outcomes valued by patients.

Background Widespread implementation of electronic health records (EHR) has created new opportunities for pediatric oncology observational research. Little attention has been given to using EHR data to identify patients with pediatric hematologic malignancies. Methods This study used EHR-derived data in a pediatric clinical data research network, PEDSnet, to develop and evaluate a computable phenotype algorithm to identify pediatric patients with leukemia and lymphoma who received treatment with chemotherapy. To guide early development, multiple computable phenotype-defined cohorts were compared to one institution's tumor registry. The most promising algorithm was chosen for formal evaluation and consisted of at least two leukemia/lymphoma diagnoses (Systematized Nomenclature of Medicine codes) within a 90-day period, two chemotherapy exposures, and three hematology-oncology provider encounters. During evaluation, the computable phenotype was executed against EHR data from 2011 to 2016 at three large institutions. Classification accuracy was assessed by masked medical record review with phenotype-identified patients compared to a control group with at least three hematology-oncology encounters. Results The computable phenotype had sensitivity of 100% (confidence interval [CI] 99%, 100%), specificity of 99% (CI 99%, 100%), positive predictive value (PPV) and negative predictive value (NPV) of 100%, and C-statistic of 1 at the development institution. The computable phenotype performance was similar at the two test institutions with sensitivity of 100% (CI 99%, 100%), specificity of 99% (CI 99%, 100%), PPV of 96%, NPV of 100%, and C-statistic of 0.99. Conclusion The EHR-based computable phenotype is an accurate cohort identification tool for pediatric patients with leukemia and lymphoma who have been treated with chemotherapy and is ready for use in clinical studies.

OBJECTIVES:To investigate children’s general health and life satisfaction in the context of chronic illness.METHODS:Caregivers (n = 1113) from 3 concurrent cohort studies completed the Patient-Reported Outcomes Measurement Information System Parent-Proxy Global Health measure, which is used to assess a child’s overall physical, mental, and social health, as well as the Patient-Reported Outcomes Measurement Information System Parent-Proxy Life Satisfaction measure between March 2017 and December 2017 for 1253 children aged 5 to 9 years. We harmonized demographic factors and family environmental stressors (single parent, maternal mental health, and income) to common metrics across the cohorts. To examine associations between chronic illness and children’s general health and life satisfaction, we fit linear regression models with cohort fixed effects and accounted for the multilevel data structure of multiple children nested within the same family (ie, twins and other siblings) with generalized estimating equations.RESULTS:Children with chronic illness had worse general health than those without illness (adjusted β = −1.20; 95% confidence interval: −2.49 to 0.09). By contrast, children with chronic illness had similar levels of life satisfaction (adjusted β = −.19; 95% confidence interval: −1.25 to 0.87). Additionally, children’s psychological stress had the strongest negative association with both outcomes, even after adjusting for demographics and family environmental stressors.CONCLUSIONS:Although children with chronic illness have lower parent-reported general health, their life satisfaction appears comparable with that of peers without chronic illness. With this study, we provide evidence that chronic illnesses do not preclude children from leading happy and satisfying lives.

BACKGROUND: Developing a research agenda that is focused on the priorities of key stakeholders may expedite implementation and dissemination. Our objective was to identify the highest-priority patient-safety research topics among pediatric clinicians, health care leaders, and families. METHODS: The Children’s Hospitals Solutions for Patient Safety Network is a network of >100 children’s hospitals working together to eliminate harm due to health care. Parents and site leaders responded to an open-ended, anonymous e-mail survey used to elicit research topics. A key stakeholder panel winnowed related topics and prioritized topics using Likert scale ratings. Site leaders and parents responded to a second anonymous e-mail survey and rated the importance of each topic. Health system executive interviews were used to elicit their opinions regarding top priorities for patient-safety research. RESULTS: The elicitation survey had 107 respondents who produced 49 unique research topics. The key stakeholder panel developed a final list of 24 topics. The prioritization survey had 74 respondents. Top-priority research topics concerned high reliability, safety culture, open communication, and early detection of patient deterioration and sepsis. During 7 qualitative interviews, health system executives highlighted diagnostic error, medication safety, deterioration, and ambulatory patient safety as priority areas. CONCLUSIONS: With this study, we take a first step toward a stakeholder-driven research agenda on the basis of the assumption that stakeholders are best positioned to determine what research will be used to address the problems of most concern to them.

