Positive Predictive Value of ICD-10 Codes to Identify Acute Suicidal and Self Harm Behaviors.

OBJECTIVE: The accuracy of diagnosis codes to identify suicidal behaviors, including suicide ideation (SI) and self-harm (SH) events, is unknown. The objective of this study was to determine the positive predictive value (PPV) of International Classification of Disease, 10th Revision codes to identify SI/SH events that may be used in studies using administrative and claims data. METHODS: We performed a secondary analysis of a cross-sectional study of children 5 to 17 years of age hospitalized at 2 US children's hospitals with a discharge diagnosis of a neuropsychiatric event, including an SI or SH event. A true International Classification of Disease, 10th Revision SI or SH diagnosis was defined as SI or SH present on admission and directly related to hospitalization as compared with physician record review. PPV with 95% confidence intervals (CIs) were calculated overall and stratified by diagnosis order and age (5 to 11 years vs 12 to 17 years). RESULTS: There were 376 children or adolescents with a discharge diagnosis of an SI or SH event. The median age was 14 years, and the majority of individuals were female (58%), non-Hispanic White (69%), and privately insured (57%). A total of 332 confirmed SI/SH cases were identified with a PPV of 0.88 (95% CI 0.85-0.91). PPVs were similar when stratified by diagnosis order: primary 0.94 (95% 0.88-0.97) versus secondary 0.86 (95% CI 81-90). PPVs were also similar in adolescents (0.89, CI 0.85-0.92) compared with children (0.84, 95% CI 0.74-0.91). CONCLUSIONS: The use of these validated code sets to identify SI or SH events may minimize misclassification in future studies of suicidal and self-harm hospitalizations.

Essential Concepts for Reducing Bias in Observational Studies.

Randomized controlled trials (RCTs) are the gold standard study design for clinical research, as prospective randomization, at least in theory, balances any differences that can exist between groups (including any differences not measured as part of the study) and isolates the studied treatment effect. Any remaining imbalances after randomization are attributable to chance. However, there are many barriers to conducting RCTs within pediatric populations, including lower disease prevalence, high costs, inadequate funding, and additional regulatory requirements. Researchers thus frequently use observational study designs to address many research questions. Observational studies, whether prospective or retrospective, do not involve randomization and thus have more potential for bias when compared with RCTs because of imbalances that can exist between comparison groups. If these imbalances are associated with both the exposure of interest and the outcome, then failure to account for these imbalances may result in a biased conclusion. Understanding and addressing differences in sociodemographic and/or clinical characteristics within observational studies are thus necessary to reduce bias. Within this Method/ology submission we describe techniques to minimize bias by controlling for important measurable covariates within observational studies and discuss the challenges and opportunities in addressing specific variables.

Characteristics Associated With Serious Self-Harm Events in Children and Adolescents.

OBJECTIVES: To identify patterns of psychiatric comorbidity among children and adolescents with a serious self-harm event. METHODS: We studied children aged 5 to 18 years hospitalized with a neuropsychiatric event at 2 children's hospitals from April 2016 to March 2020. We used Bayesian profile regression to identify distinct clinical profiles of risk for self-harm events from 32 covariates: age, sex, and 30 mental health diagnostic groups. Odds ratios (ORs) and 95% credible intervals (CIs) were calculated compared with a reference profile with the overall baseline risk of the cohort. RESULTS: We included 1098 children hospitalized with a neuropsychiatric event (median age 14 years [interquartile range (IQR) 11-16]). Of these, 406 (37%) were diagnosed with a self-harm event. We identified 4 distinct profiles with varying risk for a self-harm diagnosis. The low-risk profile (median 0.035 [IQR 0.029-0.041]; OR 0.08, 95% CI 0.04-0.15) was composed primarily of children aged 5 to 9 years without a previous psychiatric diagnosis. The moderate-risk profile (median 0.30 [IQR 0.27-0.33]; reference profile) included psychiatric diagnoses without depressive disorders. Older female adolescents with a combination of anxiety, depression, substance, and trauma disorders characterized the high-risk profile (median 0.69 [IQR 0.67-0.70]; OR 5.09, 95% CI 3.11-8.38). Younger males with mood and developmental disorders represented the very high-risk profile (median 0.76 [IQR 0.73-0.79]; OR 7.21, 95% CI 3.69-15.20). CONCLUSIONS: We describe 4 separate profiles of psychiatric comorbidity that can help identify children at elevated risk for a self-harm event and subsequent opportunities for intervention.

