Evidence map›Paper›PMID 34255237›Full record

ArticleHealth care management science2022

Enhanced coverage by integrating site interdependencies in capacitated EMS location models.

Matthias Grot, Tristan Becker, Pia Mareike Steenweg, Brigitte Werners

Abstract read
In one paragraph

Article in Health care management science, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Ahead of the ambulance: Optimizing volunteer training.Health care management science · 2026
    Article
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

4 authors.

Matthias GrotInstitute of Management ifu, Ruhr University Bochum, Universitätsstraße 150, 44801, Bochum, Germany. matthias.grot@rub.de.ORCID http://orcid.org/0000-0002-4467-0044
Tristan BeckerChair of Operations Management, RWTH Aachen University, Kackertstr. 7, 52072, Aachen, Germany.
Pia Mareike SteenwegInstitute of Management ifu, Ruhr University Bochum, Universitätsstraße 150, 44801, Bochum, Germany.
Brigitte WernersInstitute of Management ifu, Ruhr University Bochum, Universitätsstraße 150, 44801, Bochum, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In order to allocate limited resources in emergency medical services (EMS) networks, mathematical models are used to select sites and their capacities. Many existing standard models are based on simplifying assumptions, including site independency and a similar system-wide busyness of ambulances. In practice, when a site is busy, a call is forwarded to another site. Thus, the busyness of each site depends not only on the rate of calls in the surrounding area, but also on interactions with other facilities. If the demand varies across the urban area, assuming an average system-wide server busy fraction may lead to an overestimation of the actual coverage. We show that site interdependencies can be integrated into the well-known Maximum Expected Covering Location Problem (MEXCLP) by introducing an upper bound for the busyness of each site. We apply our new mathematical formulation to the case of a local EMS provider. To evaluate the solution quality, we use a discrete event simulation based on anonymized real-world call data. Results of our simulation-optimization approach indicate that the coverage can be improved in most cases by taking site interdependencies into account, leading to an improved ambulance allocation and a faster emergency care.

Indexed as

AmbulancesEmergency Medical ServicesComputer SimulationHumansModels, TheoreticalBusy fractionEmergency medical servicesFacility locationOperations ResearchSite interdependency

Identifiers

PMID34255237
PMCPMC8983527

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

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.