Evidence map›Paper›PMID 25040848›Full record

ArticleHealth services research2015

Surge capacity: analysis of census fluctuations to estimate the number of intensive care unit beds needed.

Kendiss Olafson, Clare Ramsey, Marina Yogendran, Randall Fransoo, Carla Chrusch, Evelyn Forget, Allan Garland

Abstract readComparative Study
In one paragraph

Article in Health services research, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Critical care bed growth in the United States. A comparison of regional and national trends.American journal of respiratory and critical care medicine · 2015
    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

7 authors.

Kendiss OlafsonSection of Critical Care, Department of Medicine, University of Manitoba, Winnipeg, MB.
Clare Ramsey
Marina Yogendran
Randall Fransoo
Carla Chrusch
Evelyn Forget
Allan Garland

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo compare methods of characterizing intensive care unit (ICU) bed use and estimate the number of beds needed. STUDY

settingThree geographic regions in the Canadian province of Manitoba. STUDY

designRetrospective analysis of population-based data from April 1, 2000, to March 31, 2007.

methodsWe compared three methods to estimate ICU bed requirements. Method 1 analyzed yearly patient-days. Methods 2 and 3 analyzed day-to-day fluctuations in patient census; these differed by whether each hospital needed to independently fulfill its own demand or this resource was shared across hospitals. PRINCIPAL

findingsThree main findings were as follows: (1) estimates based on yearly average usage generally underestimated the number of beds needed compared to analysis of fluctuations in census, especially in the smaller regions where underestimation ranged 25-58 percent; (2) 4-29 percent fewer beds were needed if it was acceptable for demand to exceed supply 18 days/year, versus 4 days/year; and (3) 13-36 percent fewer beds were needed if hospitals within a region could effectively share ICU beds.

conclusionsCompared to using yearly averages, analyzing day-to-day fluctuations in patient census gives a more accurate picture of ICU bed use. Failing to provide adequate "surge capacity" can lead to demand that frequently and severely exceeds supply.

Indexed as

Surge CapacityAdultCensusesHospital Bed CapacityHumansIntensive Care UnitsManitobaResource AllocationRetrospective StudiesYoung Adultbed occupancyCritical careresource allocation

Identifiers

PMID25040848
PMCPMC4319880

What OpenQuestion holds

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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.