A Pediatric Hospital Medicine Primer for Performing Research Using Administrative Data.

Provider- and claims-focused administrative databases are powerful tools for conducting health services research, and these studies often have good generalizability owing to diversity of hospitals from which samples are derived. In this research methods article, we describe administrative data and how available provider- and claims-focused administrative databases can be used to conduct health services research. We describe common observational study designs using administrative data and provide real-world examples. We highlight the strengths and weaknesses of studies conducted using administrative data and describe methodological considerations to reduce bias and improve the rigor of observational studies using administrative data. Finally, we provide guidance on the types of study questions suitable for observational study designs using administrative data.

Pediatric emergency department to primary care transfer protocol: Transforming access for patients' needs.

BACKGROUND: Previous interventions to reduce emergency department (ED) overutilization from non-urgent visits have shown little success. At our hospital, we created an ED to primary care clinic (PCC) transfer protocol for non-urgent ED visits of established patients. Our study analyzed the impact of this protocol on patient encounters. METHODS: Chart reviews were conducted for a retrospective cohort of transfers from the ED to PCC from 9/01/17-8/31/18. Primary outcomes included length of stay (LOS), cost, and need for return to the ED. Cost savings were calculated by comparing encounters with identical primary diagnoses in the ED with internal technical and professional financial data. Secondary outcomes were final diagnoses and primary care services provided. RESULTS: 374 patient encounters were transferred from ED to PCC. The five most common diagnoses were viral upper respiratory infection (n=80, 21.4%), dermatologic diagnoses (n=37, 9.9%), acute otitis media (n=35, 9.4%), pharyngitis (n=34, 9.1%), and influenza (n=34, 9.1%). Overall, total cost savings equaled approximately $100,000. For the top 10 diagnoses, costs were reduced from $29-$46 per $100 of ED costs and LOS was reduced by a mean of 49 min/encounter. For 9 of these 10 conditions, costs exceeded reimbursement in both settings; however, evaluation in PCC versus ED reduced the loss of revenue by 10-68%. Sixty-four encounters (17.1%) received additional primary care services. There were no safety events or inappropriate transfers. CONCLUSIONS: This protocol provided a safe, efficient method for patients to be evaluated in their medical home while reducing non-urgent emergency visits in the ED. LEVEL OF EVIDENCE: VI.

Child Opportunity Index 2.0 and acute care utilization among children with medical complexity.

BACKGROUND: Disproportionately high acute care utilization among children with medical complexity (CMC) is influenced by patient-level social complexity. OBJECTIVE: The objective of this study was to determine associations between ZIP code-level opportunity and acute care utilization among CMC. DESIGN, SETTING, AND PARTICIPANTS: This cross-sectional, multicenter study used the Pediatric Health Information Systems database, identifying encounters between 2016-2019. CMC aged 28 days to <16 years with an initial emergency department (ED) encounter or inpatient/observation admission in 2016 were included in primary analyses. MAIN OUTCOME AND MEASURES: We assessed associations between the nationally-normed, multi-dimensional, ZIP code-level Child Opportunity Index 2.0 (COI) (high COI = greater opportunity), and total utilization days (hospital bed-days + ED discharge encounters). Analyses were conducted using negative binomial generalized estimating equations, adjusting for age and distance from hospital and clustered by hospital. Secondary outcomes included intensive care unit (ICU) days and cost of care. RESULTS: A total of 23,197 CMC were included in primary analyses. In unadjusted analyses, utilization days decreased in a stepwise fashion from 47.1 (95% confidence interval: 45.5, 48.7) days in the lowest COI quintile to 38.6 (36.9, 40.4) days in the highest quintile (p < .001). The same trend was present across all outcome measures, though was not significant for ICU days. In adjusted analyses, patients from the lowest COI quintile utilized care at 1.22-times the rate of those from the highest COI quintile (1.17, 1.27). CONCLUSIONS: CMC from low opportunity ZIP codes utilize more acute care. They may benefit from hospital and community-based interventions aimed at equitably improving child health outcomes.

