<p><strong>OBJECTIVE: </strong>To examine trends in mental health (MH) visits to pediatric emergency departments (EDs) and identify whether ED disposition varies by presence of a hospital inpatient psychiatric unit (IPU).</p>

<p><strong>STUDY DESIGN: </strong>Cross-sectional study of 8,479,311 ED visits to 35 children's hospitals from 2012 to 2016 for patients aged 3 to 21 years with a primary MH or non-MH diagnosis. Multivariable generalized estimating equations and bivariate Rao-Scott chi-square tests were used to examine trends in ED visits and ED disposition by IPU status, adjusted for clustering by hospital.</p>

<p><strong>RESULTS: </strong>From 2012 to 2016, hospitals experienced a greater increase in ED visits with a primary MH vs. non-MH diagnosis (50.7% vs. 12.7% cumulative increase, P&lt;.001). MH visits were associated with patients who were older, female, white non-Hispanic, and privately insured compared with patients of non-MH visits (all P&lt;.001). 44% of MH visits in 2016 had a primary diagnosis of depressive disorders or suicide or self-injury, and the increase in visits was highest for these diagnosis groups (depression: 109.8%; suicide or self-injury: 110.2%). Among MH visits, presence of a hospital IPU was associated with increased hospitalizations (34.6% vs. 22.5%, P&lt;.001) and less transfers (9.3% vs. 16.2%, P&lt;.001).</p>

<p><strong>CONCLUSION: </strong>The increase in ED MH visits from 2012 to 2016 was four times greater than non-MH visits at US children's hospitals, and was primarily driven by patients diagnosed with depressive disorders and suicide or self-injury. Our findings have implications for strategic planning in tertiary children's hospitals dealing with a rising demand for acute MH care.</p>

<p><strong>OBJECTIVES: </strong>To determine whether social determinants of health (SDH) risk adjustment changes hospital-level performance on the 30-day Pediatric All-Condition Readmission (PACR) measure and improves fit and accuracy of discharge-level models.</p>

<p><strong>STUDY DESIGN: </strong>We performed a retrospective cohort study of all hospital discharges meeting criteria for the PACR from 47 hospitals in the Pediatric Health Information database from January to December 2014. We built four nested regression models by sequentially adding risk adjustment factors as follows: chronic condition indicators (CCIs); PACR patient factors (age and sex); electronic health record-derived SDH (race, ethnicity, payer), and zip code-linked SDH (families below poverty level, vacant housing units, adults without a high school diploma, single-parent households, median household income, unemployment rate). For each model, we measured the change in hospitals' readmission decile-rank and assessed model fit and accuracy.</p>

<p><strong>RESULTS: </strong>For the 458 686 discharges meeting PACR inclusion criteria, in multivariable models, factors associated with higher discharge-level PACR measure included age &lt;1 year, female sex, 1 of 17 CCIs, higher CCI count, Medicaid insurance, higher median household income, and higher percentage of single-parent households. Adjustment for SDH made small but significant improvements in fit and accuracy of discharge-level PACR models, with larger effect at the hospital level, changing decile-rank for 17 of 47 hospitals.</p>

<p><strong>CONCLUSIONS: </strong>We found that risk adjustment for SDH changed hospitals' readmissions rate rank order. Hospital-level changes in relative readmissions performance can have considerable financial implications; thus, for pay for performance measures calculated at the hospital level, and for research associated therewith, our findings support the inclusion of SDH variables in risk adjustment.</p>

<p><strong>IMPORTANCE: </strong>Performance-measure risk adjustment is of great interest to hospital stakeholders who face substantial financial penalties from readmissions pay-for-performance (P4P) measures. Despite evidence of the association between social determinants of health (SDH) and individual patient readmission risk, the effect of risk adjusting for SDH on readmissions P4P penalties to hospitals is not well understood.</p>

<p><strong>OBJECTIVE: </strong>To determine whether risk adjustment for commonly available SDH measures affects the readmissions-based P4P penalty status of a national cohort of children's hospitals.</p>

<p><strong>DESIGN, SETTING, AND PARTICIPANTS: </strong>Retrospective cohort study of 43 free-standing children's hospitals within the Pediatric Health Information System database in the calendar year 2013. We evaluated hospital discharges from 2013 that met criteria for 3M Health Information Systems' potentially preventable readmissions measure for calendar year 2013. The analysis was conducted from July 2015 to August 2015.</p>

<p><strong>EXPOSURES: </strong>Two risk-adjustment models: a baseline model adjusted for severity of illness and an SDH-enhanced model that adjusted for severity of illness and the following 4 SDH variables: race, ethnicity, payer, and median household income for the patient's home zip code.</p>

<p><strong>MAIN OUTCOMES AND MEASURES: </strong>Change in a hospital's potentially preventable readmissions penalty status (ie, change in whether a hospital exceeded the penalty threshold) using an observed-to-expected potentially preventable readmissions ratio of 1.0 as a penalty threshold.</p>

<p><strong>RESULTS: </strong>For the 179 400 hospital discharges from the 43 hospitals meeting inclusion criteria, median (interquartile range [IQR]) hospital-level percentages for the SDH variables were 39.2% nonwhite (n = 71 300; IQR, 28.6%-54.6%), 17.9% Hispanic (n = 32 060; IQR, 6.7%-37.0%), and 58.7% publicly insured (n = 106 116; IQR, 50.4%-67.8%). The hospital median household income for the patient's home zip code was $40 674 (IQR, $35 912-$46 190). When compared with the baseline model, adjustment for SDH resulted in a change in penalty status for 3 hospitals within the 15-day window (2 were no longer above the penalty threshold and 1 was newly penalized) and 5 hospitals within the 30-day window (3 were no longer above the penalty threshold and 2 were newly penalized).</p>

<p><strong>CONCLUSIONS AND RELEVANCE: </strong>Risk adjustment for SDH changed hospitals' penalty status on a readmissions-based P4P measure. Without adjusting P4P measures for SDH, hospitals may receive penalties partially related to patient SDH factors beyond the quality of hospital care.</p>

<p><strong>OBJECTIVE: </strong>To determine if household income is associated with hospitalization costs for severe traumatic brain injury (TBI) and spinal cord injury (SCI).</p>

<p><strong>STUDY DESIGN: </strong>Retrospective cohort study of inpatient, nonrehabilitation hospitalizations at 43 freestanding children's hospitals for patients &lt;19&nbsp;years old with unintentional severe TBI and SCI from 2009-2012. Standardized cost of care for hospitalizations was modeled using mixed-effects methods, adjusting for age, sex, race/ethnicity, primary payer, presence of chronic medical condition, mechanism of injury, injury severity, distance from residence to hospital, and trauma center level. Main exposure was zip code level median annual household income.</p>

<p><strong>RESULTS: </strong>There were 1061 patients that met inclusion criteria, 833 with TBI only, 227 with SCI only, and 1 with TBI and SCI. Compared with those with the lowest-income zip codes, patients from the highest-income zip codes were more likely to be older, white (76.7% vs 50.4%), have private insurance (68.9% vs 27.9%), and live closer to the hospital (median distance 26.7 miles vs 81.2 miles). In adjusted models, there was no significant association between zip code level household income and hospitalization costs.</p>

<p><strong>CONCLUSIONS: </strong>Children hospitalized with unintentional, severe TBI and SCI showed no difference in standardized hospital costs relative to a patient's home zip code level median annual household income. The association between household income and hospitalization costs may vary by primary diagnosis.</p>