Predicting Low-Resource-Intensity Emergency Department Visits in Children

Margaret Samuels-Kalow, Alon Peltz, Jonathan Rodean, Matthew Hall, Elizabeth R. Alpern, Paul L. Aronson, Jay G. Berry, Kathy N. Shaw, Rustin B. Morse, Stephen B. Freedman, Eyal Cohen, Harold K. Simon, Samir S. Shah, Yiannis Katsogridakis, Mark I. Neuman

Research output: Contribution to journalArticle

1 Citation (Scopus)

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.

Original languageEnglish (US)
JournalAcademic Pediatrics
DOIs
StateAccepted/In press - Jan 1 2018

Fingerprint

Hospital Emergency Service
Medicaid
Odds Ratio
Confidence Intervals
Linear Models
Area Under Curve
Hospitalization
Cohort Studies
Demography
Databases

Keywords

  • Emergency medicine
  • Pediatrics
  • Predictive model
  • Utilization

ASJC Scopus subject areas

  • Pediatrics, Perinatology, and Child Health

Cite this

Samuels-Kalow, M., Peltz, A., Rodean, J., Hall, M., Alpern, E. R., Aronson, P. L., ... Neuman, M. I. (Accepted/In press). Predicting Low-Resource-Intensity Emergency Department Visits in Children. Academic Pediatrics. https://doi.org/10.1016/j.acap.2017.12.012

Predicting Low-Resource-Intensity Emergency Department Visits in Children. / Samuels-Kalow, Margaret; Peltz, Alon; Rodean, Jonathan; Hall, Matthew; Alpern, Elizabeth R.; Aronson, Paul L.; Berry, Jay G.; Shaw, Kathy N.; Morse, Rustin B.; Freedman, Stephen B.; Cohen, Eyal; Simon, Harold K.; Shah, Samir S.; Katsogridakis, Yiannis; Neuman, Mark I.

In: Academic Pediatrics, 01.01.2018.

Research output: Contribution to journalArticle

Samuels-Kalow, M, Peltz, A, Rodean, J, Hall, M, Alpern, ER, Aronson, PL, Berry, JG, Shaw, KN, Morse, RB, Freedman, SB, Cohen, E, Simon, HK, Shah, SS, Katsogridakis, Y & Neuman, MI 2018, 'Predicting Low-Resource-Intensity Emergency Department Visits in Children', Academic Pediatrics. https://doi.org/10.1016/j.acap.2017.12.012
Samuels-Kalow, Margaret ; Peltz, Alon ; Rodean, Jonathan ; Hall, Matthew ; Alpern, Elizabeth R. ; Aronson, Paul L. ; Berry, Jay G. ; Shaw, Kathy N. ; Morse, Rustin B. ; Freedman, Stephen B. ; Cohen, Eyal ; Simon, Harold K. ; Shah, Samir S. ; Katsogridakis, Yiannis ; Neuman, Mark I. / Predicting Low-Resource-Intensity Emergency Department Visits in Children. In: Academic Pediatrics. 2018.
@article{652ffd60f707469ca52afa34a59a444f,
title = "Predicting Low-Resource-Intensity Emergency Department Visits in Children",
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",
author = "Margaret Samuels-Kalow and Alon Peltz and Jonathan Rodean and Matthew Hall and Alpern, {Elizabeth R.} and Aronson, {Paul L.} and Berry, {Jay G.} and Shaw, {Kathy N.} and Morse, {Rustin B.} and Freedman, {Stephen B.} and Eyal Cohen and Simon, {Harold K.} and Shah, {Samir S.} and Yiannis Katsogridakis and Neuman, {Mark I.}",
year = "2018",
month = "1",
day = "1",
doi = "10.1016/j.acap.2017.12.012",
language = "English (US)",
journal = "Academic Pediatrics",
issn = "1876-2859",
publisher = "Elsevier Inc.",

}

TY - JOUR

T1 - Predicting Low-Resource-Intensity Emergency Department Visits in Children

AU - Samuels-Kalow, Margaret

AU - Peltz, Alon

AU - Rodean, Jonathan

AU - Hall, Matthew

AU - Alpern, Elizabeth R.

AU - Aronson, Paul L.

AU - Berry, Jay G.

AU - Shaw, Kathy N.

AU - Morse, Rustin B.

AU - Freedman, Stephen B.

AU - Cohen, Eyal

AU - Simon, Harold K.

AU - Shah, Samir S.

AU - Katsogridakis, Yiannis

AU - Neuman, Mark I.

PY - 2018/1/1

Y1 - 2018/1/1

N2 - 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.

AB - 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.

KW - Emergency medicine

KW - Pediatrics

KW - Predictive model

KW - Utilization

UR - http://www.scopus.com/inward/record.url?scp=85042494659&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85042494659&partnerID=8YFLogxK

U2 - 10.1016/j.acap.2017.12.012

DO - 10.1016/j.acap.2017.12.012

M3 - Article

C2 - 29331346

AN - SCOPUS:85042494659

JO - Academic Pediatrics

JF - Academic Pediatrics

SN - 1876-2859

ER -