Identifying Acute Neuropsychiatric Events in Children and Adolescents.

OBJECTIVES: The objective of this study was to develop and validate an approach to accurately identify incident pediatric neuropsychiatric events (NPEs) requiring hospitalization by using administrative data. METHODS: We performed a cross-sectional, multicenter study of children 5 to 18 years of age hospitalized at two US children's hospitals with an NPE. We developed and evaluated 3 NPE identification algorithms: (1) primary or secondary NPE International Classification of Diseases, 10th Revision diagnosis alone, (2) NPE diagnosis, the NPE was present on admission, and the primary diagnosis was not malignancy- or surgery-related, and (3) identical to algorithm 2 but without requiring the NPE be present on admission. The positive predictive value (PPV) of each algorithm was calculated overall and by diagnosis field (primary or secondary), clinical significance, and NPE subtype. RESULTS: There were 1098 NPE hospitalizations included in the study. A total of 857 confirmed NPEs were identified for algorithm 1, yielding a PPV of 0.78 (95% confidence interval [CI] 0.76-0.80). Algorithm 2 (n = 846) had an overall PPV of 0.89 (95% CI 0.87-0.91). For algorithm 3 (n = 938), the overall PPV was 0.86 (95% CI 0.83-0.88). PPVs varied by diagnosis order, NPE clinical significance, and subtype. The PPV for critical clinical significance was 0.99 (0.97-0.99) for all 3 algorithms. CONCLUSIONS: We identified a highly accurate method to identify neuropsychiatric adverse events in children and adolescents. The use of these approaches will improve the rigor of future studies of NPE, including the necessary evaluations of medication adverse events, infections, and chronic conditions.

Financial Implications of Short Stay Pediatric Hospitalizations.

BACKGROUND: Observation status (OBS) stays incur similar costs to low-acuity, short-stay inpatient (IP) hospitalizations. Despite this, payment for OBS is likely less and may represent a financial liability for children's hospitals. Thus, we described the financial outcomes associated with OBS stays compared to similar IP stays by hospital and payer. METHODS: We conducted a retrospective cohort study of clinically similar pediatric OBS and IP encounters at 15 hospitals contributing to the revenue management program in 2017. Clinical and demographic characteristics were described. For each hospitalization, the cost coverage ratio (CCR) was calculated by dividing revenue by estimated cost of hospitalization. Differences in CCR were evaluated using Wilcoxon rank sum tests and results were stratified by billing designation and payer. CCR for OBS and IP stays were compared by institution, and the estimated increase in revenue by billing OBS stays as IP was calculated. RESULTS: OBS was assigned to 70 981 (56.9%) of 124 789 hospitalizations. Use of OBS varied across hospitals (8%-86%). For included hospitalizations, OBS stays were more likely than IP stays to result in financial loss (57.0% vs 35.7%). OBS stays paid by public payer had the lowest median CCR (0.6; interquartile range [IQR], 0.2-0.9). Paying OBS stays at the median IP rates would have increased revenue by $167 million across the 15 hospitals. CONCLUSIONS: OBS stays were significantly more likely to result in poor financial outcomes than similar IP stays. Costs of hospitalization and billing designations are poorly aligned and represent an opportunity for children's hospitals and payers to restructure payment models.

Variation in Condition-Specific Readmission Rates Across US Children's Hospitals.

