<p><strong>OBJECTIVE: </strong>To describe the prevalence and characteristics of infection-related readmissions in children and to identify opportunities for readmission reduction and estimate associated cost savings.</p>

<p><strong>STUDY DESIGN: </strong>Retrospective analysis of 380,067 nationally representative index hospitalizations for children using the 2014 Nationwide Readmissions Database. We compared 30-day, all-cause unplanned readmissions and costs across 22 infection categories. We used the Inpatient Essentials database to measure hospital-level readmission rates and to establish readmission benchmarks for individual infections. We then estimated the number of readmissions avoided and costs saved if hospitals achieved the 10th percentile of hospitals' readmission rates (ie, readmission benchmark). All analyses were stratified by the presence/absence of a complex chronic condition (CCC).</p>

<p><strong>RESULTS: </strong>The overall 30-day readmission rate was 4.9%. Readmission rates varied substantially across infections and by presence/absence of a CCC (CCC: range, 0%-21.6%; no CCC: range, 1.5%-8.6%). Approximately 42.6% of readmissions (n = 3,576) for children with a CCC and 54.7% of readmissions (n = 5,507) for children without a CCC could have been potentially avoided if hospitals achieved infection-specific benchmark readmission rates, which could result in an estimated savings of $70.8 million and $44.5 million, respectively. Bronchiolitis, pneumonia, and upper respiratory tract infections were among infections with the greatest number of potentially avoidable readmissions and cost savings for children with and without a CCC.</p>

<p><strong>CONCLUSION: </strong>Readmissions following hospitalizations for infection in children vary significantly by infection type. To improve hospital resource use for infections, future preventative measures may prioritize children with complex chronic conditions and those with specific diagnoses (eg, respiratory illnesses).</p>

<p><strong>OBJECTIVE: </strong>To identify where rural children with mental health conditions are hospitalized and to determine differences in outcomes based upon location of hospitalization.</p>

<p><strong>STUDY DESIGN: </strong>Retrospective cohort analysis of US rural children aged 0-18 years with a mental health hospitalization between January 1, 2014, and November 30, 2014, using the 2014 Agency for Healthcare Research and Quality's Nationwide Readmissions Database. Hospitalizations for rural children were categorized to children's hospitals, metropolitan non-children's hospitals, or rural hospitals. Associations between hospital location and outcomes were assessed with logistic (readmission) and negative binomial regression (length of stay (LOS)) models. Classification and regression trees (CART) describe characteristics of most common hospitalizations at a rural hospital.</p>

<p><strong>RESULTS: </strong>Of 21,666 mental health hospitalizations of rural children, 20.6% were at rural hospitals. After adjustment for clinical and demographic characteristics, LOS was higher at metropolitan non-children's and children's hospitals compared with rural hospitals [LOS: adjusted rate ratio (aRR) 1.35 (95% CI 1.29, 1.41) and aRR 1.33 (95% CI 1.25, 1.41); all P &lt; .01]. 30-day readmission was lower at metropolitan non-children's and children's hospitals compared with rural hospitals [adjusted odds ratio (aOR) 0.73 (95% CI 0.63, 0.84) and aOR 0.59 (95% CI 0.48, 0.71); all p&lt;0.001]. Adolescent males living in poverty with externalizing behavior disorder had the highest percentage (69.4%) of hospitalization at rural hospitals.</p>

<p><strong>CONCLUSIONS: </strong>Although hospitalizations at children's and metropolitan non-children's hospitals were longer, patient outcomes were more favorable.</p>

<p><strong>BACKGROUND: </strong>Improvement initiatives promote safe and efficient care for hospitalized children. However, these may be associated with limited cost savings. In this article, we sought to understand the potential financial benefit yielded by improvement initiatives by describing the inpatient allocation of costs for common pediatric diagnoses.</p>

<p><strong>METHODS: </strong>This study is a retrospective cross-sectional analysis of pediatric patients aged 0 to 21 years from 48 children's hospitals included in the Pediatric Health Information System database from January 1, 2017, to December 31, 2017. We included hospitalizations for 8 common inpatient pediatric diagnoses (seizure, bronchiolitis, asthma, pneumonia, acute gastroenteritis, upper respiratory tract infection, other gastrointestinal diagnoses, and skin and soft tissue infection) and categorized the distribution of hospitalization costs (room, clinical, laboratory, imaging, pharmacy, supplies, and other). We summarized our findings with mean percentages and percent of total costs and used mixed-effects models to account for disease severity and to describe hospital-level variation.</p>

