Mathias Wargon1,2, Dominique Brun-Ney3,4, Laure Beaujouan3,4, Enrique Casalino2,5,6. 1. Hospital Saint Camille, Emergency Department, Bry Sur Marne, France. 2. Study Group on Efficiency and Quality in non-scheduled activities, Paris, France. 3. Medical Organisation Department - Emergencies and Intensive Cares, Assistance Publique-Hôpitaux de Paris, Paris, France. 4. Regional Center of Watchfulness and Action Paris Area Assistance Publique-Hôpitaux de Paris, Paris, France. 5. Hôpital Bichat-Claude Bernard, Emergency Department, Assistance Publique-Hôpitaux de Paris, Paris, France. 6. UA 7335 REMES, Paris Diderot University, Sorbonne Paris Cité, Paris, France.
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.
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.
Authors: Roger A Morbey; Andre Charlett; Iain Lake; James Mapstone; Richard Pebody; James Sedgwick; Gillian E Smith; Alex J Elliot Journal: PLoS One Date: 2020-02-10 Impact factor: 3.240