BackgroundThe Johns Hopkins ACG System is widely used to predict patient healthcare service use and costs. Most applications have focused on adult populations. In this study, we evaluated the use of the ACG software to predict pediatric unplanned hospital admission in a given month, based on the past year's clinical information captured by electronic health records (EHRs).Methods and findingsEHR data from a multi-state pediatric integrated delivery system were obtained for 920,051 patients with at least one physician visit during January 2009 to December 2016. Over this interval an average of 0.36% of patients each month had an unplanned hospitalization. In a 70% training sample, we used the generalized linear mixed model (GLMM) to generate regression coefficients for demographic, clinical predictors derived from the ACG system, and prior year hospitalizations. Applying these coefficients to a 30% test sample to generate risk scores, we found that the area under the receiver operator characteristic curve (AUC) was 0.82. Omitting prior hospitalizations decreased the AUC from 0.82 to 0.80, and increased under-estimation of hospitalizations at the greater risk levels. Patients in the top 5% of risk scores accounted for 43% and the top 1% of risk scores accounted for 20% of all unplanned hospitalizations.ConclusionsA predictive model based on 12-months of demographic and clinical data using the ACG system has excellent predictive performance for 30-day pediatric unplanned hospitalization. This model may be useful in population health and care management applications targeting patients likely to be hospitalized. External validation at other institutions should be done to confirm our results.

OBJECTIVES: Adult obesity is linked to asthma cases and is estimated to lead to 250 000 new cases yearly. Similar incidence and attributable risk (AR) estimates have not been developed for children. We sought to describe the relationship between overweight and obesity and incident asthma in childhood and quantify AR statistics in the United States for overweight and obesity on pediatric asthma. METHODS: The PEDSnet clinical data research network was used to conduct a retrospective cohort study (January 2009–December 2015) to compare asthma incidence among overweight and/or obese versus healthy weight 2- to 17-year-old children. Asthma incidence was defined as ≥2 encounters with a diagnosis of asthma and ≥1 asthma controller prescription. Stricter diagnostic criteria involved confirmation by spirometry. We used multivariable Poisson regression analyses to estimate incident asthma rates and risk ratios and accepted formulas for ARs. RESULTS: Data from 507 496 children and 19 581 972 encounters were included. The mean participant observation period was 4 years. The adjusted risk for incident asthma was increased among children who were overweight (relative risk [RR]: 1.17; 95% confidence interval [CI]: 1.10–1.25) and obese (RR: 1.26; 95% CI: 1.18–1.34). The adjusted risk for spirometry-confirmed asthma was increased among children with obesity (RR: 1.29; 95% CI: 1.16–1.42). An estimated 23% to 27% of new asthma cases in children with obesity is directly attributable to obesity. In the absence of overweight and obesity, 10% of all cases of asthma would be avoided. CONCLUSIONS: Obesity is a major preventable risk factor for pediatric asthma.

