L. Charles Bailey

Association of Antibiotics in Infancy With Early Childhood Obesity

IMPORTANCE Obesity in children and adults is associated with significant health burdens, making prevention a public health imperative. Infancy may be a critical period when environmental factors exert a lasting effect on the risk for obesity; identifying modifiable factors may help to reduce this risk. OBJECTIVE To assess the impact of antibiotics prescribed in infancy (ages 0-23 months) on obesity in early childhood (ages 24-59 months). DESIGN, SETTING, AND PARTICIPANTS We conducted a cohort study spanning 2001-2013 using electronic health records. Cox proportional hazard models were used to adjust for demographic, practice, and clinical covariates. The study spanned a network of primary care practices affiliated with the Childrens Hospital of Philadelphia including both teaching clinics and private practices in urban Philadelphia, Pennsylvania, and the surrounding region. All children with annual visits at ages 0 to 23 months, as well 1 or more visits at ages 24 to 59 months, were enrolled. The cohort comprised 64,580 children. EXPOSURES Treatment episodes for prescribed antibiotics were ascertained up to 23 months of age. MAIN OUTCOMES AND MEASURES Obesity outcomes were determined directly from anthropometric measurements using National Health and Nutrition Examination Survey 2000 body mass index norms. RESULTS Sixty-nine percent of children were exposed to antibiotics before age 24 months, with a mean (SD) of 2.3 (1.5) episodes per child. Cumulative exposure to antibiotics was associated with later obesity (rate ratio [RR], 1.11; 95% CI, 1.02-1.21 for ≥ 4 episodes); this effect was stronger for broad-spectrum antibiotics (RR, 1.16; 95% CI, 1.06-1.29). Early exposure to broad-spectrum antibiotics was also associated with obesity (RR, 1.11; 95% CI, 1.03-1.19 at 0-5 months of age and RR, 1.09; 95% CI, 1.04-1.14 at 6-11 months of age) but narrow-spectrum drugs were not at any age or frequency. Steroid use, male sex, urban practice, public insurance, Hispanic ethnicity, and diagnosed asthma or wheezing were also predictors of obesity; common infectious diagnoses and antireflux medications were not. CONCLUSIONS AND RELEVANCE Repeated exposure to broad-spectrum antibiotics at ages 0 to 23 months is associated with early childhood obesity. Because common childhood infections were the most frequent diagnoses co-occurring with broad-spectrum antibiotic prescription, narrowing antibiotic selection is potentially a modifiable risk factor for childhood obesity.

Establishment of an 11-year cohort of 8733 pediatric patients hospitalized at United States free-standing children's hospitals with de novo acute lymphoblastic leukemia from health care administrative data.

Background:Acute lymphoblastic leukemia (ALL) accounts for almost one quarter of pediatric cancer in the United States. Despite cooperative group therapeutic trials, there remains a paucity of large cohort data on which to conduct epidemiology and comparative effectiveness research studies. Research Design:We designed a 3-step process utilizing International Classification of Diseases-9 Clinical Modification (ICD-9) discharge diagnoses codes and chemotherapy exposure data contained in the Pediatric Health Information System administrative database to establish a cohort of children with de novo ALL. This process was validated by chart review at 1 of the pediatric centers. Results:An ALL cohort of 8733 patients was identified with a sensitivity of 88% [95% confidence interval (CI), 83%–92%] and a positive predictive value of 93% (95% CI, 89%–96%). The 30-day all cause inpatient case fatality rate using this 3-step process was 0.80% (95% CI, 0.63%–1.01%), which was significantly different than the case fatality rate of 1.40% (95% CI, 1.23%–1.60%) when ICD-9 codes alone were used. Conclusions:This is the first report of assembly and validation of a cohort of de novo ALL patients from a database representative of free-standing children’s hospitals across the United States. Our data demonstrate that the use of ICD-9 codes alone to establish cohorts will lead to substantial patient misclassification and result in biased outcome estimates. Systematic methods beyond the use of just ICD-9 codes must be used before analysis to establish accurate cohorts of patients with malignancy. A similar approach should be followed when establishing future cohorts from administrative data.