OBJECTIVE: Despite extensive efforts, overall readmission rates at US children's hospitals have not materially declined over the past decade, raising questions about how to direct future efforts. Using measures of prevalence and performance variation we describe readmission rates by condition and identify priority conditions for future intervention. METHODS: Retrospective cohort study of 49 US children's hospitals in the Pediatric Health Information System in 2017. Conditions were classified using All Patients Refined Diagnosis Related Groups. 30-day unadjusted and risk-adjusted readmission rates were calculated for each hospital/condition using the Pediatric All Cause Readmission measure. We ranked the highest volume conditions by rate variation (RV, interquartile range divided by the median) for each condition across hospitals. RESULTS: The sample included 811,434 index hospitalizations with 50,196 (6.2%) 30-day readmissions. The RV across hospitals/conditions was between 0 and 2.8 (median = 0.7). Common reasons for admission had low RVs across hospitals, for example, bronchiolitis (readmission rate = 5.6%, RV = 0.4), seizure (readmission rate = 6.6%, RV = 0.3), and asthma (readmission rate = 3.1%, RV = 0.4). We identified 33 conditions with high variation in readmission rates across hospitals, which accounted for 18% of all discharges and 11% of all pediatric readmissions. These conditions may serve as candidates for future readmission reduction activities. CONCLUSIONS: Many common childhood conditions have little variation in readmission rates across children's hospitals, suggesting limited future improvement opportunities. Conditions with high rate variation may provide opportunities for quality improvement; however, these conditions account for a relatively small share of total discharges suggesting modest potential impacts on national rates.

The Association of the Childhood Opportunity Index on Pediatric Readmissions and Emergency Department Revisits.

OBJECTIVE: Reutilization following discharge is costly to families and the health care system. Singular measures of the social determinants of health (SDOH) have been shown to impact utilization; however, the SDOH are multifactorial. The Childhood Opportunity Index (COI) is a validated approach for comprehensive estimation of the SDOH. Using the COI, we aimed to describe the association between SDOH and 30-day revisit rates. METHODS: This retrospective study included children 0 to 17 years within 48 children's hospitals using the Pediatric Health Information System from 1/1/2019 to 12/31/2019. The main exposure was a child's ZIP code level COI. The primary outcome was unplanned readmissions and emergency department (ED) revisits within 30 days of discharge. Primary outcomes were summarized by COI category and compared using chi-square or Kruskal-Wallis tests. Adjusted analysis used generalized linear mixed effects models with adjustments for demographics, clinical characteristics, and hospital clustering. RESULTS: Of 728,997 hospitalizations meeting inclusion criteria, 30-day unplanned returns occurred for 96,007 children (13.2%). After adjustment, the patterns of returns were significantly associated with COI. For example, 30-day returns occurred for 19.1% (95% confidence interval [CI]: 18.2, 20.0) of children living within very low opportunity areas, with a gradient-like decrease as opportunity increased (15.5%, 95% CI: 14.5, 16.5 for very high). The relative decrease in utilization as COI increased was more pronounced for ED revisits. CONCLUSIONS: Children living in low opportunity areas had greater 30-day readmissions and ED revisits. Our results suggest that a broader approach, including policy and system-level change, is needed to effectively reduce readmissions and ED revisits.

Economic evaluation of regular transfusions for cerebral infarct recurrence in the Silent Cerebral Infarct Transfusion Trial.

In 2020, the American Society of Hematology published evidence-based guidelines for cerebrovascular disease in individuals with sickle cell anemia (SCA). Although the guidelines were based on National Institutes of Health-sponsored randomized controlled trials, no cost-effectiveness analysis was completed for children with SCA and silent cerebral infarcts. We conducted a cost-effectiveness analysis comparing regular blood transfusion vs standard care using SIT (Silent Cerebral Infarct Transfusion) Trial participants. This analysis included a modified societal perspective with direct costs (hospitalization, emergency department visit, transfusion, outpatient care, and iron chelation) and indirect costs (special education). Direct medical costs were estimated from hospitalizations from SIT hospitals and unlinked aggregated hospital and outpatient costs from SIT sites by using the Pediatric Health Information System. Indirect costs were estimated from published literature. Effectiveness was prevention of infarct recurrence. An incremental cost-effectiveness ratio using a 3-year time horizon (mean SIT Trial participant follow-up) compared transfusion vs standard care. A total of 196 participants received transfusions (n = 90) or standard care (n = 106), with a mean age of 10.0 years. Annual hospitalization costs were reduced by 54% for transfusions vs standard care ($4929 vs $10 802), but transfusion group outpatient costs added $22 454 to $137 022 per year. Special education cost savings were $2634 over 3 years for every infarct prevented. Transfusion therapy had an incremental cost-effectiveness ratio of $22 025 per infarct prevented. Children with preexisting silent cerebral infarcts receiving blood transfusions had lower hospitalization costs but higher outpatient costs, primarily associated with the oral iron chelator deferasirox. Regular blood transfusion therapy is cost-effective for infarct recurrence in children with SCA. This trial is registered at www.clinicaltrials.gov as #NCT00072761.