Importance There is limited information on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) testing and infection among pediatric patients across the United States. Objective To describe testing for SARS-CoV-2 and the epidemiology of infected patients. Design, Setting, and Participants A retrospective cohort study was conducted using electronic health record data from 135 794 patients younger than 25 years who were tested for SARS-CoV-2 from January 1 through September 8, 2020. Data were from PEDSnet, a network of 7 US pediatric health systems, comprising 6.5 million patients primarily from 11 states. Data analysis was performed from September 8 to 24, 2020. Exposure Testing for SARS-CoV-2. Main Outcomes and Measures SARS-CoV-2 infection and coronavirus disease 2019 (COVID-19) illness. Results A total of 135 794 pediatric patients (53% male; mean [SD] age, 8.8 [6.7] years; 3% Asian patients, 15% Black patients, 11% Hispanic patients, and 59% White patients; 290 per 10 000 population [range, 155-395 per 10 000 population across health systems]) were tested for SARS-CoV-2, and 5374 (4%) were infected with the virus (12 per 10 000 population [range, 7-16 per 10 000 population]). Compared with White patients, those of Black, Hispanic, and Asian race/ethnicity had lower rates of testing (Black: odds ratio [OR], 0.70 [95% CI, 0.68-0.72]; Hispanic: OR, 0.65 [95% CI, 0.63-0.67]; Asian: OR, 0.60 [95% CI, 0.57-0.63]); however, they were significantly more likely to have positive test results (Black: OR, 2.66 [95% CI, 2.43-2.90]; Hispanic: OR, 3.75 [95% CI, 3.39-4.15]; Asian: OR, 2.04 [95% CI, 1.69-2.48]). Older age (5-11 years: OR, 1.25 [95% CI, 1.13-1.38]; 12-17 years: OR, 1.92 [95% CI, 1.73-2.12]; 18-24 years: OR, 3.51 [95% CI, 3.11-3.97]), public payer (OR, 1.43 [95% CI, 1.31-1.57]), outpatient testing (OR, 2.13 [1.86-2.44]), and emergency department testing (OR, 3.16 [95% CI, 2.72-3.67]) were also associated with increased risk of infection. In univariate analyses, nonmalignant chronic disease was associated with lower likelihood of testing, and preexisting respiratory conditions were associated with lower risk of positive test results (standardized ratio [SR], 0.78 [95% CI, 0.73-0.84]). However, several other diagnosis groups were associated with a higher risk of positive test results: malignant disorders (SR, 1.54 [95% CI, 1.19-1.93]), cardiac disorders (SR, 1.18 [95% CI, 1.05-1.32]), endocrinologic disorders (SR, 1.52 [95% CI, 1.31-1.75]), gastrointestinal disorders (SR, 2.00 [95% CI, 1.04-1.38]), genetic disorders (SR, 1.19 [95% CI, 1.00-1.40]), hematologic disorders (SR, 1.26 [95% CI, 1.06-1.47]), musculoskeletal disorders (SR, 1.18 [95% CI, 1.07-1.30]), mental health disorders (SR, 1.20 [95% CI, 1.10-1.30]), and metabolic disorders (SR, 1.42 [95% CI, 1.24-1.61]). Among the 5374 patients with positive test results, 359 (7%) were hospitalized for respiratory, hypotensive, or COVID-19–specific illness. Of these, 99 (28%) required intensive care unit services, and 33 (9%) required mechanical ventilation. The case fatality rate was 0.2% (8 of 5374). The number of patients with a diagnosis of Kawasaki disease in early 2020 was 40% lower (259 vs 433 and 430) than in 2018 or 2019. Conclusions and Relevance In this large cohort study of US pediatric patients, SARS-CoV-2 infection rates were low, and clinical manifestations were typically mild. Black, Hispanic, and Asian race/ethnicity; adolescence and young adulthood; and nonrespiratory chronic medical conditions were associated with identified infection. Kawasaki disease diagnosis is not an effective proxy for multisystem inflammatory syndrome of childhood.

OBJECTIVE To evaluate the content and construct validity of the existing PROMIS Pediatric Parent-Proxy Peer Relationships Measure in 5- to 12-year-old children with autism spectrum disorder (ASD). METHOD Parents of 121 children aged 5 to 12 years who met DSM-IV criteria for ASD completed the Peer Relationships Measure using computerized adaptive testing (CAT). Parents also completed the Social Responsiveness Scale, Second Edition (SRS-2) and a demographic form. Intelligence quotient test results were extracted from clinical or research records. Five parents participated in semi-structured interviews about their child's peer relationships and the item content on the Peer Relationships Measure. RESULTS The children in the sample were primarily male (87%). The sample was racially and ethnically diverse, and parents were predominantly highly educated. The mean T-score (SD) on the Peer Relationships Measure was 36 (8), with a range from 15 to 62. For 98% of subjects, the CAT required administration of 5 items to reach a standard error of measurement of less than 4 T-score units. The Peer Relationships Measure demonstrated a large correlation with the SRS-2 (r = -0.60, p < .0001). In semi-structured interviews, parents reported that the items on the Peer Relationships Measure were relevant to the peer relationships of their child with ASD, but they reported a few challenges related to variability in their children's peer relationships over time and to somewhat limited knowledge of relationships in school. CONCLUSION The PROMIS Pediatric Parent-Proxy Peer Relationships Measure may be an efficient, precise, and valid measure of peer relationships for 5- to 12-year-old children with ASD.

