No more winter crisis? Forecasting daily bed requirements for emergency department admissions to hospital

Eur J Emerg Med. 2018 Aug;25(4):250-256. doi: 10.1097/MEJ.0000000000000451.

Abstract

Study hypothesis: We hypothesized that age, calendar variables, and clinical influenza epidemics may have an impact on the number of daily through-emergency department (ED) hospitalizations. The aim of our study was to elaborate a pragmatic tool to predict the daily number of through-ED hospitalizations.

Methods: We carried out a prospective-observational study including data from 18 ED located in the Paris metropolitan area. Daily through-ED hospitalizations numbers from 2007 to 2010 were modelized to forecast the year 2011 using a general linear model by age groups (<75-years; ≥75-years) using calendar variables and influenza epidemics as explanatory variables. Lower and higher limits forecast with the 95% confidence interval of each explanatory variable were calculated.

Results: 2 741 974 ED visits and 518 857 through-ED hospitalizations were included. We found a negative trend (-2.7%) for hospitalization visits among patients less than 75 years of age and an increased trend (+6.2%) for patients of at least 75 years of age. Calendar variables were predictors for daily hospitalizations for both age groups. Influenza epidemic period was not a predictor for hospitalizations in patients less than 75 years of age; among patients of at least 75 years of age, significant value was found only in models excluding months. When forecasting hospitalizations, 70% for patients less than 75 years of age and 66.8% for patients of at least 75 years of age of daily predicted values were included in the forecast limits.

Conclusion: Daily number of emergency hospitalizations could be predicted on a regional basis using calendar variables with a low level of error. Forecasting through-ED hospitalizations requires to differentiate between elderly and younger patients, with a low impact of influenza epidemic periods in elders and absent in youngest patients.

Publication types

  • Observational Study

MeSH terms

  • Adolescent
  • Adult
  • Aged
  • Confidence Intervals
  • Delivery of Health Care / organization & administration*
  • Emergency Service, Hospital / statistics & numerical data*
  • Female
  • Forecasting
  • France
  • Hospital Bed Capacity / statistics & numerical data*
  • Hospitalization / statistics & numerical data*
  • Humans
  • Influenza, Human / epidemiology*
  • Influenza, Human / therapy
  • Male
  • Middle Aged
  • Prospective Studies
  • Seasons*
  • Young Adult