Pediatric Medical Complexity Algorithm Research Articles

Child maltreatment and behavioral health outcomes in child welfare: Exploring the roles of severity and polyvictimization

BackgroundChild maltreatment and polyvictimization are known risk factors for long-term detrimental health and development outcomes, including behavioral health challenges. However, effects from specific types and combinations of maltreatments are unclear. This study examined the association between maltreatment or polyvictimization and behavioral health in a child welfare sample. Participants and settingMedical records of children with child welfare involvement with at least one behavioral health condition (i.e., mental, behavioral or neurodevelopmental disorder, ICD-10 F01-F99) between 1/1/2018–12/31/2021 were extracted from a large, academic hospital system. MethodsBehavioral health complexity was categorized as non-chronic, non-complex chronic, or complex chronic using the Pediatric Medical Complexity Algorithm. Partial proportional logistic regression models adjusted for age, sex, race/ethnicity, caregiver type, and physical health complexity generated odds of behavioral health complexity by maltreatment type (physical abuse, sexual abuse, neglect) and maltreatment combinations. ResultsThe analytic sample included 3992 participants (mean age 7.6 (Standard Deviation, 5.0) 44 % female, 29 % white, 32 % black, 22 % Hispanic). Participants who experienced physical abuse (Odds Ratio [OR]: 1.79, 95 % Confidence Interval [CI]: 1.10–2.91), or neglect (OR: 1.69, 95 % CI: 1.38–2.07) were more likely to have increasing behavioral health complexity versus those without maltreatment. Participants with both physical abuse and neglect were over twice as likely (OR: 2.44, 95 % CI: 1.88–3.16) to have increasing behavioral health complexity versus those who did not experience maltreatment. ConclusionResults emphasize the differential impacts of maltreatment and polyvictimization exposures on behavioral health complexity among children with child welfare involvement that can guide risk assessment and clinical care.

Health Differs by Foster Care Eligibility: A Nine-Year Retrospective Observational Study Among Medicaid-Enrolled Children

ObjectiveThis study sought to determine the prevalence and rates of physical, behavioral, and chronic health conditions among Medicaid-enrolled Colorado children by foster care eligibility codes over 9 years. MethodsThis retrospective, population-based study used Colorado’s Medicaid administrative data for all enrolled children, aged <19 years old, from July 2011 to August 2020 to determine the period prevalence and rates of physical, behavioral, and chronic health conditions. We identified children in foster care by Medicaid eligibility codes and used the Pediatric Medical Complexity Algorithm version 3.0 to describe health condition outcomes. We report frequencies and percentages by foster care eligibility status, birth year cohort, and sex. ResultsAmong 1,084,026 children, we identified 34,971 children in the foster cohort. Rates of physical (1105.0 per 100,000 person-months (PMs)) and behavioral health conditions (583.6 per 100,000 PMs) were two to threefold higher among the foster cohort than peers (physical 685.1 per 100,000 PMs; behavioral 212.2 per 100,000 PMs). By birth cohort, rates of behavioral health conditions among children in foster care were up to 8 times greater than peers. The foster cohort had greater prevalence of chronic conditions with (55.2%) and without (38.6%) behavioral health inclusion. ConclusionsThis study provides a broader health assessment among Medicaid-enrolled children and finds condition disparities concentrated among youth in foster care. A more complete understanding of health problems among children in foster care is critical for health, child welfare, and Medicaid systems to improve health outcomes through coordinated and evidence-based interventions, programs, and policies.

Uncertainty and the NICU Experience: A Qualitative Evaluation of Family and Provider Perspectives.

There is limited information regarding caregiver and provider perspectives on uncertainty across the continuum of the neonatal intensive care unit (NICU) experience. Open-ended semi-structured interviews were conducted with providers and English- and Spanish-speaking caregivers of infants with a history of admission to a quaternary safety-net NICU. Major themes were generated using inductive-deductive thematic analysis. Seventy-six individuals participated in the study: 47 caregivers and 29 providers. The median gestational age of the infants was 29 weeks and 85% were classified as having chronic complex disease per the Pediatric Medical Complexity Algorithm. Most providers were neonatologists (37%) and nurses (27%) and more than half had over ten years of experience. A conceptual model of caregiver uncertainty was developed and key domains included drivers of uncertainty and its impact, and factors influencing coping and adaptation. Our analysis found a positive association between caregiver information gathering, clinical continuity, support systems, maternal mental health supports, and witnessing a child's progress and the development of adjustment to chronic uncertainty. These results suggest key areas for intervention that can promote parental adaptation to the uncertainty inherent in the NICU experience.