Factors That Drive Annual Variation in Pediatric Elbow Fracture Occurrence, Severity, and Resource Utilization.

BACKGROUND: Elbow fractures are the most common pediatric fractures requiring operative treatment. To date, few studies have examined what annual factors drive pediatric elbow fracture incidence and no studies have examined which annual factors drive elbow fracture severity or resource utilization. The goal of this study was to not only document the annual patterns of pediatric elbow fracture incidence and severity but also the impact of these patterns on resource utilization in the emergency department, emergency medical service transportation, and the operating room (OR). METHODS: Retrospective cohort study of 4414 pediatric elbow fractures from a single tertiary hospital (2007 to 2017). Exclusion criteria included outside treatment or lack of diagnosis by an orthopaedist. Presentation information, injury patterns, transport, and treatment requirements were collected. Pearson correlations were used to analyze factors influencing fracture incidence, severity, and resource utilization. RESULTS: Pediatric elbow fracture incidence positively correlated with monthly daylight hours, but significantly fewer elbow fractures occurred during summer vacation from school compared with surrounding in school months. While fewer overall fractures occurred during summer break, the fractures sustained were greater in severity, conferring higher rates of displacement, higher risk of neurovascular injury, and greater needs for emergency transportation and operative treatment. Yearly, elbow fractures required 320.6 OR hours (7.7% of all pediatric orthopaedic OR time and 12.3% of all pediatric orthopaedic operative procedures), 203.4 hospital admissions, and a total of 4753.7 miles traveled by emergency medical service transportation to manage. All-cause emergency department visits were negatively correlated with daylight hours, inversing the pattern seen in elbow fractures. CONCLUSION: Increased daylight, while school was in session, was a major driver of the incidence of pediatric elbow fractures. While summer vacation conferred fewer fractures, these were of higher severity. As such, increased daylight correlated strongly with monthly resource utilization, including the need for emergency transportation and operative treatment. This study provides objective data by which providers and administrators can more accurately allocate resources. LEVEL OF EVIDENCE: Level III-Retrospective comparative study.

Trends in Length of Stay and Readmissions in Children's Hospitals.

BACKGROUND AND OBJECTIVES: Patient complexity at US children's hospitals is increasing. Hospitals experience concurrent pressure to reduce length of stay (LOS) and readmissions, yet little is known about how these common measures of resource use and quality have changed over time. Our aim was to examine temporal trends in medical complexity, hospital LOS, and readmissions across a sample of US children's hospitals. METHODS: Retrospective cohort study of hospitalized patients from 42 children's hospitals in the Pediatric Health Information System from 2013 to 2017. After excluding deaths, healthy newborns, obstetric care, and low volume service lines, we analyzed trends in medical complexity, LOS, and 14-day all-cause readmissions using generalized linear mixed effects models, adjusting for changes in patient factors and case-mix. RESULTS: Between 2013 and 2017, a total of 3 355 815 discharges were included. Over time, the mean case-mix index and the proportion of hospitalized patients with complex chronic conditions or receiving intensive care increased (P < .001 for all). In adjusted analyses, mean LOS declined 3% (61.1 hours versus 59.3 hours from 2013 to 2017, P < .001), whereas 14-day readmissions were unchanged (7.0% vs 6.9%; P = .03). Reductions in adjusted LOS were noted in both medical and surgical service lines (3.6% and 2.0% decline, respectively; P < .001). CONCLUSIONS: Across US children's hospitals, adjusted LOS declined whereas readmissions remained stable, suggesting that children's hospitals are providing more efficient care for an increasingly complex patient population.