ObjectivesContent elucidation for patient-reported outcomes (PROs) in paediatric cancer survivorship is understudied. We aimed to compare differences in the contents of five PRO domains that are important to paediatric cancer survivorship through semistructured interviews with paediatric cancer survivors and caregivers, and identified new concepts that were not covered in the item banks of the Patient-Reported Outcomes Measurement Information System (PROMIS).DesignSemistructured interviews to collect qualitative PRO data from survivors and caregivers.SettingA survivorship care clinic of a comprehensive cancer centre in the USA.ParticipantsThe study included 51 survivors (ResultsFor pain and meaning and purpose, ‘Hurt a lot’ and ‘Purpose in life’ were top concepts for survivors and caregivers, respectively. For fatigue and psychological stress, ‘Needed to sleep during the day’/‘Trouble doing schoolwork’ and ‘Felt worried’ were top concepts for survivors, and ‘Felt tired’ and ‘Felt distress’/‘Felt stressed’ for caregivers. Survivors reported more physically relevant contents (eg, ‘Hard to do sport/exercise’; 0.78 vs 0.23, p=0.007) for pain, fatigue and stress, whereas caregivers used more emotionally relevant concepts (eg, ‘Too tired to enjoy things I like to do’; 0.31 vs 0.05, p=0.025). Both groups reported positive thoughts for meaning and purpose (eg, ‘Have goals for myself’). One (psychological stress, meaning and purpose) to eleven (fatigue) new concepts were generated.ConclusionsImportant PRO contents in the form of meaningful concepts raised by survivors and caregivers were different and new concepts emerged. PRO measures are warranted to include survivorship-specific items by accounting for the child’s and the caregiver’s viewpoints.

OBJECTIVES: To determine the association of antibiotic use with weight outcomes in a large cohort of children. METHODS: Health care data were available from 2009 to 2016 for 35 institutions participating in the National Patient-Centered Clinical Research Network. Participant inclusion required same-day height and weight measurements at 0 to RESULTS: Among 1 792 849 children with a same-day height and weight measurement at CONCLUSIONS: Antibiotic use at

Objective: To develop the Patient Reported Outcome Measurement Information System (PROMIS) Pediatric Sleep Health item pool and evaluate its content validity. Participants: Participants included 8 ...

The purpose of this study was to assess whether there is an association between oral thrush or other Candida-related conditions in infancy and early childhood caries (ECC) diagnosed by pediatricians.We conducted a retrospective cohort study using electronic health records from six national children's hospitals that participate in the PEDSnet research network. There were 1,012,668 children with a visit at ages one to 12 months and another visit at ages 13 to 71 months. The independent variables were diagnosis of thrush or Candida-related conditions in the first year of life, while the dependent variable was diagnosis of ECC between 13 to 71 months old.Oral thrush detection was strongly associated with ECC, particularly between 13 and 36 months (rate ratio between 2.7 [95 percent confidence interval (95% CI) equals 2.5 to 2.9; P.001] and 3.0 [95% CI, equals 2.8 to 3.4; P.001]). A similar trend was observed with other Candida-related conditions.Oral thrush may be a risk factor for early childhood caries.

Study objectives To develop and evaluate the measurement properties of child-report and parent-proxy versions of the Patient-Reported Outcomes Measurement Information System (PROMIS) Pediatric Sleep Disturbance and Sleep-Related Impairment item banks. Methods A national sample of 1104 children (8-17 years old) and 1477 parents of children 5-17 years old was recruited from an internet panel to evaluate the psychometric properties of 43 sleep health items. A convenience sample of children and parents recruited from a pediatric sleep clinic was obtained to provide evidence of the measures' validity; polysomnography data were collected from a subgroup of these children. Results Factor analyses suggested two dimensions: sleep disturbance and daytime sleep-related impairment. The final item banks included 15 items for Sleep Disturbance and 13 for Sleep-Related Impairment. Items were calibrated using the graded response model from item-response theory. Of the 28 items, 16 are included in the parallel PROMIS adult sleep health measures. Reliability of the measures exceeded 0.90. Validity was supported by correlations with existing measures of pediatric sleep health and higher sleep disturbance and sleep-related impairment scores for children with sleep problems and those with chronic and neurodevelopmental disorders. The sleep health measures were not correlated with results from polysomnography. Conclusions The PROMIS Pediatric Sleep Disturbance and Sleep-Related Impairment item banks provide subjective assessments of child's difficulty falling and staying asleep as well as daytime sleepiness and its impact on functioning. They may prove useful in the future for clinical research and practice. Future research should evaluate their responsiveness to clinical change in diverse patient populations.

