Evidence map›Paper›PMID 33506300›Full record

ArticleJournal of medical systems2021

Forecasting the Patients Flow at Pediatric Emergency Departments.

Thomas Morzadec, Hélène Chappuy, Naïm Bouazza, Saïk Urien, Jean-Marc Treluyer, Frantz Foissac, Nathanaël Beeker

Abstract read
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Article in Journal of medical systems, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Thomas MorzadecPharmacology and Drug Evaluation in Children and Pregnant Women EA7323, Université de Paris, Paris, France. thomas.morzadec@protonmail.com.ORCID http://orcid.org/0000-0003-1631-5421
Hélène ChappuyPharmacology and Drug Evaluation in Children and Pregnant Women EA7323, Université de Paris, Paris, France.
Naïm BouazzaPharmacology and Drug Evaluation in Children and Pregnant Women EA7323, Université de Paris, Paris, France.
Saïk UrienPharmacology and Drug Evaluation in Children and Pregnant Women EA7323, Université de Paris, Paris, France.
Jean-Marc TreluyerPharmacology and Drug Evaluation in Children and Pregnant Women EA7323, Université de Paris, Paris, France.
Frantz FoissacPharmacology and Drug Evaluation in Children and Pregnant Women EA7323, Université de Paris, Paris, France.
Nathanaël BeekerPharmacology and Drug Evaluation in Children and Pregnant Women EA7323, Université de Paris, Paris, France.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Emergency departments (EDs) have a key role in the public health system. They are facing a constant growth of their volume. Forecasting the daily volume is a major tool to adapt the allocation of resources. In this paper, we focus on pediatric EDs. They are specific by their strong seasonal variation, determined by the academic pace. The main contribution of this paper is to integrate the effects of this pace to the annual seasonality. We also tried out to improve the daily forecasting by forecasting the week means of the flow first. We trained and tested these models specifically on the pediatric EDs of Paris university hospital trust. For the eight pediatric EDs gathered, on average for the years 2016 to 2019, we forecasted the daily volume with a Mean Absolute Percentage Error (MAPE) of 6.6% for a 7-days forecasting, 7.1% for a 14-days forecasting and 7.6% for a 28-days forecasting. Account of rhythm allows a performance increase, with results respectively 7%, 10.1% and 8.4% better relatively to a baseline model based on a periodic regression on the weeks.

Indexed as

Emergency Service, HospitalChildForecastingHospitals, UniversityHumansEmergency departmentFlowForecastingPediatrics

Identifiers

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.