Comparing twodefinitions of pediatric complexity among children cared for in general and pediatric emergency departments in a statewide sample.

The number of children cared for in emergency departments (EDs) with medical complexity continues to rise. We sought to identify the concordance between 2 commonly used criteria of medical complexity among children presenting to a statewide sample of EDs. We conducted a retrospective cross-sectional study of children presenting to a statewide sample of Illinois EDs between 2016 and 2021. We classified patients as having medical complexity when using 2 definitions (≥1 pediatric Complex Chronic Condition [CCC] or complex chronic disease using the Pediatric Medical Complexity Algorithm [PMCA]) and compared their overlap and clinical outcomes. Of 6,550,296 pediatric ED encounters, CCC criteria and PMCA criteria were met in 217,609 (3.3%) and 175,708 (2.7%) encounters, respectively. Among patients with complexity, 100,015 (34.1%) met both criteria, with moderate agreement (κ=0.49). Children with complexity by CCC had similar rates of presentation to a pediatric hospital (16.3%vs 14.8%), admission (28.5%vs 33.7%), ICU stay (10.0%vs 10.1%), and in-hospital mortality (0.5%vs 0.5%) compared to children with complexity by PMCA. The most common visit diagnoses for children with CCCs were related to sickle cell disease with crisis (3.9%), abdominal pain (3.6%), and non-specific chest pain (2.7%). The most common diagnoses by PMCA were related to depressive disorders (4.9%), sickle cell disease with crisis (4.8%), and seizures (3.2%). The CCC and PMCA criteria of multisystem complexity identified different populations, with moderate agreement. Careful selection of operational definitions is required for proper application and interpretation in clinical and health services research.

Predictive Modeling to Identify Children With Complex Health Needs At Risk for Hospitalization.

Identifying children at high risk with complex health needs (CCHN) who have intersecting medical and social needs is challenging. This study's objectives were to (1) develop and evaluate an electronic health record (EHR)-based clinical predictive model ("model") for identifying high-risk CCHN and (2) compare the model's performance as a clinical decision support (CDS) to other CDS tools available for identifying high-risk CCHN. This retrospective cohort study included children aged 0 to 20 years with established care within a single health system. The model development/validation cohort included 33 months (January 1, 2016-September 30, 2018) and the testing cohort included 18 months (October 1, 2018-March 31, 2020) of EHR data. Machine learning methods generated a model that predicted probability (0%-100%) for hospitalization within 6 months. Model performance measures included sensitivity, positive predictive value, area under receiver-operator curve, and area under precision-recall curve. Three CDS rules for identifying high-risk CCHN were compared: (1) hospitalization probability ≥10% (model-predicted); (2) complex chronic disease classification (using Pediatric Medical Complexity Algorithm [PMCA]); and (3) previous high hospital utilization. Model development and testing cohorts included 116 799 and 27 087 patients, respectively. The model demonstrated area under receiver-operator curve = 0.79 and area under precision-recall curve = 0.13. PMCA had the highest sensitivity (52.4%) and classified the most children as high risk (17.3%). Positive predictive value of the model-based CDS rule (19%) was higher than CDS based on the PMCA (1.9%) and previous hospital utilization (15%). A novel EHR-based predictive model was developed and validated as a population-level CDS tool for identifying CCHN at high risk for future hospitalization.

Dental Caries in Medicaid-Insured Preschool Children With or Without Special Health Care Needs in Northeast Ohio

