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Assessing the Coherence of Parents' Short Narratives Regarding their Child Using the Five-Minute Speech Sample Procedure
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Association between child psychiatric emergency room outcomes and dimensions of psychopathology

Thomas H McCoy1, Anna K Wiste2, Alysa E Doyle3

  • 1Center for Quantitative Health, Massachusetts General Hospital, 185 Cambridge Street, Boston, MA 02114, USA; Harvard Medical School, 25 Shattuck Street, Boston, MA 02114, USA; Department of Psychiatry, Massachusetts General Hospital, 55 Fruit Street, Boston, MA 02114, USA.

General Hospital Psychiatry
|April 30, 2019
PubMed

Insights

Dimensional psychopathology in children presenting to the emergency department (ED) impacts care duration. Symptoms of arousal and cognitive function significantly predict longer ED stays and hospital admission likelihood.

Area of Science:

  • Child and Adolescent Psychiatry
  • Emergency Medicine
  • Computational Psychiatry

Background:

  • Emergency departments (EDs) frequently manage children with psychiatric complaints.
  • Predicting ED length of stay and admission is crucial for resource allocation and patient care.
  • Dimensional approaches to psychopathology offer a nuanced understanding beyond diagnostic categories.

Purpose of the Study:

  • To assess if dimensional psychopathology predicts ED length of stay and hospital admission in pediatric psychiatric patients.
  • To explore the utility of the Research Domain Criteria (RDoC) framework in this clinical setting.

Main Methods:

  • Analysis of electronic health records for 3061 children (aged 4-17) evaluated by psychiatry.
  • Utilized natural language processing to estimate RDoC symptom domain scores.
  • Regression models evaluated associations between RDoC scores, length of stay, and admission probability.

Main Results:

  • Higher RDoC arousal, cognitive, positive, and social domain scores correlated with increased ED length of stay.
  • Increased RDoC arousal and cognitive scores raised the odds of hospital admission.
  • Higher RDoC negative domain scores decreased the odds of hospital admission.

Conclusions:

  • Natural language processing-based RDoC scores effectively identify children at higher risk for prolonged ED stays and admission.
  • This in silico approach supports precision psychiatry for pediatric emergency care.
  • Arousal and cognitive symptom dimensions are key predictors of ED outcomes in children.
Abstract

Keywords:
Computed phenotypeElectronic health recordEmergency psychiatryNatural language processingRisk stratification

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