Dataset Information

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

ABSTRACT:

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.

SUBMITTER: Fritz CQ

PROVIDER: S-EPMC9254633 | biostudies-literature | 2022 Apr

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

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

Fritz Cristin Q CQ Hall Matt M Bettenhausen Jessica L JL Beck Andrew F AF Krager Molly K MK Freundlich Katherine L KL Ibrahim Dena D Thomson Joanna E JE Gay James C JC Carroll Alison R AR Neeley Maya M Frost Patricia A PA Herndon Alison C AC Kehring Allysa L AL Williams Derek J DJ

Journal of hospital medicine 20220316 4

<h4>Background</h4>Disproportionately high acute care utilization among children with medical complexity (CMC) is influenced by patient-level social complexity.<h4>Objective</h4>The objective of this study was to determine associations between ZIP code-level opportunity and acute care utilization among CMC.<h4>Design, setting, and participants</h4>This cross-sectional, multicenter study used the Pediatric Health Information Systems database, identifying encounters between 2016-2019. CMC aged 28 ...[more]

PMID: 35535923

Similar Datasets

Project description:The need to understand how Community-based disparities impact morbidity and mortality in pediatric critical illness, such as traumatic brain injury. Test the hypothesis that ZIP code-based disparities in hospital utilization, including length of stay (LOS) and hospital costs, exist in a cohort of children with traumatic brain injury (TBI) admitted to a PICU using the Child Opportunity Index (COI).DesignMulticenter retrospective cohort study.SettingPediatric Health Information System (PHIS) database.PatientsChildren 0-18 years old admitted to a PHIS hospital with a diagnosis of TBI from January 2016 to December 2020 requiring PICU care. To identify the most severely injured children, a study-specific definition of "Complicated TBI" was created based on radiology, pharmacy, and procedure codes.InterventionsNone.Main outcomes and measuresUsing nationally normed ZIP code-level COI data, patients were categorized into COI quintiles. A low COI ZIP code has low childhood opportunity based on weighted indicators within educational, health and environmental, and social and economic domains. Population-averaged generalized estimating equation (GEE) models, adjusted for patient and clinical characteristics examined the association between COI and study outcomes, including hospital LOS and accrued hospital costs. The median age of this cohort of 8,055 children was 58 months (interquartile range [IQR], 8-145 mo). There were differences in patient demographics and rates of Complicated TBI between COI levels. The median hospital LOS was 3.0 days (IQR, 2.0-6.0 d) and in population-averaged GEE models, children living in very low COI ZIP codes were expected to have a hospital LOS 10.2% (95% CI, 4.1-16.8%; p = 0.0142) longer than children living in very high COI ZIP codes. For the 11% of children with a Complicated TBI, the relationship between COI and LOS was lost in multivariable models. COI level was not predictive of accrued hospital costs in this study.ConclusionsChildren with TBI requiring PICU care living in low-opportunity ZIP codes have higher injury severity and longer hospital LOS compared with children living in higher-opportunity ZIP codes. Additional studies are needed to understand why these differences exist.

Project description:ImportanceChildren 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.ObjectiveTo 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.Design, setting, and participantsThis 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.ExposuresThe 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.Main outcomes and measuresPrimary 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.ResultsOf 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.Conclusions and relevanceIn 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.

Project description:BackgroundWhile neighborhood conditions have previously been shown to have substantial effects on later occupational, educational and health outcomes, this is the first study to examine the relation between neighborhood factors and attention-deficit/hyperactivity disorder (ADHD) symptoms in children with autism and developmental delays.MethodsChildren from the CHARGE (Childhood Autism Risks from Genetics and the Environment) Study were evaluated at ages 2-5 years and then later in the ReCHARGE (follow-up) Study at ages 8-20 years (mid-childhood/adolescence). Using linear regression, we assessed associations between the Child Opportunity Index 2.0 (COI) at birth, a multidimensional neighborhood measure of childhood opportunity, and ADHD symptoms on the Aberrant Behavior Checklist at mid-childhood/adolescence.ResultsParticipants included a total of 524 youth (401 males; 123 females), composed of 246 autistic children (AUT), 85 children with Developmental Delays (DD) without autism, and 193 Typically Developing (TD) children. Mean age was 3.8 years (SD = 0.79) when evaluated at CHARGE and 13.5 years (SD = 3.69) when evaluated at ReCHARGE. Regression analyses revealed COI at birth significantly predicted ADHD symptoms during mid-childhood/adolescence and early childhood diagnosis modified the COI effect. More specifically, COI significantly predicted ADHD symptoms in the AUT group, but not the TD or DD groups. Additional regression analyses indicated that this interaction was only present in the Social and Economic COI domain. Secondary analyses revealed autistic youth with High and Low Social and Economic COI domain scores had similar levels of ADHD symptoms during early childhood, but by mid-childhood/adolescence, those with low Social and Economic COI domain scores had higher ADHD symptoms.ConclusionsAmong autistic, but not TD or DD youth, poorer neighborhood conditions at birth predict greater ADHD symptoms in later development. These findings have important clinical implications and highlight the need for increased and improved resources in poorer neighborhoods to reduce existing disparities in ADHD, a common neurodevelopmental impairment.