Children with special health care needs (CSHCN) are recognized to be at increased risk of developing dental caries (decay). Evidence is mixed regarding the association of preventive oral health care delivered by pediatric primary care clinicians with caries experience among CSHCN. To investigate caries experience, including untreated decay, among Medicaid-enrolled preschoolers with or without special health care needs. This cross-sectional study used baseline data from the Pediatric Providers Against Cavities in Children's Teeth study, a cluster-randomized hybrid effectiveness-implementation trial conducted among 1022 Medicaid-enrolled preschoolers aged 3 to 6 years attending well-child visits at 18 participating community pediatric primary care practices in northeast Ohio. Baseline data were collected from November 1, 2017, to August 31, 2019, with statistical analyses conducted from April to August 2022. Presence of special health care needs, as assessed by applying the Pediatric Medical Complexity Algorithm to International Statistical Classification of Diseases and Related Health Problems, Tenth Revision codes, was abstracted from electronic medical records. CSHCN were defined as having either noncomplex chronic disease (presence of only 1 nonprogressive chronic condition, or multiple nonprogressive chronic conditions in a single body system) or complex chronic disease (presence of any progressive chronic condition, malignant neoplasm, or significant chronic conditions involving multiple body systems). Untreated dental decay and caries experience as assessed through clinical dental examinations using International Caries Detection and Assessment System criteria. A total of 1022 children aged 3 to 6 years from 18 practices were enrolled in the study. The mean (SD) age of the study population was 4.3 (1.1) years, 554 (54.2%) were boys, and of 988 with data on race and ethnicity, 451 (45.6%) were Black. Of these, 301 of 1019 (29.5%) had a likely special health care need (225 with noncomplex chronic conditions and 76 with complex chronic conditions). The most frequent chronic conditions included asthma (n = 209) and mental or behavioral health disorders (n = 146), including attention-deficit/hyperactivity disorder, autism, and developmental delays. Overall, 296 children (29.0%) had untreated decay, and 378 (37.0%) had caries experience (decayed and filled teeth). Accounting for sociodemographic characteristics, CSHCN had 34% reduced odds of untreated decay (adjusted odds ratio [AOR], 0.66 [95% CI, 0.48-0.92]) compared with those with without chronic disease. In addition, caries experience was lower among CSHCN (AOR, 0.79 [95% CI, 0.60-1.04]). In this cross-sectional study of Medicaid-enrolled children who attended well-child visits as preschoolers, untreated dental decay was lower among CSHCN compared with those without chronic conditions. This study suggests that CSHCN may have had better access to the various types of dental care facilitated in medical settings.

Skeletal Outcomes in Children and Young Adults with Glomerular Disease.

Children with glomerular disease have unique risk factors for compromised bone health. Studies addressing skeletal complications in this population are lacking. This retrospective cohort study utilized data from PEDSnet, a national network of pediatric health systems with standardized electronic health record data for more than 6.5 million patients from 2009 to 2021. Incidence rates (per 10,000 person-years) of fracture, slipped capital femoral epiphysis (SCFE), and avascular necrosis/osteonecrosis (AVN) in 4598 children and young adults with glomerular disease were compared with those among 553,624 general pediatric patients using Poisson regression analysis. The glomerular disease cohort was identified using a published computable phenotype. Inclusion criteria for the general pediatric cohort were two or more primary care visits 1 year or more apart between 1 and 21 years of age, one visit or more every 18 months if followed >3 years, and no chronic progressive conditions defined by the Pediatric Medical Complexity Algorithm. Fracture, SCFE, and AVN were identified using SNOMED-CT diagnosis codes; fracture required an associated x-ray or splinting/casting procedure within 48 hours. We found a higher risk of fracture for the glomerular disease cohort compared with the general pediatric cohort in girls only (incidence rate ratio [IRR], 1.6; 95% CI, 1.3 to 1.9). Hip/femur and vertebral fracture risk were increased in the glomerular disease cohort: adjusted IRR was 2.2 (95% CI, 1.3 to 3.7) and 5 (95% CI, 3.2 to 7.6), respectively. For SCFE, the adjusted IRR was 3.4 (95% CI, 1.9 to 5.9). For AVN, the adjusted IRR was 56.2 (95% CI, 40.7 to 77.5). Children and young adults with glomerular disease have significantly higher burden of skeletal complications than the general pediatric population.

Variable Identification of Children With Medical Complexity in United States PICUs.