The Pediatric Ulcerative Colitis Activity Index (PUCAI) is a noninvasive disease activity index developed as a clinical trial endpoint. More recently, practice guidelines have recommended the use of PUCAI in routine clinical care. We therefore sought to evaluate the feasibility, validity, and responsiveness of PUCAI in a large, diverse collection of pediatric gastroenterology practices.We extracted data from the 2 most recent encounters for patients with ulcerative colitis in the ImproveCareNow registry. Feasibility was determined by the percentage of patients for whom all PUCAI components were recorded, validity by correlation of PUCAI scores across physician global assessment (PGA) categories, and responsiveness to change by the correlation between the change in PUCAI and PGA scores between visits.A total of 2503 patients were included (49.5% boys, age 15.2 ± 4.1 years, disease duration 3.7 ± 3.2 years). All items in the PUCAI were completed for 96% of visits. PUCAI demonstrated excellent discriminatory ability between remission, mild, and moderate disease; discrimination between moderate and severe disease was less robust. There was good correlation with PGA (r = 0.76 [P 0.001] and weighted kappa κ = 0.73 [P 0.001]). The PUCAI change scores correlated well with PGA change scores (P 0.001). Test-retest reliability of the PUCAI was good (intraclass correlation coefficient 0.72 [95% confidence interval 0.70-0.75], P 0.001). Guyatt responsiveness statistic was 1.18, and the correlation of ΔPUCAI with ΔPGA was 0.69 (P 0.001).The PUCAI is feasible to use in routine clinical settings. Evidence of its validity and responsiveness supports its use as a clinical tool for monitoring disease activity for patients with ulcerative colitis.

To describe the psychometric evaluation and item response theory calibration of the PROMIS Pediatric Life Satisfaction item banks, child-report, and parent-proxy editions. A pool of 55 life satisfaction items was administered to 1992 children 8–17 years old and 964 parents of children 5–17 years old. Analyses included descriptive statistics, reliability, factor analysis, differential item functioning, and assessment of construct validity. Thirteen items were deleted because of poor psychometric performance. An 8-item short form was administered to a national sample of 996 children 8–17 years old, and 1294 parents of children 5–17 years old. The combined sample (2988 children and 2258 parents) was used in item response theory (IRT) calibration analyses. The final item banks were unidimensional, the items were locally independent, and the items were free from impactful differential item functioning. The 8-item and 4-item short form scales showed excellent reliability, convergent validity, and discriminant validity. Life satisfaction decreased with declining socio-economic status, presence of a special health care need, and increasing age for girls, but not boys. After IRT calibration, we found that 4- and 8-item short forms had a high degree of precision (reliability) across a wide range (>4 SD units) of the latent variable. The PROMIS Pediatric Life Satisfaction item banks and their short forms provide efficient, precise, and valid assessments of life satisfaction in children and youth.

Objective To provide psychometric evaluation of the PROMIS® Pediatric Psychological and Physical Stress Experiences measures. Methods Across two studies, Psychological and Physical Stress Experiences items were administered to 2,875 children aged 8-17 years and 2,212 parents of children aged 5-17 years. Analyses included descriptive statistics, reliability, factor analysis, differential item functioning (DIF), and assessment of construct validity. Items were calibrated using item response theory to estimate item parameters representative of the United States. Recommended eight- and four-item short forms were constructed for child- and parent-report versions of the Psychological and Physical Stress Experiences item banks. Results Final item banks were unidimensional and items were locally independent and free from impactful DIF. Psychological Stress banks include 19 child-report and 12 parent-proxy items. Physical Stress banks include 26 child-report and 26 parent-proxy items. All instruments have strong internal consistency and retest-reliability, and provide precise estimates of varying stress levels. The instruments' construct validity was evidenced by known-group comparisons and convergence with legacy measures. Conclusions The Patient Reported Outcome Measurement Information System (PROMIS) Pediatric Psychological and Physical Stress item banks and short forms provide efficient, precise, and valid assessments of children's stress experiences.

