Trends of Antihypertensive Prescription Among US Adults From 2010 to 2019 and Changes Following Treatment Guidelines: Analysis of Multicenter Electronic Health Records

BACKGROUND

Guidelines for the use of antihypertensives changed in 2014 and 2017. To understand the effect of these guidelines, we examined trends in antihypertensive prescriptions in the United States from 2010 to 2019 using a repeated cross-sectional design.

METHODS AND RESULTS

Using electronic health records from 15 health care institutions for adults (20-85 years old) who had ≥1 antihypertensive prescription, we assessed whether (1) prescriptions of beta blockers decreased after the 2014 Eighth Joint National Committee (JNC 8) report discouraged use for first-line treatment, (2) prescriptions for calcium channel blockers and thiazide diuretics increased among Black patients after the JNC 8 report encouraged use as first-line therapy, and (3) prescriptions for dual therapy and fixed-dose combination among patients with blood pressure ≥140/90 mm Hg increased after recommendations in the 2017 Hypertension Clinical Practice Guidelines. The study included 1 074 314 patients with 2 133 158 prescription episodes. After publication of the JNC 8 report, prescriptions for beta blockers decreased (3% lower in 2018-2019 compared to 2010-2014), and calcium channel blockers increased among Black patients (20% higher in 2015-2017 and 41% higher in 2018-2019, compared to 2010-2014), in accordance with guideline recommendations. However, contrary to guidelines, dual therapy and fixed-dose combination decreased after publication of the 2017 Hypertension Clinical Practice Guidelines (9% and 11% decrease in 2018-2019 for dual therapy and fixed-dose combination, respectively, compared to 2015-2017), and thiazide diuretics decreased among Black patients after the JNC 8 report (6% lower in 2018-2019 compared to 2010-2014).

CONCLUSIONS

Adherence to guidelines on prescribing antihypertensive medication was inconsistent, presenting an opportunity for interventions to achieve better blood pressure control in the US population.

Vaccine Effectiveness Against Long COVID in Children

OBJECTIVES

Vaccination reduces the risk of acute coronavirus disease 2019 (COVID-19) in children, but it is less clear whether it protects against long COVID. We estimated vaccine effectiveness (VE) against long COVID in children aged 5 to 17 years.

METHODS

This retrospective cohort study used data from 17 health systems in the RECOVER PCORnet electronic health record program for visits after vaccine availability. We examined both probable (symptom-based) and diagnosed long COVID after vaccination.

RESULTS

The vaccination rate was 67% in the cohort of 1 037 936 children. The incidence of probable long COVID was 4.5% among patients with COVID-19, whereas diagnosed long COVID was 0.8%. Adjusted vaccine effectiveness within 12 months was 35.4% (95 CI 24.5-44.7) against probable long COVID and 41.7% (15.0-60.0) against diagnosed long COVID. VE was higher for adolescents (50.3% [36.6-61.0]) than children aged 5 to 11 (23.8% [4.9-39.0]). VE was higher at 6 months (61.4% [51.0-69.6]) but decreased to 10.6% (-26.8% to 37.0%) at 18-months.

CONCLUSIONS

This large retrospective study shows moderate protective effect of severe acute respiratory coronavirus 2 vaccination against long COVID. The effect is stronger in adolescents, who have higher risk of long COVID, and wanes over time. Understanding VE mechanism against long COVID requires more study, including electronic health record sources and prospective data.

Real-World Effectiveness of BNT162b2 Against Infection and Severe Diseases in Children and Adolescents

BACKGROUND

The efficacy of the BNT162b2 vaccine in pediatrics was assessed by randomized trials before the Omicron variant's emergence. The long-term durability of vaccine protection in this population during the Omicron period remains limited.

OBJECTIVE

To assess the effectiveness of BNT162b2 in preventing infection and severe diseases with various strains of the SARS-CoV-2 virus in previously uninfected children and adolescents.

DESIGN

Comparative effectiveness research accounting for underreported vaccination in 3 study cohorts: adolescents (12 to 20 years) during the Delta phase and children (5 to 11 years) and adolescents (12 to 20 years) during the Omicron phase.

SETTING

A national collaboration of pediatric health systems (PEDSnet).

PARTICIPANTS

77 392 adolescents (45 007 vaccinated) during the Delta phase and 111 539 children (50 398 vaccinated) and 56 080 adolescents (21 180 vaccinated) during the Omicron phase.

INTERVENTION

First dose of the BNT162b2 vaccine versus no receipt of COVID-19 vaccine.

MEASUREMENTS

Outcomes of interest include documented infection, COVID-19 illness severity, admission to an intensive care unit (ICU), and cardiac complications. The effectiveness was reported as (1-relative risk)*100, with confounders balanced via propensity score stratification.

RESULTS

During the Delta period, the estimated effectiveness of the BNT162b2 vaccine was 98.4% (95% CI, 98.1% to 98.7%) against documented infection among adolescents, with no statistically significant waning after receipt of the first dose. An analysis of cardiac complications did not suggest a statistically significant difference between vaccinated and unvaccinated groups. During the Omicron period, the effectiveness against documented infection among children was estimated to be 74.3% (CI, 72.2% to 76.2%). Higher levels of effectiveness were seen against moderate or severe COVID-19 (75.5% [CI, 69.0% to 81.0%]) and ICU admission with COVID-19 (84.9% [CI, 64.8% to 93.5%]). Among adolescents, the effectiveness against documented Omicron infection was 85.5% (CI, 83.8% to 87.1%), with 84.8% (CI, 77.3% to 89.9%) against moderate or severe COVID-19, and 91.5% (CI, 69.5% to 97.6%) against ICU admission with COVID-19. The effectiveness of the BNT162b2 vaccine against the Omicron variant declined 4 months after the first dose and then stabilized. The analysis showed a lower risk for cardiac complications in the vaccinated group during the Omicron variant period.

LIMITATION

Observational study design and potentially undocumented infection.

CONCLUSION

This study suggests that BNT162b2 was effective for various COVID-19-related outcomes in children and adolescents during the Delta and Omicron periods, and there is some evidence of waning effectiveness over time.

PRIMARY FUNDING SOURCE

National Institutes of Health.

Development and validation of a federated learning framework for detection of subphenotypes of multisystem inflammatory syndrome in children

Background

Multisystem inflammatory syndrome in children (MIS-C) is a severe post-acute sequela of SARS-CoV-2 infection. The highly diverse clinical features of MIS-C necessities characterizing its features by subphenotypes for improved recognition and treatment. However, jointly identifying subphenotypes in multi-site settings can be challenging. We propose a distributed multi-site latent class analysis (dMLCA) approach to jointly learn MIS-C subphenotypes using data across multiple institutions.

Methods

We used data from the electronic health records (EHR) systems across nine U.S. children's hospitals. Among the 3,549,894 patients, we extracted 864 patients < 21 years of age who had received a diagnosis of MIS-C during an inpatient stay or up to one day before admission. Using MIS-C conditions, laboratory results, and procedure information as input features for the patients, we applied our dMLCA algorithm and identified three MIS-C subphenotypes. As validation, we characterized and compared more granular features across subphenotypes. To evaluate the specificity of the identified subphenotypes, we further compared them with the general subphenotypes identified in the COVID-19 infected patients.

Findings

Subphenotype 1 (46.1%) represents patients with a mild manifestation of MIS-C not requiring intensive care, with minimal cardiac involvement. Subphenotype 2 (25.3%) is associated with a high risk of shock, cardiac and renal involvement, and an intermediate risk of respiratory symptoms. Subphenotype 3 (28.6%) represents patients requiring intensive care, with a high risk of shock and cardiac involvement, accompanied by a high risk of >4 organ system being impacted. Importantly, for hospital-specific clinical decision-making, our algorithm also revealed a substantial heterogeneity in relative proportions of these three subtypes across hospitals. Properly accounting for such heterogeneity can lead to accurate characterization of the subphenotypes at the patient-level.