Children with medical complexity are at increased risk for critical illness and adverse outcomes. However, there is currently no consensus definition of medical complexity in pediatric critical care research. Retrospective, cross-sectional cohort study. One hundred thirty-one U.S. PICUs participating in the Virtual Pediatric Systems Database. Children less than 21 years old admitted from 2017 to 2019. Multisystem complexity was identified on the basis of two common definitions of medical complexity, Pediatric Complex Chronic Conditions (CCC), greater than or equal to 2 qualifying diagnoses, and Pediatric Medical Complexity Algorithm (PMCA), complex chronic disease. None. Of 291,583 index PICU admissions, 226,430 (77.7%) met at least one definition of multisystem complexity, including 168,332 patients identified by CCC and 201,537 by PMCA. Of these, 143,439 (63.3%) were identified by both definitions. Cohen kappa was 0.39, indicating only fair agreement between definitions. Children identified by CCC were younger and were less frequently scheduled admissions and discharged home from the ICU than PMCA. The most common reason for admission was respiratory in both groups, although this represented a larger proportion of CCC patients. ICU and hospital length of stay were longer for patients identified by CCC. No difference in median severity of illness scoring was identified between definitions, but CCC patients had higher inhospital mortality. Readmission to the ICU in the subsequent year was seen in approximately one-fifth of patients in either group. Commonly used definitions of medical complexity identified distinct populations of children with multisystem complexity in the PICU with only fair agreement.

Variation in care between pediatric and adult patients presenting with nephrolithiasis to tertiary care pediatric emergency departments in the United States (2009–2020)

Individuals with nephrolithiasis frequently present to the Emergency Department (ED). Safety and quality principles are often applied in pediatric EDs to children presenting with nephrolithiasis, such as limiting ionizing radiation exposure and opioid analgesics. However, it is unknown whether pediatric EDs apply these same principles to adult patients who present with nephrolithiasis. We hypothesized that adult patients would be associated with higher use of radiation-based imaging and opioid analgesics. To assess variations in diagnostic and treatment interventions and hospital utilization between pediatric and adult patients presenting to the pediatric ED with nephrolithiasis. A retrospective cohort study was conducted, examining outcomes for pediatric (<18-years-old) versus adult (≥18-years-old) patients in 42 pediatric EDs from 2009 to 2020 using the Pediatric Health Information System (PHIS) database. Patients with an ICD-9/10 principal diagnosis code of nephrolithiasis with no nephrolithiasis-related visits within the prior 6 months were included. Primary outcomes were imaging, medications, and surgical interventions. Secondary outcomes were hospital admissions, 90-day ED revisits, and 90-day readmissions. Generalized linear mixed models with random effects were used to adjust for confounding and clustering. In total, 16,117 patients with 17,837 encounters were included. Most hospitals were academic (95.2%), and a plurality were located in the South (38.1%). Most patients were <18-years-old (84.4%, median (interquartile range): 15 (12-17)-years-old), female (57.9%), and White (76.3%), and 17.1% were Hispanic/Latino. Most had no complex chronic conditions (89.2%) and no chronic disease per pediatric medical complexity algorithm (51.5%). For the primary outcome, adults, relative to pediatric patients, who presented to the pediatric ED with nephrolithiasis had higher adjusted odds of receiving computerized tomography (CT) scans (Odds Ratio [OR] 1.43 [95% Confidence Interval [CI] 1.29-1.59]) and opioid analgesics (OR 1.45 [95%CI 1.33-1.58]) (Summary Figure). Secondary outcomes showed that adults, relative to pediatric patients, had lower adjusted odds of hospital admissions, 90-day ED revisits, and 90-day readmissions. Our results suggest that certain pediatric safety and quality principles, such as limiting ionizing radiation exposure and opioid analgesic prescriptions, are not being equally applied to pediatric and adult patients who present to pediatric EDs with nephrolithiasis. The mechanism of these findings remains to be elucidated. Variations in care for individuals with nephrolithiasis reflect an opportunity for quality improvement in pediatric EDs and inform work exploring optimal care pathways for all patients presenting to the pediatric ED with nephrolithiasis.

Demographic and Clinical Differences Between Applied Definitions of Medical Complexity.

