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Acad Pediatr. 2018 Apr;18(3):297-304. doi: 10.1016/j.acap.2017.12.012. Epub 2018 Jan 10.

Predicting Low-Resource-Intensity Emergency Department Visits in Children.

Author information

1
Department of Emergency Medicine, Massachusetts General Hospital, Boston, Mass. Electronic address: msamuels-kalow@partners.org.
2
Robert Wood Johnson Foundation Clinical Scholars Program, Yale School of Medicine, New Haven, Conn.
3
Children's Hospital Association, Lenexa, Kans.
4
Division of Emergency Medicine, Department of Pediatrics, Ann and Robert H. Lurie Children's Hospital of Chicago, Northwestern University Feinberg School of Medicine, Chicago, Ill.
5
Section of Pediatric Emergency Medicine, Departments of Pediatrics and Emergency Medicine, Yale School of Medicine, New Haven, Conn.
6
Division of General Pediatrics, Department of Medicine, Boston Children's Hospital, Harvard Medical School, Boston, Mass.
7
Department of Pediatrics, Perelman School of Medicine at the University of Pennsylvania, The Children's Hospital of Philadelphia, Philadelphia, Pa.
8
Children's Health System of Texas, Dallas, Tex; Department of Pediatrics, University of Texas Southwestern, Dallas, Tex.
9
Sections of Pediatric Emergency Medicine and Gastroenterology, Department of Pediatrics, Alberta Children's Hospital, Alberta Children's Hospital Research Institute, Cumming School of Medicine, University of Calgary, Alberta, Canada.
10
Division of Pediatric Medicine, Department of Pediatrics, The Hospital for Sick Children, University of Toronto, Toronto, Ontario, Canada.
11
Division of Emergency Medicine, Departments of Pediatrics and Emergency Medicine, Emory University School of Medicine and Children's Healthcare of Atlanta, Atlanta, Ga.
12
Divisions of Hospital Medicine and Infectious Diseases, Department of Pediatrics, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio.
13
Division of Emergency Medicine, Boston Children's Hospital, Harvard Medical School, Boston, Mass.

Abstract

OBJECTIVES:

Interventions to reduce frequent emergency department (ED) use in children are often limited by the inability to predict future risk. We sought to develop a population-based model for predicting Medicaid-insured children at risk for high frequency (HF) of low-resource-intensity (LRI) ED visits.

METHODS:

We conducted a retrospective cohort analysis of Medicaid-insured children (aged 1-18 years) included in the MarketScan Medicaid database with ≥1 ED visit in 2013. LRI visits were defined as ED encounters with no laboratory testing, imaging, procedures, or hospitalization; and HF as ≥3 LRI ED visits within 365 days of the initial encounter. A generalized linear regression model was derived and validated using a split-sample approach. Validity testing was conducted examining model performance using 3 alternative definitions of LRI.

RESULTS:

Among 743,016 children with ≥1 ED visit in 2013, 5% experienced high-frequency LRI ED use, accounting for 21% of all LRI visits. Prior LRI ED use (2 visits: adjusted odds ratio = 3.5; 95% confidence interval, 3.3, 3.7; and ≥3 visits: adjusted odds ratio = 7.7; 95% confidence interval, 7.3, 8.1) and presence of ≥3 chronic conditions (adjusted odds ratio = 1.7; 95% confidence interval, 1.6, 1.8) were strongly associated with future HF-LRI ED use. A model incorporating patient characteristics and prior ED use predicted future HF-LRI ED utilization with an area under the curve of 0.74.

CONCLUSIONS:

Demographic characteristics and patterns of prior ED use can predict future risk of HF-LRI ED use in the following year. Interventions for reducing low-value ED use in these high-risk children should be considered.

KEYWORDS:

emergency medicine; pediatrics; predictive model; utilization

PMID:
29331346
DOI:
10.1016/j.acap.2017.12.012

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