Interpretation

Our identified three MIS-C subphenotypes have profound implications for personalized treatment strategies, potentially influencing clinical outcomes. Further, the proposed algorithm facilitates federated subphenotyping while accounting for the heterogeneity across hospitals.

Spectrum of severity of multisystem inflammatory syndrome in children: an EHR-based cohort study from the RECOVER program

Multi-system inflammatory syndrome in children (MIS-C) is a severe post-acute sequela of SARS-CoV-2 infection in children, and there is a critical need to unfold its highly heterogeneous disease patterns. Our objective was to characterize the illness spectrum of MIS-C for improved recognition and management. We conducted a retrospective cohort study using data from March 1, 2020-September 30, 2022, in 8 pediatric medical centers from PEDSnet. We included 1139 children hospitalized with MIS-C and used their demographics, symptoms, conditions, laboratory values, and medications for analyses. We applied heterogeneity-adaptive latent class analyses and identified three latent classes. We further characterized the sociodemographic and clinical characteristics of the latent classes and evaluated their temporal patterns. Class 1 (47.9%) represented children with the most severe presentation, with more admission to the ICU, higher inflammatory markers, hypotension/shock/dehydration, cardiac involvement, acute kidney injury and respiratory involvement. Class 2 (23.3%) represented a moderate presentation, with 4-6 organ systems involved, and some overlapping features with acute COVID-19. Class 3 (28.8%) represented a mild presentation. Our results indicated that MIS-C has a spectrum of clinical severity ranging from mild to severe and the proportion of severe or critical MIS-C decreased over time.

Venous Access: National Guideline and Registry Development (VANGUARD): Advancing Patient-Centered Venous Access Care Through the Development of a National Coordinated Registry Network

There are over 8 million central venous access devices inserted each year, many in patients with chronic conditions who rely on central access for life-preserving therapies. Central venous access device-related complications can be life-threatening and add tens of billions of dollars to health care costs, while their incidence is most likely grossly mis- or underreported by medical institutions. In this communication, we review the challenges that impair retention, exchange, and analysis of data necessary for a meaningful understanding of critical events and outcomes in this clinical domain. The difficulty is not only with data extraction and harmonization from electronic health records, national surveillance systems, or other health information repositories where data might be stored. The problem is that reliable and appropriate data are not recorded, or falsely recorded, at least in part because policy, payment, penalties, proprietary concerns, and workflow burdens discourage completeness and accuracy. We provide a roadmap for the development of health care information systems and infrastructure that address these challenges, framed within the context of research studies that build a framework of standardized terminology, decision support, data capture, and information exchange necessary for the task. This roadmap is embedded in a broader Coordinated Registry Network Learning Community, and facilitated by the Medical Device Epidemiology Network, a Public-Private Partnership sponsored by the US Food and Drug Administration, with the scope of advancing methods, national and international infrastructure, and partnerships needed for the evaluation of medical devices throughout their total life cycle.

Real-world Effectiveness of BNT162b2 Against Infection and Severe Diseases in Children and Adolescents

Background

The efficacy of the BNT162b2 vaccine in pediatrics was assessed by randomized trials before the Omicron variant's emergence. The long-term durability of vaccine protection in this population during the Omicron period remains limited.

Objective

To assess the effectiveness of BNT162b2 in preventing infection and severe diseases with various strains of the SARS-CoV-2 virus in previously uninfected children and adolescents.

Design

Comparative effectiveness research accounting for underreported vaccination in three study cohorts: adolescents (12 to 20 years) during the Delta phase, children (5 to 11 years) and adolescents (12 to 20 years) during the Omicron phase.

Setting

A national collaboration of pediatric health systems (PEDSnet).

Participants

77,392 adolescents (45,007 vaccinated) in the Delta phase, 111,539 children (50,398 vaccinated) and 56,080 adolescents (21,180 vaccinated) in the Omicron period.

Exposures

First dose of the BNT162b2 vaccine vs. no receipt of COVID-19 vaccine.

Measurements

Outcomes of interest include documented infection, COVID-19 illness severity, admission to an intensive care unit (ICU), and cardiac complications. The effectiveness was reported as (1-relative risk)*100% with confounders balanced via propensity score stratification.

Results

During the Delta period, the estimated effectiveness of BNT162b2 vaccine was 98.4% (95% CI, 98.1 to 98.7) against documented infection among adolescents, with no significant waning after receipt of the first dose. An analysis of cardiac complications did not find an increased risk after vaccination. During the Omicron period, the effectiveness against documented infection among children was estimated to be 74.3% (95% CI, 72.2 to 76.2). Higher levels of effectiveness were observed against moderate or severe COVID-19 (75.5%, 95% CI, 69.0 to 81.0) and ICU admission with COVID-19 (84.9%, 95% CI, 64.8 to 93.5). Among adolescents, the effectiveness against documented Omicron infection was 85.5% (95% CI, 83.8 to 87.1), with 84.8% (95% CI, 77.3 to 89.9) against moderate or severe COVID-19, and 91.5% (95% CI, 69.5 to 97.6)) against ICU admission with COVID-19. The effectiveness of the BNT162b2 vaccine against the Omicron variant declined after 4 months following the first dose and then stabilized. The analysis revealed a lower risk of cardiac complications in the vaccinated group during the Omicron variant period.

Limitations

Observational study design and potentially undocumented infection.

Conclusions

Our study suggests that BNT162b2 was effective for various COVID-19-related outcomes in children and adolescents during the Delta and Omicron periods, and there is some evidence of waning effectiveness over time.

Primary Funding Source

National Institutes of Health.

Risk of post-acute sequelae of SARS-CoV-2 infection associated with pre-coronavirus disease obstructive sleep apnea diagnoses: an electronic health record-based analysis from the RECOVER initiative

STUDY OBJECTIVES

Obstructive sleep apnea (OSA) has been associated with more severe acute coronavirus disease-2019 (COVID-19) outcomes. We assessed OSA as a potential risk factor for Post-Acute Sequelae of SARS-CoV-2 (PASC).

METHODS

We assessed the impact of preexisting OSA on the risk for probable PASC in adults and children using electronic health record data from multiple research networks. Three research networks within the REsearching COVID to Enhance Recovery initiative (PCORnet Adult, PCORnet Pediatric, and the National COVID Cohort Collaborative [N3C]) employed a harmonized analytic approach to examine the risk of probable PASC in COVID-19-positive patients with and without a diagnosis of OSA prior to pandemic onset. Unadjusted odds ratios (ORs) were calculated as well as ORs adjusted for age group, sex, race/ethnicity, hospitalization status, obesity, and preexisting comorbidities.

RESULTS

Across networks, the unadjusted OR for probable PASC associated with a preexisting OSA diagnosis in adults and children ranged from 1.41 to 3.93. Adjusted analyses found an attenuated association that remained significant among adults only. Multiple sensitivity analyses with expanded inclusion criteria and covariates yielded results consistent with the primary analysis.

CONCLUSIONS

Adults with preexisting OSA were found to have significantly elevated odds of probable PASC. This finding was consistent across data sources, approaches for identifying COVID-19-positive patients, and definitions of PASC. Patients with OSA may be at elevated risk for PASC after SARS-CoV-2 infection and should be monitored for post-acute sequelae.

A machine learning-based phenotype for long COVID in children: An EHR-based study from the RECOVER program

As clinical understanding of pediatric Post-Acute Sequelae of SARS CoV-2 (PASC) develops, and hence the clinical definition evolves, it is desirable to have a method to reliably identify patients who are likely to have post-acute sequelae of SARS CoV-2 (PASC) in health systems data. In this study, we developed and validated a machine learning algorithm to classify which patients have PASC (distinguishing between Multisystem Inflammatory Syndrome in Children (MIS-C) and non-MIS-C variants) from a cohort of patients with positive SARS- CoV-2 test results in pediatric health systems within the PEDSnet EHR network. Patient features included in the model were selected from conditions, procedures, performance of diagnostic testing, and medications using a tree-based scan statistic approach. We used an XGboost model, with hyperparameters selected through cross-validated grid search, and model performance was assessed using 5-fold cross-validation. Model predictions and feature importance were evaluated using Shapley Additive exPlanation (SHAP) values. The model provides a tool for identifying patients with PASC and an approach to characterizing PASC using diagnosis, medication, laboratory, and procedure features in health systems data. Using appropriate threshold settings, the model can be used to identify PASC patients in health systems data at higher precision for inclusion in studies or at higher recall in screening for clinical trials, especially in settings where PASC diagnosis codes are used less frequently or less reliably. Analysis of how specific features contribute to the classification process may assist in gaining a better understanding of features that are associated with PASC diagnoses.

