<p>Healthcare and outcomes for children with medical complexity (CMC) and their families can be improved by conducting well-conceived, designed, implemented, and analyzed research studies of clinical interventions. This article presents a framework for how to approach the study of clinical interventions for CMC, including 7 key questions and example answers to each: (1) What intervention questions should be our focus? (2) What barriers to intervention research exist? (3) How do we design and optimize interventions? (4) How do we characterize and select patients to enroll? (5) How can we enhance data collection and integration? (6) How can we improve enrollment and participation? And (7) which intervention experimental designs should we choose? By exploring each of these key aspects of intervention-based research, we hope to expand thinking about and spark ideas for specific research projects focused on clinical interventions for CMC.</p>

<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>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>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>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><strong>OBJECTIVE: </strong>Mental health conditions (MHCs) are prevalent among hospitalized children and could influence the success of hospital discharge. We assessed the relationship between MHCs and 30-day readmissions.</p>

<p><strong>METHODS: </strong>This retrospective, cross-sectional study of the 2013 Nationwide Readmissions Database included 512,997 hospitalizations of patients ages 3 to 21 years for the 10 medical and 10 procedure conditions with the highest number of 30-day readmissions. MHCs were identified by using the International Classification of Diseases, 9th Revision-Clinical Modification codes. We derived logistic regression models to measure the associations between MHC and 30-day, all-cause, unplanned readmissions, adjusting for demographic, clinical, and hospital characteristics.</p>

<p><strong>RESULTS: </strong>An MHC was present in 17.5% of medical and 13.1% of procedure index hospitalizations. Readmission rates were 17.0% and 6.2% for medical and procedure hospitalizations, respectively. In the multivariable analysis, compared with hospitalizations with no MHC, hospitalizations with MHCs had higher odds of readmission for medical admissions (adjusted odds ratio [AOR], 1.23; 95% confidence interval [CI], 1.19-1.26] and procedure admissions (AOR, 1.24; 95% CI, 1.15-1.33). Three types of MHCs were associated with higher odds of readmission for both medical and procedure hospitalizations: depression (medical AOR, 1.57; 95% CI, 1.49-1.66; procedure AOR, 1.39; 95% CI, 1.17-1.65), substance abuse (medical AOR, 1.24; 95% CI, 1.18-1.30; procedure AOR, 1.26; 95% CI, 1.11-1.43), and multiple MHCs (medical AOR, 1.43; 95% CI, 1.37-1.50; procedure AOR, 1.26; 95% CI, 1.11-1.44).</p>

<p><strong>CONCLUSIONS: </strong>MHCs are associated with a higher likelihood of hospital readmission in children admitted for medical conditions and procedures. Understanding the influence of MHCs on readmissions could guide strategic planning to reduce unplanned readmissions for children with cooccurring physical and mental health conditions.</p>

<p><strong>BACKGROUND: </strong>Discharging hospitalized children involves several different components, but their relative value is unknown. We assessed which discharge components are perceived as most and least important by clinicians.</p>

<p><strong>METHODS: </strong>March and June of 2014, we conducted an online discrete choice experiment (DCE) among national societies representing 704 nursing, physician, case management, and social work professionals from 46 states. The DCE consisted of 14 discharge care components randomly presented two at a time for a total of 28 choice tasks. Best-worst scaling of participants' choices generated mean relative importance (RI) scores for each component, which allowed for ranking from least to most important.</p>

<p><strong>RESULTS: </strong>Participants, regardless of field or practice setting, perceived "Discharge Education/Teach-Back" (RI 11.1 [95% confidence interval, CI: 11.0-11.3]) and "Involve the Child's Care Team" (RI 10.6 [95% CI: 10.4-10.8]) as the most important discharge components, and "Information Reconciliation" (RI 4.1 [95% CI: 3.9-4.4]) and "Assigning Roles/Responsibilities of Discharge Care" (RI 2.8 [95% CI: 2.6-3.0]) as least important.</p>

<p><strong>CONCLUSIONS: </strong>A diverse group of pediatric clinicians value certain components of the pediatric discharge care process much more than others. Efforts to optimize the quality of hospital discharge for children should consider these findings.</p>