To identify the degree of concordance and characterize demographic and clinical differences between commonly used definitions of multisystem medical complexity in children hospitalized in children's hospitals. We conducted a retrospective, cross-sectional cohort study of children <21 years of age hospitalized at 47 US Pediatric Health Information System-participating children's hospitals between January 2017 to December 2019. We classified patients as having multisystem complexity when using 3 definitions of medical complexity (pediatric complex chronic conditions, pediatric medical complexity algorithm, and pediatric chronic critical illness) and assessed their overlap. We compared demographic, clinical, outcome, cost characteristics, and longitudinal healthcare utilization for each grouping. Nearly one-fourth (23.5%) of children hospitalized at Pediatric Health Information System-participating institutions were identified as meeting at least 1 definition of multisystem complexity. Children with multisystem complexity ranged from 1.0% to 22.1% of hospitalized children, depending on the definition, with 31.2% to 95.9% requiring an ICU stay during their index admission. Differences were seen in demographic, clinical, and resource utilization patterns across the definitions. Definitions of multisystem complexity demonstrated poor agreement (Fleiss' κ 0.21), with 3.5% of identified children meeting all 3. Three definitions of multisystem complexity identified varied populations of children with complex medical needs, with poor overall agreement. Careful consideration is required when applying definitions of medical complexity in health services research, and their lack of concordance should result in caution in the interpretation of research using differing definitions of medical complexity.

Prevalence of Children With Medical Complexity and Associations With Health Care Utilization and In-Hospital Mortality

Children with medical complexity (CMC) have substantial health care needs and frequently experience poor health care quality. Understanding the population prevalence and associated health care needs can inform clinical and public health initiatives. To estimate the prevalence of CMC using open-source pediatric algorithms, evaluate performance of these algorithms in predicting health care utilization and in-hospital mortality, and identify associations between medical complexity as defined by these algorithms and clinical outcomes. This retrospective cohort study used all-payer claims data from Colorado, Massachusetts, and New Hampshire from 2012 through 2017. Children and adolescents younger than 18 years residing in these states were included if they had 12 months or longer of enrollment in a participating health care plan. Analyses were conducted from March 12, 2021, to January 7, 2022. The pediatric Complex Chronic Condition Classification System, Pediatric Medical Complexity Algorithm, and Children With Disabilities Algorithm were applied to 3 years of data to identify children with complex and disabling conditions, first in their original form and then using more conservative criteria that required multiple health care claims or involvement of 3 or more body systems. Primary outcomes, examined over 2 years, included in-hospital mortality and a composite measure of health care services, including specialized therapies, specialized medical equipment, and inpatient care. Outcomes were modeled using logistic regression. Model performance was evaluated using C statistics, sensitivity, and specificity. Of 1 936 957 children, 48.4% were female, 87.8% resided in urban core areas, and 45.1% had government-sponsored insurance as their only primary payer. Depending on the algorithm and coding criteria applied, 0.67% to 11.44% were identified as CMC. All 3 algorithms had adequate discriminative ability, sensitivity, and specificity to predict in-hospital mortality and composite health care services (C statistic = 0.76 [95% CI, 0.73-0.80] to 0.81 [95% CI, 0.78-0.84] for mortality and 0.77 [95% CI, 0.76-0.77] to 0.80 [95% CI, 0.79-0.80] for composite health care services). Across algorithms, CMC had significantly greater odds of mortality (adjusted odds ratio [aOR], 9.97; 95% CI, 7.70-12.89; to aOR, 69.35; 95% CI, 52.52-91.57) and composite health care services (aOR, 4.59; 95% CI, 4.44-4.73; to aOR, 18.87; 95% CI, 17.87-19.93) than children not identified as CMC. In this study, open-source algorithms identified different cohorts of CMC in terms of prevalence and magnitude of risk, but all predicted increased health care utilization and in-hospital mortality. These results can inform research, programs, and policies for CMC.

Patient Characteristics Associated With Missed Appointments in Pediatric Subspecialty Clinics.

Missed appointments negatively affect patients, providers, and health systems. This study aimed to (1) quantify the percentage of missed appointments across 14 pediatric subspecialties in a tertiary-care children's hospital and (2) identify patient characteristics associated with missed appointments in those subspecialties. We extracted patient characteristics from 267,151 outpatient appointments, between January 1, 2013, and December 31, 2018, across 14 subspecialty clinics. Medical complexity was categorized using the Pediatric Medical Complexity Algorithm. The primary outcome was appointment nonattendance. Cancellations, imaging/laboratory visits, patients older than 18 years, and duplicate visits were excluded. Characteristics associated with nonattendance were analyzed with chi-square tests and included in the multivariable model if p < .1. Missing data were addressed using random forest imputation, and assuming data were "missing at random." Variables were considered statistically significant if p < .05. Of the 128,117 scheduled appointments analyzed, 23,204 (18.1%) were missed. In the multivariable model, clinical nutrition had the greatest subspecialty odds of missed appointments, whereas cardiology had the lowest. Patient characteristics most strongly associated with missed appointments were public insurance, history of >2 missed appointments, appointment lead time, lesser medical complexity, Black race/ethnicity, and fewer medications. Clinical characteristics including lesser medical complexity and fewer medications are associated with missed appointments in pediatric subspecialties.