Can Multisystem Inflammatory Syndrome in Children Be Managed in the Outpatient Setting? An EHR-Based Cohort Study From the RECOVER Program

Using electronic health record data combined with primary chart review, we identified seven children across nine participant pediatric medical centers with a diagnosis of Multisystem Inflammatory Syndrome in Children (MIS-C) managed exclusively as outpatients. These findings should raise awareness of mild presentations of MIS-C and the option of outpatient management.

Understanding pediatric long COVID using a tree-based scan statistic approach: an EHR-based cohort study from the RECOVER Program

Objectives

Post-acute sequalae of SARS-CoV-2 infection (PASC) is not well defined in pediatrics given its heterogeneity of presentation and severity in this population. The aim of this study is to use novel methods that rely on data mining approaches rather than clinical experience to detect conditions and symptoms associated with pediatric PASC.

Materials and Methods

We used a propensity-matched cohort design comparing children identified using the new PASC ICD10CM diagnosis code (U09.9) (N = 1309) to children with (N = 6545) and without (N = 6545) SARS-CoV-2 infection. We used a tree-based scan statistic to identify potential condition clusters co-occurring more frequently in cases than controls.

Results

We found significant enrichment among children with PASC in cardiac, respiratory, neurologic, psychological, endocrine, gastrointestinal, and musculoskeletal systems, the most significant related to circulatory and respiratory such as dyspnea, difficulty breathing, and fatigue and malaise.

Discussion

Our study addresses methodological limitations of prior studies that rely on prespecified clusters of potential PASC-associated diagnoses driven by clinician experience. Future studies are needed to identify patterns of diagnoses and their associations to derive clinical phenotypes.

Conclusion

We identified multiple conditions and body systems associated with pediatric PASC. Because we rely on a data-driven approach, several new or under-reported conditions and symptoms were detected that warrant further investigation.

Leveraging serologic testing to identify children at risk for post-acute sequelae of SARS-CoV-2 infection: An EHR-based cohort study from the RECOVER program

Using an EHR-based algorithm we identified children with COVID-19 based exclusively on serologic testing from 3/2020 through 4/2022. The 2,714 serology-positive children were more likely to be inpatients (24% vs. 2%), have chronic conditions (37% vs 24%), or a MIS-C diagnosis (23% vs. <1%) than the 131,537 PCR-positive children. Identification of children who could have been asymptomatic or paucisymptomatic and not tested is critical to define the burden of PASC in children.

A machine learning-based phenotype for long COVID in children: an EHR-based study from the RECOVER program

Background

As clinical understanding of pediatric Post-Acute Sequelae of SARS CoV-2 (PASC) develops, and hence the clinical definition evolves, it is desirable to have a method to reliably identify patients who are likely to have post-acute sequelae of SARS CoV-2 (PASC) in health systems data.

Methods and Findings

In this study, we developed and validated a machine learning algorithm to classify which patients have PASC (distinguishing between Multisystem Inflammatory Syndrome in Children (MIS-C) and non-MIS-C variants) from a cohort of patients with positive SARS-CoV-2 test results in pediatric health systems within the PEDSnet EHR network. Patient features included in the model were selected from conditions, procedures, performance of diagnostic testing, and medications using a tree-based scan statistic approach. We used an XGboost model, with hyperparameters selected through cross-validated grid search, and model performance was assessed using 5-fold cross-validation. Model predictions and feature importance were evaluated using Shapley Additive exPlanation (SHAP) values.

Conclusions

The model provides a tool for identifying patients with PASC and an approach to characterizing PASC using diagnosis, medication, laboratory, and procedure features in health systems data. Using appropriate threshold settings, the model can be used to identify PASC patients in health systems data at higher precision for inclusion in studies or at higher recall in screening for clinical trials, especially in settings where PASC diagnosis codes are used less frequently or less reliably. Analysis of how specific features contribute to the classification process may assist in gaining a better understanding of features that are associated with PASC diagnoses.

Funding Source

This research was funded by the National Institutes of Health (NIH) Agreement OT2HL161847-01 as part of the Researching COVID to Enhance Recovery (RECOVER) program of research.

Disclaimer

The content is solely the responsibility of the authors and does not necessarily represent the official views of the RECOVER Program, the NIH or other funders.

Skeletal Outcomes in Children and Young Adults with Glomerular Disease

BACKGROUND

Children with glomerular disease have unique risk factors for compromised bone health. Studies addressing skeletal complications in this population are lacking.

METHODS

This retrospective cohort study utilized data from PEDSnet, a national network of pediatric health systems with standardized electronic health record data for more than 6.5 million patients from 2009 to 2021. Incidence rates (per 10,000 person-years) of fracture, slipped capital femoral epiphysis (SCFE), and avascular necrosis/osteonecrosis (AVN) in 4598 children and young adults with glomerular disease were compared with those among 553,624 general pediatric patients using Poisson regression analysis. The glomerular disease cohort was identified using a published computable phenotype. Inclusion criteria for the general pediatric cohort were two or more primary care visits 1 year or more apart between 1 and 21 years of age, one visit or more every 18 months if followed >3 years, and no chronic progressive conditions defined by the Pediatric Medical Complexity Algorithm. Fracture, SCFE, and AVN were identified using SNOMED-CT diagnosis codes; fracture required an associated x-ray or splinting/casting procedure within 48 hours.

RESULTS

We found a higher risk of fracture for the glomerular disease cohort compared with the general pediatric cohort in girls only (incidence rate ratio [IRR], 1.6; 95% CI, 1.3 to 1.9). Hip/femur and vertebral fracture risk were increased in the glomerular disease cohort: adjusted IRR was 2.2 (95% CI, 1.3 to 3.7) and 5 (95% CI, 3.2 to 7.6), respectively. For SCFE, the adjusted IRR was 3.4 (95% CI, 1.9 to 5.9). For AVN, the adjusted IRR was 56.2 (95% CI, 40.7 to 77.5).

CONCLUSIONS

Children and young adults with glomerular disease have significantly higher burden of skeletal complications than the general pediatric population.

Clinical Features and Burden of Postacute Sequelae of SARS-CoV-2 Infection in Children and Adolescents

Importance

The postacute sequelae of SARS-CoV-2 infection (PASC) has emerged as a long-term complication in adults, but current understanding of the clinical presentation of PASC in children is limited.

Objective

To identify diagnosed symptoms, diagnosed health conditions, and medications associated with PASC in children.

Design, Setting and Participants

This retrospective cohort study used electronic health records from 9 US children's hospitals for individuals younger than 21 years who underwent antigen or reverse transcriptase-polymerase chain reaction (RT-PCR) testing for SARS-CoV-2 between March 1, 2020, and October 31, 2021, and had at least 1 encounter in the 3 years before testing.

Exposures

SARS-CoV-2 positivity by viral test (antigen or RT-PCR).

Main Outcomes and Measures

Syndromic (symptoms), systemic (conditions), and medication PASC features were identified in the 28 to 179 days following the initial test date. Adjusted hazard ratios (aHRs) were obtained for 151 clinically predicted PASC features by contrasting viral test-positive groups with viral test-negative groups using proportional hazards models, adjusting for site, age, sex, testing location, race and ethnicity, and time period of cohort entrance. The incidence proportion for any syndromic, systemic, or medication PASC feature was estimated in the 2 groups to obtain a burden of PASC estimate.

