<p><strong>BACKGROUND: </strong>Use of intravenous magnesium (IVMg) for childhood asthma exacerbations has increased significantly in the last decade. Emergency department administration of IVMg has been shown to reduce asthma hospitalization, yet most children receiving IVMg in the emergency department are subsequently hospitalized. Our objective with the study was to examine hospital outcomes of children given IVMg for asthma exacerbations.</p>

<p><strong>METHODS: </strong>We conducted a retrospective cohort study using data from the Pediatric Health Information System. We used propensity score matching to compare children who received IVMg on the first day of hospitalization with those who did not. Primary outcomes were initiation and duration of noninvasive positive pressure ventilation. Secondary outcomes included mechanical ventilation (MV) initiation, duration of MV, length of stay, and subsequent tertiary medication use. Primary analysis was restricted to children admitted to nonintensive care inpatient units.</p>

<p><strong>RESULTS: </strong>Overall, 91 309 hospitalizations met inclusion criteria. IVMg was administered in 25 882 (28.4%) children. After propensity score matching, IVMg was not significantly associated with lower initiation (adjusted odds ratio 0.88; 95% confidence interval [CI] 0.74-1.05) or shorter duration of noninvasive positive pressure ventilation (rate ratio 0.94; 95% CI 0.87-1.02). Similarly, no significant associations were seen for MV initiation, MV duration, or length of stay. IVMg was associated with lower subsequent tertiary medication use (adjusted odds ratio 0.66; 95% CI 0.60-0.72). However, the association was lost when ipratropium was removed from the tertiary medication definition.</p>

<p><strong>CONCLUSIONS: </strong>IVMg administration was not significantly associated with improved hospital outcomes. Further study is needed to inform the optimal indications and timing of magnesium use during hospitalization.</p>

<p>Intravenous (IV) magnesium is used as an adjunct therapy in management of status asthmaticus with a goal of reducing intubation rate. A recent review suggests that IV magnesium use in status asthmaticus reduces admission rates. This is contrary to the observation of practicing emergency room physicians. The goal of this study was to assess trends in IV magnesium use for status asthmaticus in US children's hospitals over 8 years through a retrospective analysis of children younger than 18 years using the Pediatric Health Information System database. Outcomes were IV magnesium use, inpatient and intensive care unit admission rate, geometric mean length of stay, and 7-day all-cause readmission rate. IV magnesium use for asthma hospitalization more than doubled over 8 years (17% vs. 36%; P &lt; .001). Yearly trends were not significantly associated with hospital or intensive care unit admission rate or 7-day all-cause readmissions, although length of stay was reduced (P &lt; .001).</p>

<p><strong>BACKGROUND AND OBJECTIVES: </strong>Length of stay (LOS) is a common benchmarking measure for hospital resource use and quality. Observation status (OBS) is considered an outpatient service despite the use of the same facilities as inpatient status (IP) in most children's hospitals, and LOS calculations often exclude OBS stays. Variability in the use of OBS by hospitals may significantly impact calculated LOS. We sought to determine the impact of including OBS in calculating LOS across children's hospitals.</p>

<p><strong>METHODS: </strong>Retrospective cohort study of hospitalized children (age &lt;19 years) in 2017 from the Pediatric Health Information System (Children's Hospital Association, Lenexa, KS). Normal newborns, transfers, deaths, and hospitals not reporting LOS in hours were excluded. Risk-adjusted geometric mean length of stay (RA-LOS) for IP-only and IP plus OBS was calculated and each hospital was ranked by quintile.</p>

<p><strong>RESULTS: </strong>In 2017, 45 hospitals and 625 032 hospitalizations met inclusion criteria (IP = 410 731 [65.7%], OBS = 214 301 [34.3%]). Across hospitals, OBS represented 0.0% to 60.3% of total discharges. The RA-LOS (SD) in hours for IP and IP plus OBS was 75.2 (2.6) and 54.3 (2.7), respectively ( &lt; .001). For hospitals reporting OBS, the addition of OBS to IP RA-LOS calculations resulted in a decrease in RA-LOS compared with IP encounters alone. Three-fourths of hospitals changed ≥1 quintile in LOS ranking with the inclusion of OBS.</p>

<p><strong>CONCLUSIONS: </strong>Children's hospitals exhibit significant variability in the assignment of OBS to hospitalized patients and inclusion of OBS significantly impacts RA-LOS calculations. Careful consideration should be given to the inclusion of OBS when determining RA-LOS for benchmarking, quality and resource use measurements.</p>

<p><strong>OBJECTIVES: </strong>To describe hospital-based asthma-specific discharge components at children's hospitals and determine the association of these discharge components with pediatric asthma readmission rates.</p>

<p><strong>STUDY DESIGN: </strong>This is a multicenter retrospective cohort study of pediatric asthma hospitalizations in 2015 at children's hospitals participating in the Pediatric Health Information System. Children ages 5 to 17 years were included. An electronic survey assessing 13 asthma-specific discharge components was sent to quality leaders at all 49 hospitals. Correlations of combinations of asthma-specific discharge components and adjusted readmission rates were calculated.</p>

<p><strong>RESULTS: </strong>The survey response rate was 92% (45 of 49 hospitals). Thirty-day and 3-month adjusted readmission rates varied across hospitals, ranging from 1.9% to 3.9% for 30-day readmissions and 5.7% to 9.1% for 3-month readmissions. No individual or combination discharge components were associated with lower 30-day adjusted readmission rates. The only single-component significantly associated with a lower rate of readmission at 3 months was having comprehensive content of education (P &lt; .029). Increasing intensity of discharge components in bundles was associated with reduced adjusted 3-month readmission rates, but this did not reach statistical significance. This was seen in a 2-discharge component bundle including content of education and communication with the primary medical doctor, as well as a 3-discharge component bundle, which included content of education, medications in-hand, and home-based environmental mitigation.</p>

