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Pediatric Emergency Assessment Tool (PEAT): A Risk‐adjustment Measure for Pediatric Emergency Patients
Author(s) -
Gorelick Marc H.,
Lee Chistopher,
Cronan Kathleen,
Kost Susanne,
Palmer Kathleen
Publication year - 2001
Publication title -
academic emergency medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.221
H-Index - 124
eISSN - 1553-2712
pISSN - 1069-6563
DOI - 10.1111/j.1553-2712.2001.tb01281.x
Subject(s) - medicine , triage , emergency department , logistic regression , emergency medicine , medical record , receiver operating characteristic , multinomial logistic regression , statistics , mathematics , psychiatry
.Objective: To develop a multivariable model predicting the level of care required by pediatric patients for use as a risk‐adjustment tool in the evaluation of emergency medical services for children. Methods: A random 10% sample of records of all visits over a 12‐month period to a suburban, university‐affiliated pediatric emergency department (PED) was selected and abstracted. The outcome variable, level of care received, was categorized in three levels: routine care only (R); diagnostic or therapeutic procedures performed in the ED but patient not admitted (EDT); and admission to hospital (ADM). Predictor variables included information routinely elicited and recorded at the time of triage. Using multinomial logistic regression, a predictive model was derived from a subset of 70% of the selected visits, and was validated in the remaining 30%. Results: The total sample included 2,287 visits. The overall rate of each outcome was R‐37%, EDT‐53%, and ADM‐10%. The final regression model included the following predictors significantly associated with the outcome: age, past medical history, temperature, abnormal respiratory rate or pulse oximetry in triage, chief complaint, and triage level (model likelihood ratio chi‐square, 14 df = 332, p < 0.00001, R 2 = 0.14). The number of outcomes was well predicted by the model in both subsamples. Analysis of variance showed a significant association between Pediatric Emergency Assessment Tool (PEAT) score (weighted sum of the predicted probabilities of EDT and ADM) and both ED charges and time spent in the ED (p < 0.001). Conclusions: A model based on easily and routinely measured variables can accurately predict the level of care rendered in the PED. The predicted probabilities from such a model correlate well with other outcomes of care and may be useful in adjusting for differences in risk when evaluating quality of care.