Evidence map›Paper›PMID 37860598›Full record

ArticleHealth systems (Basingstoke, England)2023

Using stochastic simulation modelling to study occupancy levels of decentralised admission avoidance units in Norway.

Meetali Kakad, Martin Utley, Fredrik A Dahl

Abstract read
In one paragraph

Article in Health systems (Basingstoke, England), 2023. 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. 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

3 authors.

Meetali KakadHealth Services Research Unit, Akershus University Hospital Trust, Lørenskog, Norway.ORCID https://orcid.org/0000-0003-1708-0847
Martin UtleyClinical Operational Research Unit, Department of Mathematics, University College London, London, UK.ORCID https://orcid.org/0000-0001-9928-1516
Fredrik A DahlHealth Services Research Unit, Akershus University Hospital Trust, Lørenskog, Norway.ORCID https://orcid.org/0000-0002-6835-0985

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Identifying alternatives to acute hospital admission is a priority for many countries. Over 200 decentralised municipal acute units (MAUs) were established in Norway to divert low-acuity patients away from hospitals. MAUs have faced criticism for low mean occupancy and not relieving pressures on hospitals. We developed a discrete time simulation model of admissions and discharges to MAUs to test scenarios for increasing absolute mean occupancy. We also used the model to estimate the number of patients turned away as historical data was unavailable. Our experiments suggest that mergers alone are unlikely to substantially increase MAU absolute mean occupancy as unmet demand is generally low. However, merging MAUs offers scope for up to 20% reduction in bed capacity, without affecting service provision. Our work has relevance for other admissions avoidance units and provides a method for estimating unconstrained demand for beds in the absence of historical data.

Indexed as

Admission avoidancecommunity-baseddiscrete event simulationErlanghealthcareregression

Identifiers

PMID37860598
PMCPMC10583632

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.