Results

Among 659 286 children in the study sample, 348 091 (52.8%) were male, and the mean (SD) age was 8.1 (5.7) years. A total of 59 893 (9.1%) tested positive by viral test for SARS-CoV-2, and 599 393 (90.9%) tested negative. Most were tested in outpatient testing facility settings (322 813 [50.3%]) or office settings (162 138 [24.6%]). The most common syndromic, systemic, and medication features were loss of taste or smell (aHR, 1.96; 95% CI, 1.16-3.32), myocarditis (aHR, 3.10; 95% CI, 1.94-4.96), and cough and cold preparations (aHR, 1.52; 95% CI, 1.18-1.96), respectively. The incidence of at least 1 systemic, syndromic, or medication feature of PASC was 41.9% (95% CI, 41.4-42.4) among viral test-positive children vs 38.2% (95% CI, 38.1-38.4) among viral test-negative children, with an incidence proportion difference of 3.7% (95% CI, 3.2-4.2). A higher strength of association for PASC was identified in those cared for in the intensive care unit during the acute illness phase, children younger than 5 years, and individuals with complex chronic conditions.

Conclusions and Relevance

In this large-scale, exploratory study, the burden of pediatric PASC that presented to health systems was low. Myocarditis was the most commonly diagnosed PASC-associated condition. Acute illness severity, young age, and comorbid complex chronic disease increased the risk of PASC.

Clinical Subphenotypes of Multisystem Inflammatory Syndrome in Children: An EHR-based cohort study from the RECOVER program

Background

Multi-system inflammatory syndrome in children (MIS-C) represents one of the most severe post-acute sequelae of SARS-CoV-2 infection in children, and there is a critical need to characterize its disease patterns for improved recognition and management. Our objective was to characterize subphenotypes of MIS-C based on presentation, demographics and laboratory parameters.

Methods

We conducted a retrospective cohort study of children with MIS-C from March 1, 2020 - April 30, 2022 and cared for in 8 pediatric medical centers that participate in PEDSnet. We included demographics, symptoms, conditions, laboratory values, medications and outcomes (ICU admission, death), and grouped variables into eight categories according to organ system involvement. We used a heterogeneity-adaptive latent class analysis model to identify three clinically-relevant subphenotypes. We further characterized the sociodemographic and clinical characteristics of each subphenotype, and evaluated their temporal patterns.

Findings

We identified 1186 children hospitalized with MIS-C. The highest proportion of children (44·4%) were aged between 5-11 years, with a male predominance (61.0%), and non- Hispanic white ethnicity (40·2%). Most (67·8%) children did not have a chronic condition. Class 1 represented children with a severe clinical phenotype, with 72·5% admitted to the ICU, higher inflammatory markers, hypotension/shock/dehydration, cardiac involvement, acute kidney injury and respiratory involvement. Class 2 represented a moderate presentation, with 4-6 organ systems involved, and some overlapping features with acute COVID-19. Class 3 represented a mild presentation, with fewer organ systems involved, lower CRP, troponin values and less cardiac involvement. Class 1 initially represented 51·1% of children early in the pandemic, which decreased to 33·9% from the pre-delta period to the omicron period.

Interpretation

MIS-C has a spectrum of clinical severity, with degree of laboratory abnormalities rather than the number of organ systems involved providing more useful indicators of severity. The proportion of severe/critical MIS-C decreased over time.

Research in context

Evidence before this study: We searched PubMed and preprint articles from December 2019, to July 2022, for studies published in English that investigated the clinical subphenotypes of MIS-C using the terms "multi-system inflammatory syndrome in children" or "pediatric inflammatory multisystem syndrome" and "phenotypes". Most previous research described the symptoms, clinical characteristics and risk factors associated with MIS-C and how these differ from acute COVID-19, Kawasaki Disease and Toxic Shock Syndrome. One single-center study of 63 patients conducted in 2020 divided patients into Kawasaki and non-Kawasaki disease subphenotypes. Another CDC study evaluated 3 subclasses of MIS-C in 570 children, with one class representing the highest number of organ systems, a second class with predominant respiratory system involvement, and a third class with features overlapping with Kawasaki Disease. However, this study evaluated cases from March to July 2020, during the early phase of the pandemic when misclassification of cases as Kawasaki disease or acute COVID-19 may have occurred. Therefore, it is not known from the existing literature whether the presentation of MIS-C has changed with newer variants such as delta and omicron.Added value of this study: PEDSnet provides one of the largest MIS-C cohorts described so far, providing sufficient power for detailed analyses on MIS-C subphenotypes. Our analyses span the entire length of the pandemic, including the more recent omicron wave, and provide an update on the presentations of MIS-C and its temporal dynamics. We found that children have a spectrum of illness that can be characterized as mild (lower inflammatory markers, fewer organ systems involved), moderate (4-6 organ involvement with clinical overlap with acute COVID-19) and severe (higher inflammatory markers, critically ill, more likely to have cardiac involvement, with hypotension/shock and need for vasopressors).Implications of all the available evidence: These results provide an update to the subphenotypes of MIS-C including the more recent delta and omicron periods and aid in the understanding of the various presentations of MIS-C. These and other findings provide a useful framework for clinicians in the recognition of MIS-C, identify factors associated with children at risk for increased severity, including the importance of laboratory parameters, for risk stratification, and to facilitate early evaluation, diagnosis and treatment.

Clinical features and burden of post-acute sequelae of SARS-CoV-2 infection in children and adolescents: an exploratory EHR-based cohort study from the RECOVER program

Importance

The post-acute sequelae of SARS-CoV-2 (PASC) has emerged as a long-term complication in adults, but current understanding of the clinical presentation of PASC in children is limited.

Objective

To identify diagnosed symptoms, diagnosed health conditions and medications associated with PASC in children.

Design Setting and Participants

Retrospective cohort study using electronic health records from 9 US children's hospitals for individuals <21 years-old who underwent reverse transcriptase polymerase chain reaction (RT-PCR) testing for SARS-CoV-2 between March 1, 2020 - October 31, 2021 and had at least 1 encounter in the 3 years before testing.

Exposure

SARS-CoV-2 PCR positivity.

Main Outcomes and Measures

We identified syndromic (symptoms), systemic (conditions), and medication PASC features in the 28-179 days following the initial test date. Adjusted hazard ratios (aHRs) were obtained for 151 clinically predicted PASC features by contrasting PCR-positive with PCR-negative groups using proportional hazards models, adjusting for site, age, sex, testing location, race/ethnicity, and time-period of cohort entrance. We estimated the incidence proportion for any syndromic, systemic or medication PASC feature in the two groups to obtain a burden of PASC estimate.

Results

Among 659,286 children in the study sample, 59,893 (9.1%) tested positive by PCR for SARS-CoV-2. Most were tested in outpatient testing facility (50.3%) or office (24.6%) settings. The most common syndromic, systemic, and medication features were loss of taste or smell (aHR 1.96 [95% CI 1.16-3.32), myocarditis (aHR 3.10 [95% CI 1.94-4.96]), and cough and cold preparations (aHR 1.52 [95% CI 1.18-1.96]). The incidence of at least one systemic/syndromic/medication feature of PASC was 41.9% among PCR-positive children versus 38.2% among PCR-negative children, with an incidence proportion difference of 3.7% (95% CI 3.2-4.2%). A higher strength of association for PASC was identified in those cared for in the ICU during the acute illness phase, children less than 5 years-old, and individuals with complex chronic conditions.

Conclusions and Relevance

In this large-scale, exploratory study, the burden of pediatric PASC that presented to health systems was low. Myocarditis was the most commonly diagnosed PASC-associated condition. Acute illness severity, young age, and comorbid complex chronic disease increased the risk of PASC.

Key Points

Question: What are the incidence and clinical features of post-acute sequelae of SARS-CoV-2 infection (PASC) in children?Findings: In this retrospective cohort study of 659,286 children tested for SARS-CoV-2 by polymerase chain reaction (PCR), the symptom, condition and medication with the strongest associations with SARS-CoV-2 infection were loss of taste/smell, myocarditis, and cough and cold preparations. The incidence proportion of non-MIS-C related PASC in the PCR-positive group exceeded the PCR-negative group by 3.7% (95% CI 3.2-4.2), with increased rates associated with acute illness severity, young age, and medical complexity.Meaning: PASC in children appears to be uncommon, with features that differ from adults.