To describe the development of pediatric family relationships measures, with versions for child self-report (8-17 years) and parent-report for children 5-17 years old. Measures were created for integration into the Patient Reported Outcomes Measurement Information System (PROMISSemi-structured interviews with 10 experts, 24 children, and 8 parents were conducted to elicit and clarify essential elements of family relationships. A systematic literature review was conducted to identify item concepts representative of each element. The concepts were transformed into items that were iteratively revised based on cognitive interviews (n = 43 children) and item translatability review. Psychometric studies involving 2846 children and 2262 parents were conducted to further refine and validate the instruments.Qualitative procedures supported the development of content valid Family Relationships item banks. Final child- and parent-report item banks each contain 47 items. Unidimensional item banks were calibrated using IRT-modeling to estimate item parameters representative of the US population and to enable computerized adaptive test administration. Four- and eight-item short forms were constructed for standard fixed format administration. All instruments have strong internal consistency, retest-reliability, and provide precise estimates of various levels of family relationship quality. Preliminary evidence of the instruments' validity was provided by known-group comparisons and convergence with legacy measures.The PROMIS pediatric Family Relationships measures can be applied in research focused on determinants, outcomes, and the protective effects of children's subjective family relationship experiences.

OBJECTIVES: ImproveCareNow (ICN) is the largest pediatric learning health system in the nation and started as a quality improvement collaborative. To test the feasibility and validity of using ICN data for clinical research, we evaluated the effectiveness of anti-tumor necrosis factor-α (anti-TNFα) agents in the management of pediatric Crohn disease (CD). METHODS: Data were collected in 35 pediatric gastroenterology practices (April 2007 to March 2012) and analyzed as a sequence of nonrandomized trials. Patients who had moderate to severe CD were classified as initiators or non-initiators of anti-TNFα therapy. Among 4130 patients who had pediatric CD, 603 were new users and 1211 were receiving anti-TNFα therapy on entry into ICN. RESULTS: During a 26-week follow-up period, rate ratios obtained from Cox proportional hazards models, adjusting for patient and disease characteristics and concurrent medications, were 1.53 (95% confidence interval [CI], 1.20–1.96) for clinical remission and 1.74 (95% CI, 1.33–2.29) for corticosteroid-free remission. The rate ratio for corticosteroid-free remission was comparable to the estimate produced by the adult SONIC study, which was a randomized controlled trial on the efficacy of anti-TNFα therapy. The number needed to treat was 5.2 (95% CI, 3.4–11.1) for clinical remission and 5.0 (95% CI, 3.4–10.0) for corticosteroid-free remission. CONCLUSIONS: In routine pediatric gastroenterology practice settings, anti-TNFα therapy was effective at achieving clinical and corticosteroid-free remission for patients who had Crohn disease. Using data from the ICN learning health system for the purpose of observational research is feasible and produces valuable new knowledge.

Background: Children’s activity level is commonly assessed in clinical research, but rigorous assessment tools for children are scarce. Our objectives were to improve pediatric activity self-report measures using qualitative methods to develop item pools that measure these concepts. Methods: On the basis of the items generated from our conceptual framework development, we applied cognitive interviews and comprehensibility reviews to ensure children readily understood the items. Results: Our methods resulted in 129 unique items—physical activities (80 items), sedentary behaviors (23 items), and strengthening activities (26 items)—that were comprehensible to children between the ages of 8 and 18 years. Comprehensibility review resulted in the deletion of 4 items. Conclusions: The resultant item pools reflect children’s experiences and understanding of the concepts of physical activities, sedentary behaviors, and strengthening activities. The item pools will undergo

Children's physical activity (PA) levels are commonly assessed in pediatric clinical research, but rigorous self-report assessment tools for children are scarce, and computer adaptive test implementations are rare. Our objective was to improve pediatric self-report measures of activity using semistructured interviews with experts and children for conceptualization of a child-informed framework.Semistructured interviews were conducted to conceptualize PA, sedentary behaviors, and strengthening activities. We performed systematic literature reviews to identify item-level concepts used to assess these 3 domains.We developed conceptual frameworks for each domain using words and phrases identified by children as relevant.Semistructured interview methods provide valuable information of children's perspectives and the ways children recall previous activities. Conceptualized domains of PA are based on the literature and expert views, which also reflect children's experiences and understanding, providing a basis for pediatric self-report instruments.