Out-of-Network Care in Commercially Insured Pediatric Patients According to Medical Complexity.

Commercial health plans establish networks and require much higher cost sharing for out-of-network (OON) care. Yet, the adequacy of health plan networks for access to pediatric specialists, especially for children with medical complexity, is largely unknown. To examine differences in OON care and associated cost-sharing payments for commercially insured children with different levels of medical complexity. Cross-sectional study using a nationwide commercial claims database. Enrollees 0-18 years old in employer-sponsored insurance plans. The Pediatric Medical Complexity Algorithm was used to classify individuals into 3 levels of medical complexity: children with no chronic disease, children with non-complex chronic diseases, and children with complex chronic diseases. OON care rates, cost-sharing payments for OON care and in-network care, OON cost sharing as a proportion of total health care spending, and OON cost sharing as a proportion of total cost sharing. The study sample included 6,399,006 individuals with no chronic disease, 1,674,450 with noncomplex chronic diseases, and 603,237 with complex chronic diseases. Children with noncomplex chronic diseases were more likely to encounter OON care by 6.77 percentage points with higher cost-sharing by $288 for OON care, relative to those with no chronic disease. For those with complex chronic diseases, these differences rose to 16.08 percentage points and $599, respectively. Among children who saw behavioral health providers, rates of OON care were especially high. Commercially insured children with medical complexity experience higher rates of OON care with higher OON cost-sharing payments compared with those with no chronic disease.

Connecting to Early Intervention Services After Neonatal Intensive Care Unit Discharge in a Medicaid Sample.

To describe caregiver perspectives regarding connecting to early intervention (EI) services after neonatal intensive care unit discharge in a Medicaid sample. Open-ended semistructured interviews and focus groups were conducted with English- or Spanish-speaking families enrolled in Medicaid in an urban high-risk infant follow-up clinic at a safety-net center, which serves preterm and high-risk term infants. We generated salient themes using inductive-deductive thematic analysis. Thirty-two participants completed the study. The infant's median (interquartile range) birth weight was 1365 (969, 2800) grams; 50% were Hispanic; 31% reported living in a neighborhood with fourth quartile economic hardship. Eighty-one percent were classified as having chronic complex disease per the Pediatric Medical Complexity Algorithm and 63% had a diagnosis of developmental delay. A conceptual model was constructed and the analysis revealed major themes describing families' challenges and ideas to facilitate connection to EI. We identified subthemes related to the person in environment: health care environment/support and socio-economic resources, parent perspectives and built environment; provider level factors such as appointment scheduling, staff limitations, and parent suggestions to improve health care and service navigation, which included improved information sharing, the importance of patient advocates, video resources, early referrals to EI facilitated by the discharging hospital and system workarounds. The results from this study may provide a granular roadmap for providers to help facilitate referrals to EI services. We identified several ideas such as using advocates and providing transitional resources, including online media, that might improve the connection to EI services.

Association Between Neighborhood Disadvantage and Pediatric Readmissions.

Although individual-level social determinants of health (SDH) are known to influence 30-day readmission risk, contextual-level associations with readmission are poorly understood among children. This study explores associations between neighborhood disadvantage measured by Area Deprivation Index (ADI) and pediatric 30-day readmissions. This retrospective cohort study included discharges of patients aged < 20years from Maryland's 2013-2016 all-payer dataset. The ADI, which quantifies 17 indicators of neighborhood socioeconomic disadvantage within census block groups, is used as a proxy for contextual-level SDH. Readmissions were identified with the 30-day Pediatric All-Condition Readmissions measure. Associations between ADI and readmission were identified with generalized estimating equations adjusted for patient demographics and clinical severity (Chronic Condition Indicator [CCI], Pediatric Medical Complexity Algorithm [PMCA], Index Hospital All Patients Refined Diagnosis Related Groups [APR-DRG]), and hospital discharge volume. Discharges (n = 138,998) were mostly female (52.7%), publicly insured (55.1%), urban-dwelling (93.0%), with low clinical severity levels (0-1 CCIs [82.3%], minor APR-DRG severity [48.4%]). Overall readmission rate was 4.0%. Compared to the least disadvantaged ADI quartile, readmissions for the most disadvantaged quartile were significantly more likely (aOR 1.19, 95% CI 1.09-1.30). After adjustment, readmissions were associated with public insurance and indicators of medical complexity (higher number of CCIs, complex-chronic disease PMCA, and APR-DRG severity). In this all-payer, statewide sample, living in the most socioeconomically disadvantaged neighborhoods independently predicted pediatric readmission. While the relative magnitude of neighborhood disadvantage was modest compared to medical complexity, disadvantage is modifiable and thus represents an important consideration for prevention and risk stratification efforts.