Severity of Acute COVID-19 in Children <18 Years Old March 2020 to December 2021

This national study evaluated trends in illness severity among 82 798 children with coronavirus disease 2019 from March 1, 2020, to December 30, 2021.

Comparison of Rates of Type 2 Diabetes in Adults and Children Treated With Anticonvulsant Mood Stabilizers

IMPORTANCE

Anticonvulsant mood stabilizer treatment is associated with an increased risk of weight gain, but little is known about the risk of developing type 2 diabetes (T2D).

OBJECTIVE

To evaluate the comparative safety of anticonvulsant mood stabilizers on risk of T2D in adults and children by emulating a target trial.

DESIGN, SETTING, AND PARTICIPANTS

This observational cohort study used data from IBM MarketScan (2010-2019), with a 5-year follow-up period. The nationwide sample of US commercially insured patients included children (aged 10-19 years) and adults (aged 20-65 years) who initiated anticonvulsant mood stabilizer treatment. Data were analyzed from August 2020 to May 2021.

EXPOSURES

Initiation and continuation of carbamazepine, lamotrigine, oxcarbazepine, or valproate.

MAIN OUTCOMES AND MEASURES

Onset of T2D during follow-up. Weighted pooled logistic regression was used to estimate the association of initiation and continuation of carbamazepine, lamotrigine, oxcarbazepine, or valproate with the risk of developing T2D. Inverse probability weights were used to control for confounding and loss to follow-up by measured baseline and time-varying covariates.

RESULTS

The analysis included 274 206 adults (159 428 women [58%]; mean [SD] age, 39.9 [13.2] years) and 74 005 children (38 672 girls [52%]; mean [SD] age, 15.6 [2.6] years) who initiated an anticonvulsant mood stabilizer. In adults, initiation of valproate was associated with an increased risk of developing T2D compared with initiation of lamotrigine (5-year risk difference [RD], 1.17%; 95% CI, 0.66% to 1.76%). The number needed to harm was 87 patients initiating valproate for 1 patient to develop T2D within 5 years compared with initiation of lamotrigine. Point estimates were similar when evaluating the association of treatment continuation (5-year RD, 1.99%; 95% CI, -0.64% to 5.31%). The estimated association was smaller and more variable comparing carbamazepine and oxcarbazepine to lamotrigine. In children, RDs were much smaller and more variable (5-year RD for initiation of oxcarbazepine vs lamotrigine, 0.29%; 95% CI, -0.12% to 0.69%; 5-year RD for initiation of valproate vs lamotrigine, 0.18%; 95% CI, -0.09% to 0.49%).

CONCLUSIONS AND RELEVANCE

In this cohort study, valproate was associated with the highest risk of developing T2D in adults. The comparative safety was generally similar in children, but estimates were small and variable. In the absence of randomized trials, emulating target trials within health care databases can generate the age-specific drug safety data needed to inform treatment decision-making.

Implementation science in pediatric oncology: A narrative review and future directions

Implementation science (IS) has garnered attention within oncology, and most prior IS work has focused on adult, not pediatric, oncology. This narrative review broadly characterizes IS for pediatric oncology. It includes studies through 2020 using the following search terms in PubMed, Ovid Medline, and Cochrane: "implementation science," "pediatric," "childhood," "cancer," and "oncology." Systematic review was not performed due to the limited number of heterogeneous studies. Of 216 articles initially reviewed, nine were selected as specific to IS and pediatric oncology. All nine examined oncologic supportive care, cancer prevention, or cancer control. The supportive care focus is potentially due to the presence of cooperative study groups such as the Children's Oncology Group, which efficiently drive cancer-directed therapy changes through clinical trials. Future IS within pediatric oncology should embrace this ecosystem and focus on cancer control interventions that benefit patients across multiple cancer types and patients treated outside cooperative group studies.

Prevalence of Select New Symptoms and Conditions Among Persons Aged Younger Than 20 Years and 20 Years or Older at 31 to 150 Days After Testing Positive or Negative for SARS-CoV-2

IMPORTANCE

New symptoms and conditions can develop following SARS-CoV-2 infection. Whether they occur more frequently among persons with SARS-CoV-2 infection compared with those without is unclear.

OBJECTIVE

To compare the prevalence of new diagnoses of select symptoms and conditions between 31 and 150 days after testing among persons who tested positive vs negative for SARS-CoV-2.

DESIGN, SETTING, AND PARTICIPANTS

This cohort study analyzed aggregated electronic health record data from 40 health care systems, including 338 024 persons younger than 20 years and 1 790 886 persons aged 20 years or older who were tested for SARS-CoV-2 during March to December 2020 and who had medical encounters between 31 and 150 days after testing.

MAIN OUTCOMES AND MEASURES

International Statistical Classification of Diseases, Tenth Revision, Clinical Modification codes were used to capture new symptoms and conditions that were recorded 31 to 150 days after a SARS-CoV-2 test but absent in the 18 months to 7 days prior to testing. The prevalence of new symptoms and conditions was compared between persons with positive and negative SARS-CoV-2 tests stratified by age (20 years or older and young than 20 years) and care setting (nonhospitalized, hospitalized, or hospitalized and ventilated).

RESULTS

A total of 168 701 persons aged 20 years or older and 26 665 younger than 20 years tested positive for SARS-CoV-2, and 1 622 185 persons aged 20 years or older and 311 359 younger than 20 years tested negative. Shortness of breath was more common among persons with a positive vs negative test result among hospitalized patients (≥20 years: prevalence ratio [PR], 1.89 [99% CI, 1.79-2.01]; <20 years: PR, 1.72 [99% CI, 1.17-2.51]). Shortness of breath was also more common among nonhospitalized patients aged 20 years or older with a positive vs negative test result (PR, 1.09 [99% CI, 1.05-1.13]). Among hospitalized persons aged 20 years or older, the prevalence of new fatigue (PR, 1.35 [99% CI, 1.27-1.44]) and type 2 diabetes (PR, 2.03 [99% CI, 1.87-2.19]) was higher among those with a positive vs a negative test result. Among hospitalized persons younger than 20 years, the prevalence of type 2 diabetes (PR, 2.14 [99% CI, 1.13-4.06]) was higher among those with a positive vs a negative test result; however, the prevalence difference was less than 1%.

CONCLUSIONS AND RELEVANCE

In this cohort study, among persons hospitalized after a positive SARS-CoV-2 test result, diagnoses of certain symptoms and conditions were higher than among those with a negative test result. Health care professionals should be aware of symptoms and conditions that may develop after SARS-CoV-2 infection, particularly among those hospitalized after diagnosis.

Using a Multi-Institutional Pediatric Learning Health System to Identify Systemic Lupus Erythematosus and Lupus Nephritis: Development and Validation of Computable Phenotypes

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.

Developing a systematic approach to assessing data quality in secondary use of clinical data based on intended use

INTRODUCTION

Secondary use of electronic health record (EHR) data for research requires that the data are fit for use. Data quality (DQ) frameworks have traditionally focused on structural conformance and completeness of clinical data extracted from source systems. In this paper, we propose a framework for evaluating semantic DQ that will allow researchers to evaluate fitness for use prior to analyses.

METHODS

We reviewed current DQ literature, as well as experience from recent multisite network studies, and identified gaps in the literature and current practice. Derived principles were used to construct the conceptual framework with attention to both analytic fitness and informatics practice.

RESULTS

We developed a systematic framework that guides researchers in assessing whether a data source is fit for use for their intended study or project. It combines tools for evaluating clinical context with DQ principles, as well as factoring in the characteristics of the data source, in order to develop semantic DQ checks.

CONCLUSIONS

Our framework provides a systematic process for DQ development. Further work is needed to codify practices and metadata around both structural and semantic data quality.