Outcomes Associated With High- Versus Low-Frequency Laboratory Testing Among Hospitalized Children.

BACKGROUND AND OBJECTIVES: Previous pediatric studies have revealed substantial variation in laboratory testing for specific conditions, but clinical outcomes associated with high- versus low-frequency testing are unclear. We hypothesized that hospitals with high- versus low-testing frequency would have worse clinical outcomes. METHODS: We conducted a multicenter retrospective cohort study of patients 0 to 18 years old with low-acuity hospitalizations in the years 2018-2019 for 1 of 10 common All Patient Refined Diagnosis Related Groups. We identified hospitals with high-, moderate-, and low-frequency testing for 3 common groups of laboratory tests: complete blood cell count, basic chemistry studies, and inflammatory markers. Outcomes included length of stay, 7- and 30-day emergency department revisit and readmission rates, and hospital costs, comparing hospitals with high- versus low-frequency testing. RESULTS: We identified 132 391 study encounters across 44 hospitals. Laboratory testing frequency varied by hospital and condition. We identified hospitals with high- (13), moderate- (20), and low-frequency (11) laboratory testing. When we compared hospitals with high- versus low-frequency testing, there were no differences in adjusted hospital costs (rate ratio 0.89; 95% confidence interval 0.71-1.12), length of stay (rate ratio 0.98; 95% confidence interval 0.91-1.06), 7-day (odds ratio 0.99; 95% confidence interval 0.81-1.21) or 30-day (odds ratio 1.01; 95% confidence interval 0.82-1.25) emergency department revisit rates, or 7-day (odds ratio 0.84; 95% confidence interval 0.65-1.25) or 30-day (odds ratio 0.91; 95% confidence interval 0.76-1.09) readmission rates. CONCLUSIONS: In a multicenter study of children hospitalized for common low-acuity conditions, laboratory testing frequency varied widely across hospitals, without substantial differences in outcomes. Our results suggest opportunities to reduce laboratory overuse across conditions and children's hospitals.

Observation Status Stays With Low Resource Use Within Children's Hospitals.

BACKGROUND: High costs associated with hospitalization have encouraged reductions in unnecessary encounters. A subset of observation status patients receive minimal interventions and incur low use costs. These patients may contain a cohort that could safely be treated outside of the hospital. Thus, we sought to describe characteristics of low resource use (LRU) observation status hospitalizations and variation in LRU stays across hospitals. METHODS: We conducted a retrospective cohort study of pediatric observation encounters at 42 hospitals contributing to the Pediatric Health Information System database from January 1, 2019, to December 31, 2019. For each hospitalization, we calculated the use ratio (nonroom costs to total hospitalization cost). We grouped stays into use quartiles with the lowest labeled LRU. We described associations with LRU stays and performed classification and regression tree analyses to identify the combination of characteristics most associated with LRU. Finally, we described the proportion of LRU hospitalizations across hospitals. RESULTS: We identified 174 315 observation encounters (44 422 LRU). Children <1 year (odds ratio [OR] 3.3; 95% confidence interval [CI] 3.1-3.4), without complex chronic conditions (OR 3.6; 95% CI 3.2-4.0), and those directly admitted (OR 4.2; 95% CI 4.1-4.4) had the greatest odds of experiencing an LRU encounter. Those children with the combination of direct admission, no medical complexity, and a respiratory diagnosis experienced an LRU stay 69.5% of the time. We observed variation in LRU encounters (1%-57% of observation encounters) across hospitals. CONCLUSIONS: LRU observation encounters are variable across children's hospitals. These stays may include a cohort of patients who could be treated outside of the hospital.

Readmissions Following Hospitalization for Infection in Children With or Without Medical Complexity.

OBJECTIVE: To describe the prevalence and characteristics of infection-related readmissions in children and to identify opportunities for readmission reduction and estimate associated cost savings. STUDY DESIGN: 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). RESULTS: 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. CONCLUSION: 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).

