Although the number of randomized controlled trials (RCTs) published each year involving adult populations is steadily rising, the annual number of RCTs published involving pediatric populations has not changed since 2005. Barriers to the broader utilization of RCTs in pediatrics include a lower prevalence of disease, less available funding, and more complicated regulatory requirements. Although child health researchers have been successful in overcoming these barriers for isolated diseases such as pediatric cancer, common pediatric diseases are underrepresented in RCTs relative to their burden. This article proposes a strategy called High-Efficiency RandOmIzed Controlled (HEROIC) trials to increase RCTs focused on common diseases among hospitalized children. HEROIC trials are multicenter RCTs that pursue the rapid, low-cost accumulation of study participants with minimal burden for individual sites. Five key strategies distinguish HEROIC trials: (1) dispersed low-volume recruitment, in which a large number of sites (50-150 hospitals) enroll a small number of participants per site (2-10 participants per site), (2) incentivizing site leads with authorship, training, education credits, and modest financial support, (3) a focus on pragmatic questions that examine simple, widely used interventions, (4) the use of a single institutional review board, integrated consent, and other efficient solutions to regulatory requirements, and (5) scaling the HEROIC trial strategy to accomplish multiple trials simultaneously. HEROIC trials can boost RCT feasibility and volume to answer fundamental clinical questions and improve care for hospitalized children.

<p><strong>OBJECTIVE: </strong>To assess the performance of previously published high-intensity neurologic impairment (NI) diagnosis codes in identification of hospitalized children with clinical NI.</p>

<p><strong>METHODS: </strong>Retrospective study of 500 randomly selected discharges in 2019 from a freestanding children's hospital. All charts were reviewed for 1) NI discharge diagnosis codes and 2) documentation of clinical NI (a neurologic diagnosis and indication of functional impairment like medical technology). Test statistics of clinical NI were calculated for discharges with and without an NI diagnosis code. A sensitivity analysis varied the threshold for "substantial functional impairment." Secondary analyses evaluated misclassified discharges and a more stringent definition for NI.</p>

<p><strong>RESULTS: </strong>Diagnosis codes identified clinically documented NI with 88.1% (95% CI: 84.7, 91) specificity, and 79.4% (95% CI: 67.3, 88.5) sensitivity; NPV was 96.7% (95% CI: 94.8, 98.0), and PPV was 49% (95% CI: 42, 56.1). Including children with milder functional impairment (lower threshold) resulted in NPV of 95.7% and PPV of 77.5%. Restricting to children with more severe functional impairment (higher threshold) resulted in NPV of 98.2% and PPV of 44.1%. Misclassification was primarily due to inclusion of children without functional impairments. A more stringent NI definition including diagnosis codes for NI and feeding tubes had a specificity of 98.4% (95% CI: 96.7-99.3) and sensitivity of 28.6% (19.4-41.3).</p>

<p><strong>CONCLUSIONS: </strong>All scenarios evaluated demonstrated high NPV and low-to-moderate PPV of the diagnostic code list. To maximize clinical utility, NI diagnosis codes should be used with strategies to mitigate the risk of misclassification.</p>

<p><strong>BACKGROUND AND OBJECTIVES: </strong>Hospitals treating patients with greater diagnosis diversity may have higher fixed and overhead costs. We assessed the relationship between hospitals' diagnosis diversity and cost per hospitalization for children.</p>

<p><strong>METHODS: </strong>Retrospective analysis of 1 654 869 all-condition hospitalizations for children ages 0 to 21 years from 2816 hospitals in the Kids' Inpatient Database 2016. Mean hospital cost per hospitalization, Winsorized and log-transformed, was assessed for freestanding children's hospitals (FCHs), nonfreestanding children's hospitals (NFCHs), and nonchildren's hospitals (NCHs). Hospital diagnosis diversity index (HDDI) was calculated by using the D-measure of diversity in Shannon-Wiener entropy index from 1254 diagnosis and severity-of-illness groups distinguished with 3M Health's All Patient Refined Diagnosis Related Groups. Log-normal multivariable models were derived to regress hospital type on cost per hospitalization, adjusting for hospital-level HDDI in addition to patient-level demographic (eg, age, race and ethnicity) and clinical (eg, chronic conditions) characteristics and hospital teaching status.</p>

<p><strong>RESULTS: </strong>Admission counts were 383 789 (23.2%) in FCHs, 588 463 (35.6%) in NFCHs, and 682 617 (41.2%) in NCHs. Unadjusted mean cost per hospitalization was $10 757 (95% confidence interval [CI]: $9451 to $12 243) in FCHs, $6264 (95% CI: $5830 to $6729) in NFCHs, and $4192 (95% CI: $4121 to $4265) in NCHs. HDDI was significantly ( &lt; .001) higher in FCHs and NFCHs (median 9.2 and 6.4 times higher, respectively) than NCHs. Across all hospitals, greater HDDI was associated ( = .002) with increased cost. Adjusting for HDDI resulted in a nonsignificant ( = .1) difference in cost across hospital types.</p>