<p><strong>RESULTS: </strong>For 195 436 hospitalizations, room costs accounted for 52.5% to 70.3% of total hospitalization costs. We observed wide hospital-level variation in nonroom costs for the same diagnoses (25%-81% for seizure, 12%-51% for bronchiolitis, 19%-63% for asthma, 19%-62% for pneumonia, 21%-78% for acute gastroenteritis, 21%-63% for upper respiratory tract infection, 28%-69% for other gastrointestinal diagnoses, and 21%-71% for skin and soft tissue infection). However, to achieve a cost reduction equal to 10% of room costs, large, often unattainable reductions (&gt;100%) in nonroom cost categories are needed.</p>

<p><strong>CONCLUSIONS: </strong>Inconsistencies in nonroom costs for similar diagnoses suggest hospital-level treatment variation and improvement opportunities. However, individual improvement initiatives may not result in significant cost savings without specifically addressing room costs.</p>

<p><strong>OBJECTIVE: </strong>To examine how characteristics vary between children with any mental health (MH) diagnosis who have typical spending and the highest spending; to identify independent predictors of highest spending; and to examine drivers of spending groups.</p>

<p><strong>METHODS: </strong>This retrospective analysis utilized 2016 Medicaid claims from 11 states and included 775,945 children ages 3-17 years with any MH diagnosis and at least 11 months of continuous coverage. We compared demographic characteristics and Medicaid expenditures based on total healthcare spending: the top 1% (highest-spending) and remaining 99% (typical-spending). We used chi-squared tests to compare the 2 groups and adjusted logistic regression to identify independent predictors of being in the top 1% highest-spending group.</p>

<p><strong>RESULTS: </strong>Children with MH conditions accounted for 55% of Medicaid spending among 3- to 17-year-olds. Patients in the highest-spending group were more likely to be older, have multiple MH conditions, and have complex chronic physical health conditions (p&lt;0.001). The highest-spending group had $164,003 per-member-per-year (PMPY) in total healthcare spending, compared to $6097 PMPY in the typical-spending group. Ambulatory MH services contributed the largest proportion (40%) of expenditures ($2455 PMPY) in the typical-spending group; general health hospitalizations contributed the largest proportion (36%) of expenditures ($58,363 PMPY) in the highest-spending group.</p>

<p><strong>CONCLUSIONS: </strong>Among children with MH conditions, mental and physical health comorbidities were common and spending for general healthcare outpaced spending for MH care. Future research and quality initiatives should focus on integrating MH and physical healthcare services and investigate whether current spending on MH services supports high-quality MH care.</p>

<p><strong>BACKGROUND AND OBJECTIVES: </strong>Although potentially dangerous, little is known about outpatient opioid exposure (OE) in children and youth with special health care needs (CYSHCN). We assessed the prevalence and types of OE and the diagnoses and health care encounters proximal to OE in CYSHCN.</p>

<p><strong>METHODS: </strong>This is a retrospective cohort study of 2 597 987 CYSHCN aged 0-to-18 years from 11 states, continuously enrolled in Medicaid in 2016, with ≥1 chronic condition. OE included any filled prescription (single or multiple) for opioids. Health care encounters were assessed within 7 days before and 7 and 30 days after OE.</p>

<p><strong>RESULTS: </strong>Among CYSHCN, 7.4% had OE. CYSHCN with OE versus without OE were older (ages 10-18 years: 69.4% vs 47.7%), had more chronic conditions (≥3 conditions: 49.1% vs 30.6%), and had more polypharmacy (≥5 other medication classes: 54.7% vs 31.2%), &lt; .001 for all. Most (76.7%) OEs were single fills with a median duration of 4 days (interquartile range: 3-6). The most common OEs were acetaminophen-hydrocodone (47.5%), acetaminophen-codeine (21.5%), and oxycodone (9.5%). Emergency department visits preceded 28.8% of OEs, followed by outpatient surgery (28.8%) and outpatient specialty care (19.1%). Most OEs were preceded by a diagnosis of infection (25.9%) or injury (22.3%). Only 35.1% and 62.2% of OEs were associated with follow-up visits within 7 and 30 days, respectively.</p>

