<p>Pediatric primary care (PPC) arose in the early 20 century as the fusion of acute and chronic pediatric illness care with preventive elements borrowed from public and maternal and child health. Well-established and thriving by the 1930s, PPC saw major changes in childhood morbidity and mortality in the latter half of the 20 century with the recognition of the "new morbidity" of school, behavior, and social problems. At the same time, PPC experienced changes in its workforce, which became increasingly female and added nurse practitioners and physician assistants as practitioners. Independent practice, previously the dominant business model, decreased in prominence at the end of the 20 century as health systems bought up practices and other sites morphed into federally qualified health centers. In the present century, electronic health records (EHRs) have brought profound changes in PPC workflows and practitioner experience. In addition, disruptive market competition such as retail clinics and corporate telemedicine providers coupled with changes in health insurance from fee-for-service to value-based payment further challenge the care model and economics of PPC. Finally, recognition of family social circumstances as major determinants of children's health presents another challenge to the status quo. As such, although one PPC future may resemble its present state, a more innovative future is likely to include clinics and practices more oriented toward and linked to communities and directed at the social determinants of health. In addition, the rise in physical, behavioral, and social problems in practice call for a growing focus on wellness, including sleep, nutrition, and activity, that promises to reorient the PPC future in productive new directions. The half-way technology of current EHR systems will ideally be spun into electronic hubs that facilitate teamwork between PPC, specialists, and community groups. Research and practice improvement strategies including involvement in "learning health systems" will be critical to making PPC effective in an evolving society. Although threatened by 21 century forces and hard-to-anticipate change, PPC is ideally positioned to build upon its core functions to create multidisciplinary teams that reach into the community, promoting a holistic wellness for children consistent with the broadest definition of health.</p>

<p><strong>OBJECTIVES: </strong>To determine the natural history of pediatric hypertension.</p>

<p><strong>METHODS: </strong>We conducted a 72-month retrospective cohort study among 165 primary care sites. Blood pressure measurements from two consecutive 36 month periods were compared.</p>

<p><strong>RESULTS: </strong>Among 398 079 primary care pediatric patients ages 3 to 18, 89 347 had ≥3 blood pressure levels recorded during a 36-month period, and 43 825 children had ≥3 blood pressure levels for 2 consecutive 36-month periods. Among these 43 825 children, 4.3% (1881) met criteria for hypertension (3.5% [1515] stage 1, 0.8% [366] stage 2) and 4.9% (2144) met criteria for elevated blood pressure in the first 36 months. During the second 36 months, 50% (933) of hypertensive patients had no abnormal blood pressure levels, 22% (406) had elevated blood pressure levels or &lt;3 hypertensive blood pressure levels, and 29% (542) had ≥3 hypertensive blood pressure levels. Of 2144 patients with elevated blood pressure in the first 36 months, 70% (1492) had no abnormal blood pressure levels, 18% (378) had persistent elevated blood pressure levels, and 13% (274) developed hypertension in the second 36-months. Among the 7775 patients with abnormal blood pressure levels in the first 36-months, only 52% (4025) had ≥3 blood pressure levels recorded during the second 36-months.</p>

<p><strong>CONCLUSIONS: </strong>In a primary care cohort, most children initially meeting criteria for hypertension or elevated blood pressure had subsequent normal blood pressure levels or did not receive recommended follow-up measurements. These results highlight the need for more nuanced initial blood pressure assessment and systems to promote follow-up of abnormal results.</p>

<p>In 2011, the American Academy of Pediatrics (AAP) and NHLBI recommended universal cholesterol testing at age 9 to 11 years, discussing 2 rationales. The first rationale was identification of familial hypercholesterolemia, a severe disease with a prevalence of ≈ 1:300. The long-term safety and benefits of cholesteral-lowering medications for youth with severe hypercholesterolemia have been established. These known benefits increase the value of early disease identification. The second rationale was identification of less severe dyslipidemias associated with pediatric obesity that may represent a modifiable risk for cardiovascular disease. Before 2011, pediatric cholesterol testing was most common among children with known cardiovascular risks, particularly obesity. Questions remain about the role of universal testing in pediatrics, and the United States Preventive Services Task Force has not endorsed universal testing. This uncertainty may influence guideline uptake.</p>