Objectives To characterize patterns of electronic medical record (EMR) use at pediatric primary care acute visits. Design Direct observational study of 529 acute visits with 27 experienced pediatric clinician users. Measurements For each 20 s interval and at each stage of the visit according to the Davis Observation Code, we recorded whether the physician was communicating with the family only, using the computer while communicating, or using the computer without communication. Regression models assessed the impact of clinician, patient and visit characteristics on overall visit length, time spent interacting with families, and time spent using the computer while interacting. Results The mean overall visit length was 11:30 (min:sec) with 9:06 spent in the exam room. Clinicians used the EMR during 27% of exam room time and at all stages of the visit (interacting, chatting, and building rapport; history taking; formulation of the diagnosis and treatment plan; and discussing prevention) except the physical exam. Communication with the family accompanied 70% of EMR use. In regression models, computer documentation outside the exam room was associated with visits that were 11% longer (p=0.001), and female clinicians spent more time using the computer while communicating (p=0.003). Limitations The 12 study practices shared one EMR. Conclusions Among pediatric clinicians with EMR experience, conversation accompanies most EMR use. Our results suggest that efforts to improve EMR usability and clinician EMR training should focus on use in the context of doctor–patient communication. Further study of the impact of documentation inside versus outside the exam room on productivity is warranted.

Purpose The Child Health and Illness Profile (CHIP) has separate child (6–11 years) and adolescent (12–21 years) editions that measure youth’s self-assessed health, illness, and well-being. The purpose of this study was to revise the CHIP by combining the two editions to create the Healthy Pathways Child-Report Scales. Methods We modified the original CHIP domains of Comfort, Risk Avoidance, Satisfaction, and Resilience to reflect advances in child health conceptualization. Classical test and item response theory psychometric analyses were conducted using data collected from 2,095 children (49% boys, 80% White, 17% African-American, 3% Hispanic, Age: M = 10.6, SD = 1.0) in grades 4–6 at 34 schools. Results After minor revisions, 16 of the 17 scales were found to measure unidimensional self-assessed health, illness, and well-being constructs comprehensively, but with a minimal number of items. Scales were unbiased by age, gender, survey modality, and geographic location. Construct validity was demonstrated by the instrument’s capacity to differentiate among children with and without chronic illnesses and to detect expected age and gender differences. Conclusions The Healthy Pathways Child-Report Scales may be used to reliably and accurately assess unidimensional aspects of health, illness, and well-being in clinical and population-based research studies involving youth in transition from childhood to adolescence.

OBJECTIVE. Using nationally representative data, we examined biological, medical system, and sociodemographic factors that are associated with health-related quality of life as measured by a multidimensional index that accounts for a wide range of child health domains.METHODS. Children aged ≥6 years (N = 69031) were drawn from the 2003/2004 National Survey of Children's Health. A random 25% sample was used to create a 12-item index of health-related quality of life with a range of 0 to 100, based on the conceptual framework of the Child Health and Illness Profile. Bivariate and multivariable regression analyses were conducted to identify the unadjusted and independent associations of key biological, medical system, and sociodemographic variables with health-related quality of life.RESULTS. The index mean was 72.3 (SD: 14.5), median value was 73.7, and range was 11.1 to 99.9. Only 0.2% of children had a score at the ceiling. In multivariable regression analysis, the following variables were independently associated with lower health-related quality of life: biological factors (greater disease burden, severe asthma, and overweight status); medical system factors (unmet medical needs, lack of a regular health care provider, Medicaid insurance, or being uninsured previously during the year); and sociodemographic factors (older age groups, lower family education, single-mother family, having a smoker in the household, black race, and poverty).CONCLUSIONS. Health-related quality of life in the United States is poorest for children and youth in lower socioeconomic status groups, those with access barriers, adolescents compared with children, and individuals with medical conditions. A multidimensional health-related quality-of-life index is an alternative to conventional measures (eg, mortality) for national monitoring of child health.

PURPOSE This study describes referral completion from the perspectives of patients and primary care physicians and identifies predictors of adherence to the referral recommendation. METHODS We observed a cohort of 776 referred patients from the offices of 133 physicians in 81 practices and 30 states. Referring physicians and patients completed self-administered questionnaires at the time of the referral decision and 3 months later. RESULTS Physicians reported that 79.2% of patients referred had a specialist visit, and 83.0% of patients indicated they completed the referral. The most common reasons for not completing the referral were “lack of time” and patient belief that the “health problem had resolved.” The κ statistic for patient-physician agreement on referral completion was 0.34, indicating only fair concordance. Patients in Medicaid plans were less likely than others to complete the referral, and more likely to experience a health plan denial. A longer duration of the patient relationship with the primary care physician and physician/staff scheduling of the specialty appointment were both positive predictors of referral completion. CONCLUSIONS About 8 in 10 patients referred from primary care complete a specialty referral within 3 months. Findings from this study suggest that referral completion rates may be increased by assisting patients with scheduling their specialty appointments and promoting continuity of care.