Hospitals' Diversity of Diagnosis Groups and Associated Costs of Care.

BACKGROUND AND OBJECTIVES: 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. METHODS: 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. RESULTS: 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 (P < .001) higher in FCHs and NFCHs (median 9.2 and 6.4 times higher, respectively) than NCHs. Across all hospitals, greater HDDI was associated (P = .002) with increased cost. Adjusting for HDDI resulted in a nonsignificant (P = .1) difference in cost across hospital types. CONCLUSIONS: Greater diagnosis diversity was associated with increased cost per hospitalization and should be considered when assessing associated costs of inpatient care for pediatric patients.

Opportunities for Stewardship in the Transition From Intravenous to Enteral Antibiotics in Hospitalized Pediatric Patients.

BACKGROUND/OBJECTIVE: Pediatric patients hospitalized with bacterial infections often receive intravenous (IV) antibiotics. Early transition to enteral antibiotics can reduce hospital duration, cost, and complications. We aimed to identify opportunities to transition from IV to enteral antibiotics, describe variation of transition among hospitals, and evaluate feasibility of novel stewardship metrics. METHODS: This multisite retrospective cohort study used the Pediatric Health Information System to identify pediatric patients hospitalized with pneumonia, neck infection, orbital infection, urinary tract infection (UTI), osteomyelitis, septic arthritis, or skin and soft tissue infection (SSTI) between 2017 and 2018. Opportunity days were defined as days on which patients received both IV antibiotics and enteral medications, suggesting enteral tolerance. Percent opportunity was defined as opportunity days divided by days on any antibiotics. Both outcomes excluded IV antibiotics that have no alternative oral formulation. We evaluated outcomes per infection and antibiotic and assessed across-hospital variation. RESULTS: We identified 88,522 aggregate opportunity days in 100,103 hospitalizations. On 57% of the antibiotic days, there was an opportunity to switch patients to enteral therapy, with greatest opportunity days in SSTI, neck infection, and pneumonia encounters, and with clindamycin, ceftriaxone, and ampicillin-sulbactam. Percent opportunity varied by infection (73% in septic arthritis to 40% in pneumonia). There was significant across-hospital variation in percent opportunity for all infections. CONCLUSION: This multicenter study demonstrated the potential opportunity to transition from IV to enteral therapy in over half of antibiotic days. Opportunity varied by infection, antibiotic, and hospital. Across-hospital variation demonstrated likely missed opportunities for earlier transition and the need to define optimal transition times. Stewardship efforts promoting earlier transition for highly bioavailable antibiotics could reduce healthcare utilization and promote high-value care. We identified feasible stewardship metrics.

Evaluating Definitions for Neonatal Abstinence Syndrome.

BACKGROUND AND OBJECTIVES: National estimates indicate that the incidence of neonatal abstinence syndrome (NAS), a postnatal opioid withdrawal syndrome, increased more than fivefold between 2004 and 2016. There is no gold standard definition for capturing NAS across clinical, research, and public health settings. Our objective was to evaluate how different definitions of NAS modify the calculated incidence when applied to a known population of opioid-exposed infants. METHODS: Data for this retrospective cohort study were obtained from opioid-exposed infants born at Vanderbilt University Medical Center in 2018. Six commonly used clinical and surveillance definitions of opioid exposure and NAS were applied to the study population and evaluated for accuracy in assessing clinical withdrawal. RESULTS: A total of 121 opioid-exposed infants met the criteria for inclusion in our study. The proportion of infants who met criteria for NAS varied by predefined definition, ranging from 17.4% for infants who received morphine to 52.8% for infants with the diagnostic code for opioid exposure. Twenty-eight infants (23.1%) received a clinical diagnosis of NAS by a medical provider, and 38 (34.1%) received the diagnostic code for NAS at discharge. CONCLUSIONS: We found significant variability in the incidence of opioid exposure and NAS among a single-center population using 6 common definitions. Our findings suggest a need to develop a gold standard definition to be used across clinical, research, and public health surveillance settings.