ArticleScandinavian journal of trauma, resuscitation and emergency medicine2017
Daily volume of cases in emergency call centers: construction and validation of a predictive model.
Article in Scandinavian journal of trauma, resuscitation and emergency medicine, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Impact of two-level filtering organization on population's accessibility to an emergency medical communication centre.BMC emergency medicine · 2025Observational
- Patterns of emergency dispatch calls and their changes during the COVID-19 pandemic in Ulaanbaatar, Mongolia.BMC emergency medicine · 2025Article
- Understanding EMS response times: a machine learning-based analysis.BMC medical informatics and decision making · 2025Article
- Managing High Frequency of Ambulance Calls in Hospitals: A Systematic Review.Risk management and healthcare policy · 2024Review
- Urban-sub-urban-rural variation in the supply and demand of emergency medical services.Frontiers in public health · 2022Article
- Utility of emergency call centre, dispatch and ambulance data for syndromic surveillance of infectious diseases: a scoping review.European journal of public health · 2020Article
- Variation in accessibility of the population to an Emergency Medical Communication Centre: a multicentre observational study.Scandinavian journal of trauma, resuscitation and emergency medicine · 2019Observational
Corrections and comments
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Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundVariations in the activity of emergency dispatch centers are an obstacle to the rationalization of resource allocation. Many explanatory factors are well known, available in advance and could predict the volume of emergency cases. Our objective was to develop and evaluate the performance of a predictive model of daily call center activity.
methodsA retrospective survey was conducted on all cases from 2005 to 2011 in a large medical emergency call center (1,296,153 cases). A generalized additive model of daily cases was calibrated on data from 2005 to 2008 (1461 days, development sample) and applied to the prediction of days from 2009 to 2011 (1095 days, validation sample). Seventeen calendar and epidemiological variables and a periodic function for seasonality were included in the model.
resultsThe average number of cases per day was 507 (95% confidence interval: 500 to 514) (range, 286 to 1251). Factors significantly associated with increased case volume were the annual increase, weekend days, public holidays, regional incidence of influenza in the previous week and regional incidence of gastroenteritis in the previous week. The adjusted R for the model was 0.89 in the calibration sample. The model predicted the actual number of cases within ± 100 for 90.5% of the days, with an average error of -13 cases (95% CI: -17 to 8).
conclusionsA large proportion of the variability of the medical emergency call center's case volume can be predicted using readily available covariates.
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