Improving Guideline-Congruent Care for Chemotherapy-Induced Nausea and Vomiting Prophylaxis in Pediatric Oncology Patients

PURPOSE

Chemotherapy-induced nausea and vomiting (CINV) is a very common side effect of pediatric cancer therapy. High-quality, evidence-based, pediatric-specific guidelines for prophylaxis and treatment of CINV are available. At many centers, guideline-concordant care is uncommon. We formed a multidisciplinary quality improvement team to implement guideline-concordant care for CINV prophylaxis at our center. We present the results following the first year of our interventions.

METHODS

We planned and implemented a multipronged approach in three key phases: (1) developing and publishing an acute CINV prophylaxis pathway, (2) education of providers, and (3) updating the computerized provider order entry system. We used iterative, sequential Plan-Do-Study-Act cycles and behavioral economic strategies to improve adherence to guideline-concordant CINV prophylaxis. We focused on aprepitant usage as a key area for improvement.

RESULTS

At the beginning of the study period, < 50% of patients were receiving guideline-concordant CINV prophylaxis and < 15% of eligible patients were receiving aprepitant. After 1 year, more than 60% of patients were receiving guideline-concordant care and 50% of eligible patients were receiving aprepitant.

CONCLUSION

We describe the development and implementation of a standardized pathway for prevention of acute CINV in pediatric oncology patients. With a multidisciplinary, multifaceted approach, we demonstrate significant improvements to guideline-congruent CINV prophylaxis.

Association of Early Antibiotic Exposure With Childhood Body Mass Index Trajectory Milestones

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.

Early Life Antibiotic Prescriptions and Weight Outcomes in Children 10 Years of Age

OBJECTIVE

We previously found that antibiotic use at <24 months of age was associated with slightly higher body weight at 5 years of age. In this study, we examine associations of early life antibiotic prescriptions with weight outcomes at 108 to 132 months of age ("10 years").

METHODS

We used electronic health record data from 2009 through 2016 from 10 health systems in PCORnet, a national distributed clinical research network. We examined associations of any (vs no) antibiotics at <24 months of age with body mass index z-score (BMI-z) at 10 years adjusted for confounders selected a priori. We further examined dose response (number of antibiotic episodes) and antibiotic spectrum (narrow and broad).

RESULTS

Among 56,727 included children, 57% received any antibiotics at <24 months; at 10 years, mean (standard deviation) BMI-z was 0.54 (1.14), and 36% had overweight or obesity. Any versus no antibiotic use at <24 months was associated with a slightly higher BMI-z at 10 years among children without a complex chronic condition (β 0.03; 95% confidence interval [CI] 0.01, 0.05) or with a complex chronic condition (β 0.09; 95% CI 0.03, 0.15). Any versus no antibiotic use was not associated with odds of overweight or obesity at 10 years among children without (odds ratio 1.02; 95% CI 0.97, 1.07) or with a complex chronic condition (odds ratio 1.07; 95% CI 0.96, 1.19).

CONCLUSIONS

The small and likely clinically insignificant associations in this study are consistent with our previous 5-year follow-up results, suggesting that, if this relationship is indeed causal, early increases in weight are small but maintained over time.

Assessment of 135 794 Pediatric Patients Tested for Severe Acute Respiratory Syndrome Coronavirus 2 Across the United States

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.

Standardizing Clinical Diagnoses: Evaluating Alternate Terminology Selection

In most electronic health record (EHR) systems, clinicians record diagnoses using interface terminologies, such as Intelligent Medical Objects (IMO). When extracting data from EHRs for collaborative research, local codes are often transformed to standard terminologies for consistent analyses despite the potential for loss of fidelity. EHR diagnosis codes may be standardized directly during the Extract-Transform-Load (ETL) process to the "Meaningful Use" clinical data exchange standard, SNOMED-CT, or to the International Classification of Diseases (ICD) terminologies commonly used for billing. We examined the performance of ETL standardization via the direct IMO mapping to SNOMED-CT, and via IMO mapping to ICD-9-CM or ICD-10-CM followed by UMLS mapping to SNOMED-CT. We found that for both ICD-9-CM and ICD-10-CM, only 24-27% of diagnosis codes map to the same SNOMED-CT code selected by the direct IMO-SNOMED crosswalk. We identified that differences in mapping lead to loss in the granularity and laterality of the initial diagnosis.

Privacy-protecting multivariable-adjusted distributed regression analysis for multi-center pediatric study

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 <24 months of age with body mass index z-score at 48 to <72 months of age. We ran these models using pooled individual-level data and conventional multivariable-adjusted regression (reference method), as well as using the more privacy-protecting pooled summary-level intermediate statistics and distributed regression technique. We compared the results from these two methods.

RESULTS

Pooled individual-level and distributed linear regression analyses produced virtually identical parameter estimates and standard errors. Across all 12 models, the maximum difference in any of the parameter estimates or standard errors was 4.4833 × 10^-10.

CONCLUSIONS

We demonstrated empirically the feasibility and validity of distributed linear regression analysis using only summary-level information within a large multi-center study of children. This approach could enable expanded opportunities for multi-center pediatric research, especially when sharing of granular individual-level data is challenging.

Using Electronic Health Record Data to Rapidly Identify Children with Glomerular Disease for Clinical Research

BACKGROUND

The rarity of pediatric glomerular disease makes it difficult to identify sufficient numbers of participants for clinical trials. This leaves limited data to guide improvements in care for these patients.

METHODS

The authors developed and tested an electronic health record (EHR) algorithm to identify children with glomerular disease. We used EHR data from 231 patients with glomerular disorders at a single center to develop a computerized algorithm comprising diagnosis, kidney biopsy, and transplant procedure codes. The algorithm was tested using PEDSnet, a national network of eight children's hospitals with data on >6.5 million children. Patients with three or more nephrologist encounters (n=55,560) not meeting the computable phenotype definition of glomerular disease were defined as nonglomerular cases. A reviewer blinded to case status used a standardized form to review random samples of cases (n=800) and nonglomerular cases (n=798).

RESULTS

The final algorithm consisted of two or more diagnosis codes from a qualifying list or one diagnosis code and a pretransplant biopsy. Performance characteristics among the population with three or more nephrology encounters were sensitivity, 96% (95% CI, 94% to 97%); specificity, 93% (95% CI, 91% to 94%); positive predictive value (PPV), 89% (95% CI, 86% to 91%); negative predictive value, 97% (95% CI, 96% to 98%); and area under the receiver operating characteristics curve, 94% (95% CI, 93% to 95%). Requiring that the sum of nephrotic syndrome diagnosis codes exceed that of glomerulonephritis codes identified children with nephrotic syndrome or biopsy-based minimal change nephropathy, FSGS, or membranous nephropathy, with 94% sensitivity and 92% PPV. The algorithm identified 6657 children with glomerular disease across PEDSnet, ≥50% of whom were seen within 18 months.

CONCLUSIONS

The authors developed an EHR-based algorithm and demonstrated that it had excellent classification accuracy across PEDSnet. This tool may enable faster identification of cohorts of pediatric patients with glomerular disease for observational or prospective studies.

Development and evaluation of a computable phenotype to identify pediatric patients with leukemia and lymphoma treated with chemotherapy using electronic health record data

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.

Health-related Google searches performed by parents of pediatric oncology patients

BACKGROUND

Little is known about the specific information parents of children with cancer search for online. Understanding the content of parents' searches over time could offer insight into what matters most to parents and identify knowledge gaps that could inform more comprehensive approaches to family education and support.

METHODS

We describe parents' health-related Google searches starting six months before cancer diagnosis and extending through the date of study enrollment, which was at least one month after initiating cancer treatment. Searches were obtained retrospectively and grouped into health-related and non-health-related categories. The median time to parent enrollment from date of cancer diagnosis was 264 days.