PEDSnet: a National Pediatric Learning Health System

A learning health system (LHS) integrates research done in routine care settings, structured data capture during every encounter, and quality improvement processes to rapidly implement advances in new knowledge, all with active and meaningful patient participation. While disease-specific pediatric LHSs have shown tremendous impact on improved clinical outcomes, a national digital architecture to rapidly implement LHSs across multiple pediatric conditions does not exist. PEDSnet is a clinical data research network that provides the infrastructure to support a national pediatric LHS. A consortium consisting of PEDSnet, which includes eight academic medical centers, two existing disease-specific pediatric networks, and two national data partners form the initial partners in the National Pediatric Learning Health System (NPLHS). PEDSnet is implementing a flexible dual data architecture that incorporates two widely used data models and national terminology standards to support multi-institutional data integration, cohort discovery, and advanced analytics that enable rapid learning.

Building a Common Pediatric Research Terminology for Accelerating Child Health Research

Longitudinal observational clinical data on pediatric patients in electronic format is becoming widely available. A new era of multi-institutional data networks that study pediatric diseases and outcomes across disparate health delivery models and care settings are also enabling an innovative collaborative rapid improvement paradigm called the Learning Health System. However, the potential alignment of routine clinical care, observational clinical research, pragmatic clinical trials, and health systems improvement requires a data infrastructure capable of combining information from systems and workflows that historically have been isolated from each other. Removing barriers to integrating and reusing data collected in different settings will permit new opportunities to develop a more complete picture of a patient’s care and to leverage data from related research studies. One key barrier is the lack of a common terminology that provides uniform definitions and descriptions of clinical observations and data. A well-characterized terminology ensures a common meaning and supports data reuse and integration. A common terminology allows studies to build upon previous findings and to reuse data collection tools and data management processes. We present the current state of terminology harmonization and describe a governance structure and mechanism for coordinating the development of a common pediatric research terminology that links to clinical terminologies and can be used to align existing terminologies. By reducing the barriers between clinical care and clinical research, a Learning Health System can leverage and reuse not only its own data resources but also broader extant data resources.

Multi-Institutional Sharing of Electronic Health Record Data to Assess Childhood Obesity

Objective To evaluate the validity of multi-institutional electronic health record (EHR) data sharing for surveillance and study of childhood obesity. Methods We conducted a non-concurrent cohort study of 528,340 children with outpatient visits to six pediatric academic medical centers during 2007–08, with sufficient data in the EHR for body mass index (BMI) assessment. EHR data were compared with data from the 2007–08 National Health and Nutrition Examination Survey (NHANES). Results Among children 2–17 years, BMI was evaluable for 1,398,655 visits (56%). The EHR dataset contained over 6,000 BMI measurements per month of age up to 16 years, yielding precise estimates of BMI. In the EHR dataset, 18% of children were obese versus 18% in NHANES, while 35% were obese or overweight versus 34% in NHANES. BMI for an individual was highly reliable over time (intraclass correlation coefficient 0.90 for obese children and 0.97 for all children). Only 14% of visits with measured obesity (BMI ≥95%) had a diagnosis of obesity recorded, and only 20% of children with measured obesity had the diagnosis documented during the study period. Obese children had higher primary care (4.8 versus 4.0 visits, p<0.001) and specialty care (3.7 versus 2.7 visits, p<0.001) utilization than non-obese counterparts, and higher prevalence of diverse co-morbidities. The cohort size in the EHR dataset permitted detection of associations with rare diagnoses. Data sharing did not require investment of extensive institutional resources, yet yielded high data quality. Conclusions Multi-institutional EHR data sharing is a promising, feasible, and valid approach for population health surveillance. It provides a valuable complement to more resource-intensive national surveys, particularly for iterative surveillance and quality improvement. Low rates of obesity diagnosis present a significant obstacle to surveillance and quality improvement for care of children with obesity.

Effectiveness of Anti-TNFα for Crohn Disease: Research in a Pediatric Learning Health System

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.