Project description:Care continuity is considered a critical characteristic of high-performing health systems. Few studies have examined the continuity of medication management of complex patients, who often have multiple providers and complex medication regimens.The purpose of this study was to characterize patient factors associated with having more prescribers and the association between number of prescribers and acute care utilization.A retrospective cohort study was conducted of 7,933 Veterans with one to four cardiometabolic conditions (diabetes, hypertension, hyperlipidemia or congestive heart failure) and prescribed medications for these conditions in 2008.The association between number of cardiometabolic conditions and prescribers was modeled using Poisson regression. The number of cardiometabolic conditions and number of prescribers were modeled to predict probability of inpatient admission, probability of emergency room (ER) visits, and number of ER visits among ER users. Demographic characteristics, number of cardiometabolic medications and comorbidities were included as covariates in all models.Patients had more prescribers if they had more cardiometabolic conditions (p < 0.001). The adjusted odds of an ER visit increased with the number of prescribers (two prescribers, Odds Ratio (OR)?= 1.16; three prescribers, OR = 1.21; 4+ prescribers, OR = 1.39), but not with the number of conditions. Among ER users, the number of ER visits was neither associated with the number of prescribers nor the number of conditions. The adjusted odds of an inpatient admission increased with the number of prescribers (two prescribers, OR = 1.27; three prescribers, OR = 1.30; 4+ prescribers, OR = 1.34), but not with the number of conditions.Having more prescribers was associated with greater healthcare utilization for complex patients, despite adjustment for the number of conditions and medications. The number of prescribers may be an appropriate target for reducing acute care utilization by complex patients.

Project description:BackgroundChildren with medical complexity (CMC) are prone to medical errors and longer hospital stays, while residents do not feel prepared to provide adequate medical care for this vulnerable population. No educational guidance for the training of future pediatric tertiary care specialists outside their field of expertise involving the multidisciplinary care of CMC exists. We investigated pediatric residents past educational needs and challenges to identify key learning content for future training involving care for CMC.MethodsThis was a prospective mixed-methods study at a single pediatric tertiary care center. Qualitative semi-structured interviews with residents were conducted, submitted to thematic content analysis, linked to the American Board of Pediatrics (ABP) general pediatrics content outline, and analyzed with importance performance analysis (IPA). Quantitative validation was focused on key themes of pediatric nephrology within the scope of an online survey among pediatric residents and specialists.ResultsA total of 16 interviews, median duration 69 min [interquartile range IQR 35], were conducted. The 280 listed themes of the ABP general pediatrics content outline were reduced to 165 themes, with 86% (theoretical) knowledge, 12% practical skills, and 2% soft skills. IPA identified 23 knowledge themes to be of high importance where improvement is necessary and deemed fruitful. Quantitative validation among 84 residents and specialists (response rate 55%) of key themes in nephrology yielded high agreement among specialists in pediatric nephrology but low interrater agreement among trainees and "trained" non-nephrologists. The occurrence of themes in the qualitative interviews and their calculated importance in the quantitative survey were highly correlated (tau = 0.57, p = 0.001). Two clusters of high importance for other pediatric specialties emerged together with a contextual cluster of frequent encounters in both in- and outpatient care.ConclusionRegarding patient safety, this study revealed the heterogeneous aspects and the importance of training future pediatric tertiary care specialists outside their field of expertise involving the multidisciplinary care of CMC. Our results may lay the groundwork for future detailed analysis and development of training boot camps that might be able to aid the improvement of patient safety by decreasing preventable harm by medical errors, especially for vulnerable patient groups, such as CMC in tertiary care pediatrics.

Project description:BackgroundThe Child Opportunity Index (COI) is a new and innovative tool designed to assess the environment in which children grow up, offering a broad evaluation of the opportunities available to them in different neighborhoods. This initiative aims to ensure improvements in children's living conditions and future health outcomes.MethodsThe study was performed in the cities of Palermo and Rome. Our Italian COI consists of three main domains: education, health and environment, and economy, each subdivided into specific indicators. We collected information, when available, useful for our indicators from institutional sites and municipal archives. Furthermore, in the city of Rome, we distributed a questionnaire through local pediatricians, collecting data in 2 randomly chosen neighborhoods with questions on children's health and quality of life, proposing an initial approach that, when implemented using data provided by the government and public and private health institutions, aims to evaluate the correlation between socio-economic opportunities and the psycho-physical health of children, as demonstrated in the literature.ResultsAs a result, many aspects, such as the rate of air pollution or the illegal occupation of houses, were not taken into consideration. We therefore consider our COI proposal only a starting model that will have to be implemented once all the necessary information has been obtained. However, what can be deduced from this first descriptive study is how the opportunities in different neighborhoods are not the same for all children. The number of educational opportunities as well as the number of environmental opportunities differs between the various districts and is not homogeneous between different cities or within the same city.ConclusionsIn conclusion, it is not simple to analyze in a scientific manner the child's health impact of living in different areas. The COI could be a useful and simple tool that can give us this information. Pediatricians could collaborate with institutions to implement intervention plans and to reduce existing differences, social and health inequalities. Future studies will have to implement this pilot study to create and validate an Italian model of COI to be used as a useful tool in children's assistance.

Dataset Information

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

Background

Objective

Design, setting, and participants

Main outcome and measures

Results

Conclusions

Publications

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

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets