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Record W4401342128 · doi:10.1542/peds.2024-067259

Complexity Plus: The Importance of Co-Occurring Conditions in Children With Medical Complexity

2024· letter· en· W4401342128 on OpenAlexaff
Nicolas M. Oreskovic, Eyal Cohen

Bibliographic record

VenuePEDIATRICS · 2024
Typeletter
Languageen
FieldMedicine
TopicInfant Development and Preterm Care
Canadian institutionsHospital for Sick ChildrenUniversity of Toronto
Fundersnot available
KeywordsMedicine

Abstract

fetched live from OpenAlex

In this issues of Pediatrics, Leyenaar and colleagues report results from a retrospective cohort study assessing neurodevelopmental and mental health conditions and health care utilization among children with medical complexity (CMC).1 The authors reviewed all-payer insurance claims data from over 85 000 children ages 3 to 17 years living in 3 states over 5 years and compared rates of co-occurring neurodevelopmental and mental health diagnoses in CMC to those of a comparison group of children without medical complexity, as well as differences in ambulatory clinic visits, emergency department visits, hospitalizations, and in-hospital mortality among CMC with and without these comorbidities. The authors reported that children with medical complexity were 3 times as likely to have a co-occurring neurodevelopmental disorder and twice as likely to have a mental health disorder as children without medical complexity and that these diagnoses were associated with increased utilization of both ambulatory and hospital-based health care services. The study did not find any differences in in-hospital mortality.This important study adds to the growing literature on furthering our understanding of CMC, the unique complexities seen in this population, and the implications for health services delivery and health care policy. CMC represent a small, heterogenous, high-complexity, high-needs population that in recent years has been a focus in pediatric health services research.2 Over the last several decades the number of CMC has increased, along with a growing recognition of the important health and well-being, social, and care-delivery needs and challenges particular to this population.3Although the current study found CMC to have higher rates of emergency and hospital utilization, and prior research has shown that CMC with mental health presenting to the emergency department may result in an increased likelihood of subsequent hospitalization,4 it is not clear whether some of this utilization may be preventable and what the impact of health care spending would be with increased recognition of these conditions and support services for families with CMC.By using all-payer data from several states and limiting the data before the coronavirus disease 2019 pandemic, the study captures broad populations and data while avoiding potential historical confounding because of the amplification of the youth mental health crisis during the pandemic. Nevertheless, given that over 90% of the patients were from urban settings and over 70% from Massachusetts, the population likely largely reflects the greater metropolitan Boston region, and the findings may not be broadly generalizable. Increased medical complexity often means increased engagement with the medical system and a risk of ascertainment bias in the findings, as CMC have more touchpoints with clinicians to ascertain mental health and neurodevelopmental diagnoses. The reported associations also raise important questions about underlying biologic mechanisms driving the associations between the increased co-occurrence of neurodevelopmental and mental health conditions in CMC. Many conditions within CMC classification systems, such as neurologic, metabolic5 and genetic conditions,6 and complex congenital heart disease7 directly affect brain development. For others, genetic or acquired etiologies explaining neuropsychiatric manifestations, including experiences of stress, social inequities, and other factors remains to be elucidated.The United States is suffering from a shortage of pediatric mental health providers and long wait times for services.8 Such issues may be even more important to address in CMC with co-occurring neurodevelopmental or mental health conditions given the high rate of unmet needs in this high-risk population.9 Support for parents and families of CMC is often overlooked but may play an especially important role in CMC with co-occurring conditions, given the increased social and mental health burdens experienced by parents of CMC.10,11Now that the scope of increased risk for co-occurring neurodevelopmental and mental health conditions is becoming more clear, identifying optimal ways to increase support services for CMC and their families should be a central focus of advocacy and policy. Current reimbursement models disincentivize pediatric care teams to assess the need for and provide mental health and developmental supports and services. Creating coordinated complex care delivery models that embed mental health and developmental support services in primary care or during acute hospitalizations could help address such barriers to care. In Massachusetts, recently enacted legislation will help to identify CMC statewide, including those with co-occurring mental health conditions, and their health care utilization patterns—an important first step for screening, quantification, and better needs assessment in this high-risk population.12 The proposed creation of a central database in Massachusetts with tailored performance metrics on frequent barriers in care delivery for CMC, including language, travel distance, wait times, and regional availability of primary and specialty providers, and a dedicated collaborative oversight hub composed of government and nongovernmental agencies to guide and oversee data collection would further help to provide structure to facilitate supporting the care coordination efforts and health care needs of CMC and their families.13 Only through such investments in care or a restructuring of current reimbursement models will children with medical complexity and their families begin to overcome barriers to care and obtain needed resources for addressing the important challenges of co-occurring mental and developmental health conditions.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.012
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.011
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0030.003
Open science0.0010.002
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.037
GPT teacher head0.305
Teacher spread0.268 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreCommentary

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

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