Addressing Electronic Clinical Information in the Construction of Quality Measures

Electronic health records (EHR) and registries play a central role in health care and provide access to detailed clinical information at the individual, institutional, and population level. Use of these data for clinical quality/performance improvement and cost management has been a focus of policy initiatives over the past decade. The Childrens Health Insurance Program Reauthorization Act of 2009 (CHIPRA)-mandated Pediatric Quality Measurement Program supports development and testing of quality measures for children on the basis of electronic clinical information, including de novo measures and respecification of existing measures designed for other data sources. Drawing on the experience of Centers of Excellence, we review both structural and pragmatic considerations in e-measurement. The presence of primary observations in EHR-derived data make it possible to measure outcomes in ways that are difficult with administrative data alone. However, relevant information may be located in narrative text, making it difficult to interpret. EHR systems are collecting more discrete data, but the structure, semantics, and adoption of data elements vary across vendors and sites. EHR systems also differ in ability to incorporate pediatric concepts such as variable dosing and growth percentiles. This variability complicates quality measurement, as do limitations in established measure formats, such as the Quality Data Model, to e-measurement. Addressing these challenges will require investment by vendors, researchers, and clinicians alike in developing better pediatric content for standard terminologies and data models, encouraging wider adoption of technical standards that support reliable quality measurement, better harmonizing data collection with clinical work flow in EHRs, and better understanding the behavior and potential of e-measures.

Feasibility and validity of the pediatric ulcerative colitis activity index in routine clinical practice.

Objectives: 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. Methods: 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. Results: 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 &kgr; = 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 &Dgr;PUCAI with &Dgr;PGA was 0.69 (P < 0.001). Conclusions: 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.

Atypical Chronic Myeloid Leukemia in Two Pediatric Patients.

Atypical chronic myeloid leukemia, BCR‐ABL1‐negative, (aCML) is a rare myeloid neoplasm. Recent adult data suggest the leukemic cells in a subset of patients are dependent on JAK/STAT signaling and harbor CSF3R‐activating mutations. We hypothesized that, similar to adult patients, the presence of CSF3R‐activating mutations would be clinically relevant in pediatric myeloid neoplasms as patients would be sensitive to the JAK inhibitor, ruxolitinib. We report two cases of morphologically similar pediatric aCML, BCR‐ABL1‐negative based on WHO 2008 criteria. One patient had CSF3R‐activating mutation (T618I) and demonstrated a robust response to ruxolitinib, which was used to bridge to a successful stem cell transplant. The other patient did not have a CSF3R‐activating mutation and succumbed to refractory disease <6 months from diagnosis. This report documents CSF3R‐T618I in pediatric aCML and demonstrates the efficacy of ruxolitinib in a pediatric malignancy. As the third documented case successfully treating aCML with ruxolitinib, this case highlights the importance of prompt CSF3R sequencing analysis for myeloproliferative and myelodysplastic/myeloproliferative neoplasms. Pediatr Blood Cancer

Using Medicaid and CHIP Claims Data to Support Pediatric Quality Measurement: Lessons From 3 Centers of Excellence in Measure Development

OBJECTIVE We sought to explore the claims data-related issues relevant to quality measure development for Medicaid and the Childrens Health Insurance Program (CHIP), illustrating the challenges encountered and solutions developed around 3 distinct performance measure topics: care coordination for children with complex needs, quality of care for high-prevalence conditions, and hospital readmissions. METHODS Each of 3 centers of excellence presents an example that illustrates the challenges of using claims data for quality measurement. RESULTS Our Centers of Excellence in pediatric quality measurement used innovative methods to develop algorithms that use Medicaid claims data to identify children with complex needs; overcome some shortcomings of existing data for measuring quality of care for common conditions such as otitis media; and identify readmissions after hospitalizations for lower respiratory infections. CONCLUSIONS Our experience constructing quality measure specifications using claims data suggests that it will be challenging to measure key quality of care constructs for Medicaid-insured children at a national level in a timely and consistent way. Without better data to underpin pediatric quality measurement, Medicaid and CHIP will have difficulty using some existing measures for accountability, value-based purchasing, and quality improvement both across states and within states.