<p><strong>CONCLUSIONS: </strong>Greater diagnosis diversity was associated with increased cost per hospitalization and should be considered when assessing associated costs of inpatient care for pediatric patients.</p>

<p><strong>BACKGROUND: </strong>Children with multiple chronic conditions (CMCC) are increasingly using hospital care. We assessed how much of US pediatric inpatient care is used by CMCC and which chronic conditions are the key drivers of hospital use.</p>

<p><strong>METHODS: </strong>A retrospective analysis of all 2.3 million US acute-care hospital discharges in 2012 for children age 0 to 18 years in the Kids' Inpatient Database. The ∼4.5 million US hospitalizations for pregnancy, childbirth, and newborn and neonatal care were not assessed. We adapted the Agency for Healthcare Research and Quality's Chronic Condition Indicators to classify hospitalizations for children with no, 1, or multiple chronic conditions, and to determine which specific chronic conditions of CMCC are associated with high hospital resource use.</p>

<p><strong>RESULTS: </strong>Of all pediatric acute-care hospitalizations, 34.3% were of children with no chronic conditions, 36.5% were of those with 1 condition, and 29.3% were of CMCC. Of the $23.6 billion in total hospital costs, 19.7%, 27.4%, and 53.9% were for children with 0, 1, and multiple conditions, respectively, and similar proportions were observed for hospital days. The three populations accounted for the most hospital days were as follows: children with no chronic condition (20.9%), children with a mental health condition and at least 1 additional chronic condition (20.2%), and children with a mental health condition without an additional chronic condition (13.3%). The most common mental health conditions were substance abuse disorders and depression.</p>

<p><strong>CONCLUSIONS: </strong>CMCC accounted for over one-fourth of acute-care hospitalizations and one-half of all hospital dollars for US pediatric care in 2012. Substantial CMCC hospital resource use involves children with mental health-related conditions.</p>

<p><strong>BACKGROUND AND OBJECTIVES: </strong>Children who experience high health care costs are increasingly enrolled in clinical initiatives to improve their health and contain costs. Hospitalization is a significant cost driver. We describe hospitalization trends for children with highest annual inpatient cost (CHIC) and identify characteristics associated with persistently high inpatient costs in subsequent years.</p>

<p><strong>METHODS: </strong>Retrospective study of 265 869 children age 2 to 15 years with ≥1 admission in 2010 to 39 children's hospitals in the Pediatric Health Information System. CHIC were defined as the top 10% of total inpatient costs in 2010 (n = 26 574). Multivariate regression and regression tree modeling were used to distinguish individual characteristics and interactions of characteristics, respectively, associated with persistently high inpatient costs (≥80th percentile in 2011 and/or 2012).</p>

<p><strong>RESULTS: </strong>The top 10% most expensive children (CHIC) constituted 56.9% ($2.4 billion) of total inpatient costs in 2010. Fifty-eight percent (n = 15 391) of CHIC had no inpatient costs in 2011 to 2012, and 27.0% (n = 7180) experienced persistently high inpatient cost. Respiratory chronic conditions (odds ratio [OR] = 3.0; 95% confidence interval [CI], 2.5-3.5), absence of surgery in 2010 (OR = 2.0; 95% CI, 1.8-2.1), and technological assistance (OR = 1.6; 95% CI, 1.5-1.7) were associated with persistently high inpatient cost. In regression tree modeling, the greatest likelihood of persistence (65.3%) was observed in CHIC with ≥3 hospitalizations in 2010 and a chronic respiratory condition.</p>

<p><strong>CONCLUSIONS: </strong>Most children with high children's hospital inpatient costs in 1 year do not experience hospitalization in subsequent years. Interactions of hospital use and clinical characteristics may be helpful to determine which children will continue to experience high inpatient costs over time.</p>

<p>A small but growing population of children with medical complexity, many of whom are covered by Medicaid, accounts for a high proportion of pediatric health care spending. We first describe the expenditures for children with medical complexity insured by Medicaid across the care continuum. We report the increasingly large amount of spending on hospital care for these children, relative to the small amount of primary care and home care spending. We then present a business case that estimates how cost savings might be achieved for children with medical complexity from potential reductions in hospital and emergency department use and shows how the savings could underwrite investments in outpatient and community care. We conclude by discussing the importance of these findings in the context of Medicaid's quality of care and health care reform.</p>