1129. Outpatient Prescribing During the COVID-19 Pandemic

BackgroundThe Joint Commission requires ambulatory healthcare systems to collect, analyze and report antimicrobial prescribing data. Duke University Health System (DUHS) piloted a dashboard to capture outpatient prescribing for pediatric patients with URI. Implementation in 2020 allowed for an assessment of antibiotic prescribing during the pandemic.MethodsWe included patients 0 - < 19 years seen at DUHS for URI and pharyngitis from 1/1/2019 -2/21/2021. Patient characteristics included: age, sex, race, ethnicity, Pediatric Medical Complexity Algorithm (PMCA) score and insurance status (public versus private). Provider characteristics included: type (physician, NP, PA) and specialty (pediatrics, family medicine, internal medicine, other). We compared pre- and post-COVID ( March 1, 2020) prescribing and prescribing during telehealth versus in-person visits. A logistic regression model was used to identify factors independently associated with antibiotic prescribing.Results62,447 children were seen during the study period, 29% of whom received an antibiotic. Amoxicillin was the most commonly prescribed antibiotic (64.4%), followed by cefdinir (11%) amoxicillin-clavulanic acid (10%) and azithromycin (8%). Factors associated with antibiotic prescribing are shown in Table 1. White race, private insurance, visits with nurse practitioners and visits with non-pediatric providers were associated with high prescribing. Higher PMCA scores, indicating greater medical complexity, were associated with decreased likelihood of prescribing. Although the total number of outpatient visits plummeted during the COVID period, rates of prescribing only decreased mildly from 31% to 25% (Figure 1).Table 1. Factors Associated with Antibiotic Prescribing in Logistic Regression Model ConclusionOutpatient prescribing was associated with multiple patient and provider characteristics. Similar to other studies, white race, private insurance, and visits with non-physician, non-pediatric providers were associated with antibiotic prescription. Despite a large decrease in the number of outpatient visits during the pandemic, rates of prescribing for URI decreased minimally. A better understanding of factors associated with antibiotic prescribing during the pandemic may identify priority targets for outpatient stewardship as mitigation strategies are relaxed.Disclosures Michael J. Smith, MD, M.S.C.E, Merck (Grant/Research Support)Pfizer (Grant/Research Support)

The Impact of Having a Child With Special Healthcare Needs on Length of Military Service.

In 2010, the National Survey of Children with Special Healthcare Needs revealed that parents of children with special healthcare needs (CSHCN) report employment decisions are influenced by healthcare coverage needs. The U.S. military healthcare system arguably offers service member parents of CSHCN with the most comprehensive, inexpensive, long-term healthcare in the country-potentially increasing their incentive to remain in the military. This study explored the effect of having a CSHCN on the length of parental military service. A retrospective cohort was formed using the Military Health System database from 2008 to 2018. Included children were <10 years in 2010 and received ≥1 year of military healthcare between 2008 and 2010. The Pediatric Medical Complexity Algorithm categorized children as having special healthcare needs via ICD 9/10 codes as having complex chronic (C-CD), non-complex chronic (NC-CD), or no chronic disease (CD). Families were classified by the child with the most complex healthcare need. Duration of military healthcare eligibility measured parental length of service (LOS). ANOVA and linear regression analysis compared LOS by category. Logistic regression determined odds of parental LOS lasting the full 8-year study length. Adjusted analyses controlled for child age and sex, and military parent sex, rank, and marital status. Over 1.45 million children in 915,584 families were categorized as per the algorithm. Of individual children included, 292,050 (20.1%) were CSHCN including those with complex chronic and non-complex chronic conditions. After grouping by family, 80,909 (8.8%) families had a child/children with C-CD (mean LOS 6.39 years), 170,787 (18.7%) families had a child/children with NC-CD (mean LOS 6.41 years), and 663,888 (72.5%) families had children with no CD (mean LOS 5.7 years). In adjusted analysis, parents of children with C-CD and NC-CD served 0.4 [0.37-0.42] and 0.33 [0.31-0.34] years longer than parents of children with no CD; odds of parents serving for the full study period were increased 33% (1.33 [1.31-1.36]) in families of children with C-CD and 27% (1.27 [1.26-1.29]) in families of children with NC-CD. Findings indicate that military parents of CSHCN serve longer military careers than parents of children with no chronic conditions. Continued provision of free, high-quality healthcare coverage for dependent children may be important for service member retention. Retaining trained and experienced service members is key to ensuring a ready and lethal U.S. military.