RESULTS

Parents searched for health-related topics more frequently than the general population (13% vs 5%). Health-related searches increased in the months preceding the child's cancer diagnosis and most commonly pertained to symptoms and logistics, "directions to hospital." Health-related search volume peaked about a month after cancer diagnosis when general health-related searches were present in addition to cancer-specific searches. Eighteen percent of health-related searches were cancer specific, and of these cancer-specific searches, 54% pertained to support, for example "cancer quote for son."

CONCLUSIONS

Google search content offers insight into what matters to parents of cancer patients. Understanding search content could inform more comprehensive approaches to family education and support initiatives.

Use of EHR-Based Pediatric Quality Measures: Views of Health System Leaders and Parents

Measures of health care quality are produced from a variety of data sources, but often, physicians do not believe these measures reflect the quality of provided care. The aim was to assess the value to health system leaders (HSLs) and parents of benchmarking on health care quality measures using data mined from the electronic health record (EHR). Using in-context interviews with HSLs and parents, the authors investigated what new decisions and actions benchmarking using data mined from the EHR may enable and how benchmarking information should be presented to be most informative. Results demonstrate that although parents may have little experience using data on health care quality for decision making, they affirmed its potential value. HSLs expressed the need for high-confidence, validated metrics. They also perceived barriers to achieving meaningful metrics but recognized that mining data directly from the EHR could overcome those barriers. Parents and HSLs need high-confidence health care quality data to support decision making.

Significance of CNS 2 cerebrospinal fluid status post-induction in pediatric and adolescent patients with acute lymphoblastic leukemia

BACKGROUND

At diagnosis, there are prognostic implications of low-level leukemic blasts (CNS 2) in the cerebrospinal fluid (CSF) of patients with acute lymphoblastic leukemia (ALL). However, the significance of post-induction CNS 2 results and the impact of equipment on CNS 2 prevalence have not been well studied.

PROCEDURE

A single-institution retrospective cohort study was conducted to analyze the outcome of patients with ≥1 post-induction CNS 2. A subanalysis compared the proportion of CNS 2 CSF results using 2 different cytocentrifuges; the Shandon Cytospin used from 2005 to 2008 and the Wescor Cytopro used from 2010 to 2014.

RESULTS

Over 4500 post-induction CSF samples were analyzed, of which 59 were CNS 2. In covariate-adjusted analyses, post-induction CNS 2 did not significantly increase relapse risk. The proportion of CNS 2 results increased 4.3-fold in noninfants and 6.3-fold in infants using the Wescor Cytopro. Cytocentrifuge machine did not affect CNS 3 prevalence.

CONCLUSIONS

These findings support our current practice of not changing management based on a post-induction CNS 2 CSF and highlight how equipment changes can significantly influence testing results. More data are needed to analyze relapse by subpopulations, such as those with repeated CNS 2 findings.

Early Antibiotic Exposure and Weight Outcomes in Young Children

: media-1vid110.1542/5839981580001PEDS-VA_2018-0290Video Abstract 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 <12, 12 to <30, and 48 to <72 months of age. We assessed the association between any antibiotic use at <24 months of age with BMI z score and overweight or obesity prevalence at 48 to <72 months (5 years) of age, with secondary assessments of antibiotic spectrum and age-period exposures. We included children with and without complex chronic conditions.

RESULTS

Among 1 792 849 children with a same-day height and weight measurement at <12 months of age, 362 550 were eligible for the cohort. One-half of children (52%) were boys, 27% were African American, 18% were Hispanic, and 58% received ≥1 antibiotic prescription at <24 months of age. At 5 years, the mean BMI z score was 0.40 (SD 1.19), and 28% of children had overweight or obesity. In adjusted models for children without a complex chronic condition at 5 years, we estimated a higher mean BMI z score by 0.04 (95% confidence interval [CI] 0.03 to 0.05) and higher odds of overweight or obesity (odds ratio 1.05; 95% CI 1.03 to 1.07) associated with obtaining any (versus no) antibiotics at <24 months.

CONCLUSIONS

Antibiotic use at <24 months of age was associated with a slightly higher body weight at 5 years of age.

Effect of Levofloxacin Prophylaxis on Bacteremia in Children With Acute Leukemia or Undergoing Hematopoietic Stem Cell Transplantation: A Randomized Clinical Trial

Importance

Bacteremia causes considerable morbidity among children with acute leukemia and those undergoing hematopoietic stem cell transplantation (HSCT). There are limited data on the effect of antibiotic prophylaxis in children.

Objective

To determine the efficacy and risks of levofloxacin prophylaxis in children receiving intensive chemotherapy for acute leukemia or undergoing HSCT.

Design, Setting, and Participants

In this multicenter, open-label, randomized trial, patients (6 months-21 years) receiving intensive chemotherapy were enrolled (September 2011-April 2016) in 2 separate groups-acute leukemia, consisting of acute myeloid leukemia or relapsed acute lymphoblastic leukemia, and HSCT recipients-at 76 centers in the United States and Canada, with follow-up completed September 2017.

Interventions

Patients with acute leukemia were randomized to receive levofloxacin prophylaxis for 2 consecutive cycles of chemotherapy (n = 100) or no prophylaxis (n = 100). Those undergoing HSCT were randomized to receive levofloxacin prophylaxis during 1 HSCT procedure (n = 210) or no prophylaxis (n = 214).

Main Outcomes and Measures

The primary outcome was the occurrence of bacteremia during 2 chemotherapy cycles (acute leukemia) or 1 transplant procedure (HSCT). Secondary outcomes included fever and neutropenia, severe infection, invasive fungal disease, Clostridium difficile-associated diarrhea, and musculoskeletal toxic effects.

Results

A total of 624 patients, 200 with acute leukemia (median [interquartile range {IQR}] age, 11 years [6-15 years]; 46% female) and 424 undergoing HSCT (median [IQR] age, 7 years [3-14]; 38% female), were enrolled. Among 195 patients with acute leukemia, the likelihood of bacteremia was significantly lower in the levofloxacin prophylaxis group than in the control group (21.9% vs 43.4%; risk difference, 21.6%; 95% CI, 8.8%-34.4%, P = .001), whereas among 418 patients undergoing HSCT, the risk of bacteremia was not significantly lower in the levofloxacin prophylaxis group (11.0% vs 17.3%; risk difference, 6.3%; 95% CI, 0.3%-13.0%; P = .06). Fever and neutropenia were less common in the levofloxacin group (71.2% vs 82.1%; risk difference, 10.8%; 95% CI, 4.2%-17.5%; P = .002). There were no significant differences in severe infection (3.6% vs 5.9%; risk difference, 2.3%; 95% CI, -1.1% to 5.6%; P = .20), invasive fungal disease (2.9% vs 2.0%; risk difference, -1.0%; 95% CI, -3.4% to 1.5%, P = .41), C difficile-associated diarrhea (2.3% vs 5.2%; risk difference, 2.9%; 95% CI, -0.1% to 5.9%; P = .07), or musculoskeletal toxic effects at 2 months (11.4% vs 16.3%; risk difference, 4.8%; 95% CI, -1.6% to 11.2%; P = .15) or at 12 months (10.1% vs 14.4%; risk difference, 4.3%; 95% CI, -3.4% to 12.0%; P = .28) between the levofloxacin and control groups.

Conclusions and Relevance

Among children with acute leukemia receiving intensive chemotherapy, receipt of levofloxacin prophylaxis compared with no prophylaxis resulted in a significant reduction in bacteremia. However, there was no significant reduction in bacteremia for levofloxacin prophylaxis among children undergoing HSCT.