<p><strong>CONCLUSIONS: </strong>OE in CYSHCN is common, especially with multiple chronic conditions and polypharmacy. In subsequent studies, researchers should examine the appropriateness of opioid prescribing, particularly in emergency departments, as well as assess for drug interactions with chronic medications and reasons for insufficient follow-up.</p>

<p>Insurers are increasingly adopting narrow network strategies. Little is known about how these strategies may affect children's access to needed specialty care. We examined the percentage of pediatric specialty hospitalizations that would be beyond existing Medicare Advantage network adequacy distance requirements for adult hospital care and, as a secondary analysis, a pediatric adaptation of the Medicare Advantage requirements. We examined 748,920 hospitalizations at eighty-one children's hospitals that submitted data for the period October 2014-September 2015. Nearly half of specialty hospitalizations were outside the Medicare Advantage distance requirements. Under the pediatric adaptation, there was great variability among the hospitals, with the percent of hospitalizations beyond the distance requirements ranging from less than 1&nbsp;percent to 35&nbsp;percent. Instead of, or in addition to, time and distance standards, policy makers may need to consider more nuanced network definitions, including functional capabilities of the pediatric care network or clear exception policies for essential specialty care services.</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>Medicaid payments tend to be less than the cost of care. Federal Disproportionate Share Hospital (DSH) payments help hospitals recover such uncompensated costs of Medicaid-insured and uninsured patients. The Patient Protection and Affordable Care Act reduces DSH payments in anticipation of fewer uninsured patients and therefore decreased uncompensated care. However, unlike adults, few hospitalized children are uninsured, while many have Medicaid coverage. Therefore, DSH payment reductions may expose extensive Medicaid financial losses for hospitals serving large absolute numbers of children.</p>

<p><strong>Objectives: </strong>To identify types of hospitals with the highest Medicaid losses from pediatric inpatient care and to estimate the proportion of losses recovered through DSH payments.</p>

<p><strong>Design, Setting, and Participants: </strong>This retrospective cross-sectional analysis evaluated Medicaid-insured hospital discharges of patients 20 years and younger from 23 states in the 2009 Kids' Inpatient Database. The dates of the analysis were March to September 2015. Hospitals were categorized as freestanding children's hospitals (FSCHs), children's hospitals within general hospitals, non-children's hospital teaching hospitals, and non-children's hospital nonteaching hospitals. Financial records of FSCHs in the data set were used to estimate the proportion of Medicaid losses recovered through DSH payments.</p>

<p><strong>Main Outcomes and Measures: </strong>Hospital financial losses from inpatient care of Medicaid-insured children (defined as the reimbursement minus the cost of care) were compared across hospital types. For our subsample of FSCHs, Medicaid-insured inpatient financial losses were calculated with and without each hospital's DSH payment.</p>

<p><strong>Results: </strong>The 2009 Kids' Inpatient Database study population included 1485 hospitals and 843 725 Medicaid-insured discharges. Freestanding children's hospitals had a higher median number of Medicaid-insured discharges (4082; interquartile range [IQR], 3524-5213) vs non-children's hospital teaching hospitals (674; IQR, 258-1414) and non-children's hospital nonteaching hospitals (161; IQR, 41-420). Freestanding children's hospitals had the largest median Medicaid losses from pediatric inpatient care (-$9 722 367; IQR, -$16 248 369 to -$2 137 902). Smaller losses were experienced by non-children's hospital teaching hospitals (-$204 100; IQR, -$1 014 100 to $14 700]) and non-children's hospital nonteaching hospitals (-$28 310; IQR, -$152 370 to $9040]). Disproportionate Share Hospital payments to FSCHs reduced their Medicaid losses by almost half.</p>

<p><strong>Conclusions and Relevance: </strong>Estimated financial losses from pediatric inpatients covered by Medicaid were much larger for FSCHs than for other hospital types. For children's hospitals, small anticipated increases in insured children are unlikely to offset the reductions in DSH payments.</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>