Oregon’s approach to leveraging system-level data to guide a social determinants of health-informed approach to children’s healthcare

BackgroundChildren’s health and healthcare use are impacted by both medical conditions and social factors, such as their home and community environment. As healthcare systems manage a pediatric population, information about...

Viewpoints from families for improving transition from NICU-to-home for infants with medical complexity at a safety net hospital: a qualitative study

BackgroundWe have limited information on families’ experiences during transition and after discharge from the neonatal intensive care unit.MethodsOpen-ended semi-structured interviews were conducted with English or Spanish- speaking families enrolled in Medicaid in an urban high-risk infant follow up clinic at a safety-net center, which serves preterm and high-risk term infants. We generated salient themes using inductive-deductive thematic analysis.ResultsTwenty-one participants completed the study. The infant’s median (IQR) birth weight was 1750 (1305, 2641) grams; 71% were Hispanic and 10% were Black non-Hispanic; 62% reported living in a neighborhood with 3-4th quartile economic hardship. All were classified as having chronic disease per the Pediatric Medical Complexity Algorithm and 67% had medical complexity. A conceptual model was constructed and the analysis revealed major themes describing families’ challenges and ideas to support transition centered on the parent-child role and parent self-efficacy. The challenges were: (1) comparison to normal babies, (2) caregiver mental health, (3) need for information. Ideas to support transition included, (1) support systems, (2) interventions using mobile health technology (3) improved communication to the primary care provider and (4) information regarding financial assistance programs. Specific subthemes differed in frequency counts between infants with and without medical complexity.ConclusionsFamilies often compare their preterm or high-risk infant to their peers and mothers feel great anxiety and stress. However, families often found hope and resilience in peer support and cited that in addition to information needs, interventions using mobile health technology and transition and financial systems could better support families after discharge.

Care Quality and Spending Among Commercially Insured Children With Disabilities

ObjectiveTo identify opportunities to improve care value for children with disabilities (CWD), we examined CWD prevalence within a commercially insured population and compared outpatient care quality and annual health plan spending levels for CWD relative to children with complex medical conditions without disabilities; children with chronic conditions that are not complex; and children without disabling, complex, or chronic conditions. MethodsThis cross-sectional study comprised 1,118,081 person-years of Blue Cross Blue Shield Massachusetts data for beneficiaries aged 1 to 19years old during 2008 to 2012. We combined the newly developed and validated Children with Disabilities Algorithm with the Pediatric Medical Complexity Algorithm to identify CWD and non-CWD subgroups. We used 14 validated or National Quality Forum–endorsed measures to assess outpatient care quality and paid claims to examine annual plan spending levels and components. ResultsCWD constituted 4.5% of all enrollees. Care quality for CWD was between 11% and 59% for 8 of 14 quality measures and >80% for the 6 remaining measures and was generally comparable to that for non-CWD subgroups. Annual plan spending among CWD was a median and mean 23% and 53% higher than that for children with complex medical conditions without disabilities, respectively; CWD mean and median values were higher than for all other groups as well. ConclusionsCWD were prevalent in our commercially insured population. CWD experienced suboptimal levels of care, but those levels were comparable to non-CWD groups. Improving the care value for CWD involves a deeper understanding of what higher spending delivers and additional aspects of care quality.