<p>Prior reports examining cholesterol testing in pediatric cohorts predate the 2011 guideline, evaluate specific efforts to adopt the guideline, or were unable to evaluate other cardiovascular risk factors that may be associated with testing. This study asks whether, and to what extent, universal testing has been adopted since the 2011 guideline.</p>

<p><strong>INTRODUCTION: </strong>In 2011 the NHLBI and AAP concluded that both familial and obesity associated dyslipidemias increase cardiovascular risk and recommended universal cholesterol testing at ages 9 - 11. It remains unknown whether testing influences body mass index (BMI) trajectory, a key modifiable cardiovascular outcome.</p>

<p><strong>METHODS: </strong>This quasi-experimental matched cohort includes children aged 9 - 11 years completing well visits in a diverse primary care network from 2012 - 2014. Participants had baseline BMI &gt;= 85% and no prior cholesterol testing. Propensity score matching identified untested children similar to tested children on weight measures, practice site, sex, age, race, ethnicity, insurance, and well visit frequency. Change in BMI z-score was assessed over 18 months. Regression adjusted for residual confounding following matching. Data was analyzed in 2018.</p>

<p><strong>RESULTS: </strong>Matching improved balance between tested and untested children for all characteristics. The matched cohort of 1,808 children was predominantly non-Latino black (48%) or non-Latino white (33%), and Medicaid insured (39%). Baseline BMI z-score was 1.88 for tested and 1.84 for untested children. Of tested children, 25% had cholesterol levels above the 2011 guideline's "acceptable" range. Two children received cholesterol lowering medications. Adjusted analysis found no difference in change in BMI z-score between tested and untested children (0.02, 95% CI -0.01, 0.04).</p>

<p><strong>CONCLUSIONS: </strong>Individual risk assessment in the form of cholesterol testing is not associated with change in BMI trajectory among overweight and obese children. Though testing may identify familial hypercholesterolemia, results suggest testing does not change BMI trajectory, a key strategy to reduce cardiovascular risk.</p>

<p><strong>PURPOSE: </strong>Use electronic health record (EHR) data to (1) estimate the risk of arrhythmia associated with inhaled short-acting beta-2 agonists (SABA) in pediatric patients and (2) determine whether risk varied by on-label versus off-label prescribing.</p>

<p><strong>METHODS: </strong>Retrospective cohort study of 335&nbsp;041 children ≤18&nbsp;years using EHR primary care data from 2 pediatric health systems (2011-2013). A series of monthly pseudotrials were created, using propensity score methodology to balance baseline characteristics between SABA-exposed (identified by prescription) and SABA-unexposed children. Association between SABA and subsequent arrhythmia for each health system was estimated through pooled logistic regression with separate estimates for children initiating under and over 4&nbsp;years old (off-label and on-label, respectively).</p>

<p><strong>RESULTS: </strong>Eleven percent of the cohort received a SABA prescription, 57% occurred under the age of 4&nbsp;years (off-label). During the follow-up period, there were 283 first arrhythmia events, most commonly atrial tachyarrhythmias and premature ventricular/atrial contractions. In 1 health system, adjusted risk for arrhythmia was increased among exposed children (OR 1.89, 95% CI 1.31-2.73) without evidence of interaction between label status and risk. The absolute adjusted rate difference was 3.6/10&nbsp;000 person-years of SABA exposure. The association between SABA exposure and arrhythmias was less strong in the second system (OR 1.26, 95% CI 0.30-5.33).</p>

<p><strong>CONCLUSION: </strong>Using EHR data, we could estimate the risk of a rare event associated with medication use and determine difference in risk related to on-label versus off-label status. These findings support the value of EHR-based data for postmarketing drug studies in the pediatric population.</p>

<p><strong>Objective: </strong>Large electronic health record (EHR) datasets are increasingly used to facilitate research on growth, but measurement and recording errors can lead to biased results. We developed and tested an automated method for identifying implausible values in pediatric EHR growth data.</p>

<p><strong>Materials and Methods: </strong>Using deidentified data from 46 primary care sites, we developed an algorithm to identify weight and height values that should be excluded from analysis, including implausible values and values that were recorded repeatedly without remeasurement. The foundation of the algorithm is a comparison of each measurement, expressed as a standard deviation score, with a weighted moving average of a child's other measurements. We evaluated the performance of the algorithm by (1) comparing its results with the judgment of physician reviewers for a stratified random selection of 400 measurements and (2) evaluating its accuracy in a dataset with simulated errors.</p>