A Bayesian latent class approach for EHR-based phenotyping

Phenotyping, ie, identification of patients possessing a characteristic of interest, is a fundamental task for research conducted using electronic health records. However, challenges to this task include imperfect sensitivity and specificity of clinical codes and inconsistent availability of more detailed data such as laboratory test results. Despite these challenges, most existing electronic health records-derived phenotypes are rule-based, consisting of a series of Boolean arguments informed by expert knowledge of the disease of interest and its coding. The objective of this paper is to introduce a Bayesian latent phenotyping approach that accounts for imperfect data elements and missing not at random missingness patterns that can be used when no gold-standard data are available. We conducted simulation studies to compare alternative phenotyping methods under different patterns of missingness and applied these approaches to a cohort of 68 265 children at elevated risk for type 2 diabetes mellitus (T2DM). In simulation studies, the latent class approach had similar sensitivity to a rule-based approach (95.9% vs 91.9%) while substantially improving specificity (99.7% vs 90.8%). In the PEDSnet cohort, we found that biomarkers and clinical codes were strongly associated with latent T2DM status. The latent T2DM class was also strongly predictive of missingness in biomarkers. Glucose was missing in 83.4% of patients (odds ratio for latent T2DM status = 0.52) while hemoglobin A1c was missing in 91.2% (odds ratio for latent T2DM status = 0.03 ), suggesting missing not at random missingness. The latent phenotype approach may substantially improve on rule-based phenotyping.

Predicting Causes of Data Quality Issues in a Clinical Data Research Network

Clinical data research networks (CDRNs) invest substantially in identifying and investigating data quality problems. While identification is largely automated, the investigation and resolution are carried out manually at individual institutions. In the PEDSnet CDRN, we found that only approximately 35% of the identified data quality issues are resolvable as they are caused by errors in the extract-transform-load (ETL) code. Nonetheless, with no prior knowledge of issue causes, partner institutions end up spending significant time investigating issues that represent either inherent data characteristics or false alarms. This work investigates whether the causes (ETL, Characteristic, or False alarm) can be predicted before spending time investigating issues. We trained a classifier on the metadata from 10,281 real-world data quality issues, and achieved a cause prediction F1-measure of up to 90%. While initially tested on PEDSnet, the proposed methodology is applicable to other CDRNs facing similar bottlenecks in handling data quality results.

Management of Refractory Pediatric Kaposiform Hemangioendothelioma With Sirolimus and Aspirin

Kaposiform hemangioendothelioma (KHE) is a rare vascular tumor characterized by aggressive local invasion and a syndrome of platelet trapping known as Kasabach-Merritt phenomenon that, through deposition of platelet derived growth factors, may perpetuate the growth of the tumor. Although many cases of KHE are successfully treated with local control or low-intensity chemotherapy, some cases are often refractory even to aggressive treatment. Herein, we describe a patient with a refractory, recurrent KHE despite multiple attempts at local control and intensive chemotherapy, that ultimately was successfully treated with rationally designed and low-intensity combination therapy of sirolimus and aspirin.

Retrospective Analysis of Candida-related Conditions in Infancy and Early Childhood Caries

PURPOSE

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.

METHODS

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.

RESULTS

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.

CONCLUSIONS

Oral thrush may be a risk factor for early childhood caries.

A longitudinal analysis of data quality in a large pediatric data research network

Objective

PEDSnet is a clinical data research network (CDRN) that aggregates electronic health record data from multiple children's hospitals to enable large-scale research. Assessing data quality to ensure suitability for conducting research is a key requirement in PEDSnet. This study presents a range of data quality issues identified over a period of 18 months and interprets them to evaluate the research capacity of PEDSnet.

Materials and Methods

Results were generated by a semiautomated data quality assessment workflow. Two investigators reviewed programmatic data quality issues and conducted discussions with the data partners' extract-transform-load analysts to determine the cause for each issue.

Results

The results include a longitudinal summary of 2182 data quality issues identified across 9 data submission cycles. The metadata from the most recent cycle includes annotations for 850 issues: most frequent types, including missing data (>300) and outliers (>100); most complex domains, including medications (>160) and lab measurements (>140); and primary causes, including source data characteristics (83%) and extract-transform-load errors (9%).

Discussion

The longitudinal findings demonstrate the network's evolution from identifying difficulties with aligning the data to a common data model to learning norms in clinical pediatrics and determining research capability.

Conclusion

While data quality is recognized as a critical aspect in establishing and utilizing a CDRN, the findings from data quality assessments are largely unpublished. This paper presents a real-world account of studying and interpreting data quality findings in a pediatric CDRN, and the lessons learned could be used by other CDRNs.

Relationship Between State-Level Google Online Search Volume and Cancer Incidence in the United States: Retrospective Study

Background

In the United States, cancer is common, with high morbidity and mortality; cancer incidence varies between states. Online searches reflect public awareness, which could be driven by the underlying regional cancer epidemiology.

Objective

The objective of our study was to characterize the relationship between cancer incidence and online Google search volumes in the United States for 6 common cancers. A secondary objective was to evaluate the association of search activity with cancer-related public events and celebrity news coverage.

Methods

We performed a population-based, retrospective study of state-level cancer incidence from 2004 through 2013 reported by the Centers for Disease Control and Prevention for breast, prostate, colon, lung, and uterine cancers and leukemia compared to Google Trends (GT) relative search volume (RSV), a metric designed by Google to allow interest in search topics to be compared between regions. Participants included persons in the United States who searched for cancer terms on Google. The primary measures were the correlation between annual state-level cancer incidence and RSV as determined by Spearman correlation and linear regression with RSV and year as independent variables and cancer incidence as the dependent variable. Temporal associations between search activity and events raising public awareness such as cancer awareness months and cancer-related celebrity news were described.

Results

At the state level, RSV was significantly correlated to incidence for breast (r=.18, P=.001), prostate (r=–.27, P<.001), lung (r=.33, P<.001), and uterine cancers (r=.39, P<.001) and leukemia (r=.13, P=.003) but not colon cancer (r=–.02, P=.66). After adjusting for time, state-level RSV was positively correlated to cancer incidence for all cancers: breast (P<.001, 95% CI 0.06 to 0.19), prostate (P=.38, 95% CI –0.08 to 0.22), lung (P<.001, 95% CI 0.33 to 0.46), colon (P<.001, 95% CI 0.11 to 0.17), and uterine cancers (P<.001, 95% CI 0.07 to 0.12) and leukemia (P<.001, 95% CI 0.01 to 0.03). Temporal associations in GT were noted with breast cancer awareness month but not with other cancer awareness months and celebrity events.

Conclusions

Cancer incidence is correlated with online search volume at the state level. Search patterns were temporally associated with cancer awareness months and celebrity announcements. Online searches reflect public awareness. Advancing understanding of online search patterns could augment traditional epidemiologic surveillance, provide opportunities for targeted patient engagement, and allow public information campaigns to be evaluated in ways previously unable to be measured.

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.

Quality improvement initiative to increase influenza vaccination in pediatric cancer patients

BACKGROUND

Pediatric patients with cancer face more severe complications of influenza than healthy children. Although Centers for Disease Control and Prevention guidelines recommend yearly vaccination in these patients, in our large academic center, <60% of oncology patients receiving chemotherapy were immunized at baseline. Our objective was to increase this rate through a multifaceted quality improvement initiative.

METHODS

Eligible patients were >6 months old, within 1 year of receiving chemotherapy, >100 days from stem cell transplant, and had ≥ 1 outpatient oncology visit between September 1, 2012, and March 31, 2013. Five interventions were instituted concomitantly: (1) family education: influenza/vaccine handouts were provided to families in clinic waiting rooms; (2) health informatics: daily lists of outpatients due for immunization were generated from the electronic medical record and sent automatically to triage staff and nurses; (3) outpatient clinic: patients due for vaccination were given colored wristbands during triage to alert providers; (4) inpatient: vaccine order was built into admission order set; and (5) provider education: staff education was provided at conferences on screening of patients, vaccine ordering, and documentation of refusals/contraindications.

RESULTS

The complete influenza immunization rate increased by 20.1% to 64.5%, and the proportion of patients receiving ≥ 1 dose of vaccination increased by 22.9% to 77.7%. Similar changes were noted across all cancer types, with highest rates of immunization in leukemia/lymphoma patients (86.8%) and lowest in patients after stem cell transplant (66.7%).

CONCLUSIONS

Technology, education, and multidisciplinary clinical process changes increased influenza vaccination rates. Ongoing efforts are targeting subgroups with lowest rates of immunization.

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 Children's 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.

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 Children's 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.

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 Children's 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.