Development and Internal Validation of a Multivariable Prediction Model to Predict Repeat Attendances in the Pediatric Emergency Department: A Retrospective Cohort Study.
Pediatr Emerg Care
; 40(1): 16-21, 2024 Jan 01.
Article
em En
| MEDLINE
| ID: mdl-37195679
ABSTRACT
OBJECTIVE:
Unplanned reattendances to the pediatric emergency department (PED) occur commonly in clinical practice. Multiple factors influence the decision to return to care, and understanding risk factors may allow for better design of clinical services. We developed a clinical prediction model to predict return to the PED within 72 hours from the index visit.METHODS:
We retrospectively reviewed all attendances to the PED of Royal Manchester Children's Hospital between 2009 and 2019. Attendances were excluded if they were admitted to hospital, aged older than 16 years or died in the PED. Variables were collected from Electronic Health Records reflecting triage codes. Data were split temporally into a training (80%) set for model development and a test (20%) set for internal validation. We developed the prediction model using LASSO penalized logistic regression.RESULTS:
A total of 308,573 attendances were included in the study. There were 14,276 (4.63%) returns within 72 hours of index visit. The final model had an area under the receiver operating characteristic curve of 0.64 (95% confidence interval, 0.63-0.65) on temporal validation. The calibration of the model was good, although with some evidence of miscalibration at the high extremes of the risk distribution. After-visit diagnoses codes reflecting a nonspecific problem ("unwell child") were more common in children who went on to reattend.CONCLUSIONS:
We developed and internally validated a clinical prediction model for unplanned reattendance to the PED using routinely collected clinical data, including markers of socioeconomic deprivation. This model allows for easy identification of children at the greatest risk of return to PED.
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Modelos Estatísticos
/
Serviço Hospitalar de Emergência
Tipo de estudo:
Etiology_studies
/
Observational_studies
/
Prognostic_studies
/
Risk_factors_studies
Limite:
Aged
/
Child
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Humans
Idioma:
En
Ano de publicação:
2024
Tipo de documento:
Article