<p><strong>CONCLUSIONS: </strong>Children's hospitals demonstrate a range of asthma-specific discharge components. Although we found no significant associations for specific hospital-level discharge components and asthma readmission rates at 30 days, certain combinations of discharge components may support hospitals to reduce healthcare utilization at 3 months.</p>

<p><strong>OBJECTIVES: </strong>To determine the proportion of US children hospitalized for a primary mental health condition who are discharged to postacute care (PAC); whether PAC discharge is associated with demographic, clinical, and hospital characteristics; and whether PAC use varies by state.</p>

<p><strong>STUDY DESIGN: </strong>Retrospective cohort study of a nationally representative sample of US acute care hospitalizations for children ages 2-20 years with a primary mental health diagnosis, using the 2009 and 2012 Kids' Inpatient Databases. Discharge to PAC was used as a proxy for transfer to an inpatient mental health facility. We derived adjusted logistic regression models to assess the association of patient and hospital characteristics with discharge to PAC.</p>

<p><strong>RESULTS: </strong>In 2012, 14.7% of hospitalized children (n = 248 359) had a primary mental health diagnosis. Among these, 72% (n = 178 214) had bipolar disorder, depression, or psychosis, of whom 4.9% (n = 8696) were discharged to PAC. The strongest predictors of PAC discharge were homicidal ideation (aOR, 24.9; 96% CI, 4.1-150.4), suicide and self-injury (aOR, 15.1; 95% CI, 11.7-19.4), and substance abuse-related medical illness (aOR, 5.0; 95% CI, 4.5-5.6). PAC use varied widely by state, ranging from 2.2% to 36.3%.</p>

<p><strong>CONCLUSIONS: </strong>The majority of children hospitalized primarily for a mood disorder or psychosis were not discharged to PAC, and safety-related conditions were the primary drivers of the relatively few PAC discharges. There was substantial state-to-state variation. Target areas for quality improvement include improving access to PAC for children hospitalized for mood disorders or psychosis and equitable allocation of appropriate PAC resources across states.</p>

<p><strong>OBJECTIVE: </strong>(1) To evaluate regional variation in costs of care for 3 inpatient pediatric conditions, (2) assess potential drivers of variation, and (3) estimate cost savings from reducing variation.</p>

<p><strong>DESIGN/SETTING: </strong>Retrospective cohort study of hospitalizations for asthma, diabetic ketoacidosis (DKA), and acute gastroenteritis (AGE) at 46 children</p>

<p><strong>MEASUREMENTS:</strong> Variation in trimmed standardized costs were assessed within and across regions. Linear mixed effects models were adjusted for patient- and encounter-level variables to assess drivers of variation.</p>

<p><strong>RESULTS:</strong> After adjusting for patient-level factors, variation remained. Using census division clusters, mean trimmed and adjusted total standardized costs were 120% higher for asthma ($1920 vs $4227), 46% higher for DKA ($7429 vs $10,881), and 150% higher for AGE ($3316 vs $8292) in the highest-cost compared with the lowest-cost region. Comparing hospitals in the same region, standardized costs were significantly different (P &lt; 0.001) for each condition in each region. Drivers of variation were encounter-level variables including length of stay and intensive care unit utilization. For this cohort, annual savings from reducing variation would equal $69.1 million at the interregional level and $25.2 million at the intraregional level.</p>

<p><strong>CONCLUSIONS:</strong> Pediatric hospital costs vary between and within regions. Future studies should examine how much of this variation is avoidable. To the extent that less spending does not compromise outcomes, care models may be adjusted to eliminate unwarranted variation and reduce costs.</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>BACKGROUND AND OBJECTIVE: </strong>Like their adult counterparts, pediatric hospitals are increasingly at risk for financial penalties based on readmissions. Limited information is available on how the composition of a hospital's patient population affects performance on this metric and hence affects reimbursement for hospitals providing pediatric care. We sought to determine whether applying different readmission metrics differentially affects hospital performance based on the characteristics of patients a hospital serves.</p>

<p><strong>METHODS: </strong>We performed a cross-sectional analysis of 64 children's hospitals from the Children's Hospital Association Case Mix Comparative Database 2012 and 2013. We calculated 30-day observed-to-expected readmission ratios by using both all-cause (AC) and Potentially Preventable Readmissions (PPR) metrics. We examined the association between observed-to-expected rates and hospital characteristics by using multivariable linear regression.</p>

<p><strong>RESULTS: </strong>We examined a total of 1 416 716 hospitalizations. The mean AC 30-day readmission rate was 11.3% (range 4.3%-19.6%); the mean PPR rate was 4.9% (range 2.9%-6.9%). The average 30-day AC observed-to-expected ratio was 0.96 (range 0.63-1.23), compared with 0.95 (range 0.65-1.23) for PPR; 59% of hospitals performed better than expected on both measures. Hospitals with higher volumes, lower percentages of infants, and higher percentage of patients with low income performed worse than expected on PPR.</p>

<p><strong>CONCLUSIONS: </strong>High-volume hospitals, those that serve fewer infants, and those with a high percentage of patients from low-income neighborhoods have higher than expected PPR rates and are at higher risk of reimbursement penalties.</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>