<p><strong>Results: </strong>Of 2 000 595 growth measurements from 280 610 patients 1 to 21 years old, 3.8% of weight and 4.5% of height values were identified as implausible or excluded for other reasons. The proportion excluded varied widely by primary care site. The automated method had a sensitivity of 97% (95% confidence interval [CI], 94-99%) and a specificity of 90% (95% CI, 85-94%) for identifying implausible values compared to physician judgment, and identified 95% (weight) and 98% (height) of simulated errors.</p>

<p><strong>Discussion and Conclusion: </strong>This automated, flexible, and validated method for preparing large datasets will facilitate the use of pediatric EHR growth datasets for research.</p>

<p><strong>BACKGROUND AND OBJECTIVES: </strong>Pediatric hypertension predisposes children to adult hypertension and early markers of cardiovascular disease. No large-scale studies have examined diagnosis and initial medication management of pediatric hypertension and prehypertension. The objective of this study was to evaluate diagnosis and initial medication management of pediatric hypertension and prehypertension in primary care.</p>

<p><strong>METHODS: </strong>Retrospective cohort study aggregating electronic health record data on &gt;1.2 million pediatric patients from 196 ambulatory clinics across 27 states. Demographic, diagnosis, blood pressure (BP), height, weight, and medication prescription data extracted. Main outcome measures include proportion of pediatric patients with ≥3 visits with abnormal BPs, documented hypertension and prehypertension diagnoses, and prescribed antihypertensive medications. Marginal standardization via logistic regression produced adjusted diagnosis rates.</p>

<p><strong>RESULTS: </strong>Three hundred ninety-eight thousand seventy-nine patients, ages 3 to 18, had ≥3 visits with BP measurements (48.9% girls, 58.6% &lt;10 years old). Of these, 3.3% met criteria for hypertension and 10.1% for prehypertension. Among practices with ≥50 eligible patients, 2813 of 12 138 patients with hypertension (23.2%; 95% confidence interval, 18.2%-28.2%) and 3990 of 38 874 prehypertensive patients (10.2%; 95% confidence interval, 8.2%-12.2%) were diagnosed. Age, weight, height, sex, and number and magnitude of abnormal BPs were associated with diagnosis rates. Of 2813 diagnosed, persistently hypertensive patients, 158 (5.6%) were prescribed antihypertensive medication within 12 months of diagnosis (angiotensin-converting enzyme inhibitors/angiotensin receptive blockers [35%], diuretics [22%], calcium channel blockers [17%], and β-blockers [10%]).</p>

<p><strong>CONCLUSIONS: </strong>Hypertension and prehypertension were infrequently diagnosed among pediatric patients. Guidelines for diagnosis and initial medication management of abnormal BP in pediatric patients are not routinely followed.</p>

<p><strong>BACKGROUND: </strong>Primary care pediatricians increasingly care for children's mental health problems, but little is known about practice-level variation in diagnosis and psychotropic medication prescribing practices.</p>

<p><strong>METHODS: </strong>This retrospective review of electronic heath records from 43 US primary care practices included children aged 4 to 18 years with ≥1 office visit from January 1, 2009, to June 30, 2014. We examined variability in diagnosis and psychotropic prescribing across practices using logistic regression with practice fixed effects and evaluated associations of the availability of colocated or community-based mental health providers or the proportion of children in foster care with diagnosis and prescribing using generalized linear mixed models.</p>

<p><strong>RESULTS: </strong>Among 294 748 children, 40 932 (15%) received a mental health diagnosis and 39 695 (14%) were prescribed psychotropic medication. Attention deficit/hyperactivity disorder was most commonly diagnosed (1%-16% per practice). The proportion of children receiving any psychotropic medication (4%-26%) and the proportion receiving ≥2 medication classes (1%-12%) varied across practices. Prescribing of specific medication classes also varied (stimulants, 3%-18%; antidepressants, 1%-12%; α-agonists, 0%-8%; second-generation antipsychotics, 0%-5%). Variability was partially explained by community availability of psychiatrists (significantly higher odds of a diagnosis or prescription when not available) but not by colocation of mental health professionals or percentage of children in foster care.</p>

<p><strong>CONCLUSIONS: </strong>The prevalence of mental health diagnosis and psychotropic medication prescribing varies substantially across practices and is only partially explained by psychiatrist availability. Research is needed to better define the causes of variable practice-level diagnosis and prescribing and implications for child mental health outcomes.</p>