Evidence map›Paper›PMID 38286888›Full record

Observational studyHealth care management science2024

The potential of patient-based nurse staffing - a queuing theory application in the neonatal intensive care setting.

Sandra Sülz, Andreas Fügener, Michael Becker-Peth, Bernhard Roth

Abstract readObservational Study
In one paragraph

Observational study in Health care management science, 2024. 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. Capacity Planning (Capital, Staff and Costs) of Inpatient Maternity Services: Pitfalls for the Unwary.International journal of environmental research and public health · 2025
    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.

Sandra SülzErasmus School of Health Policy & Management, Burg. Oudlaan 50, 3062 PA, Rotterdam, The Netherlands. sulz@eshpm.eur.nl.ORCID http://orcid.org/0000-0002-2354-1307
Andreas FügenerDepartment of Supply Chain Management & Management Science, University of Cologne, Albertus-Magnus Platz, 50923, Cologne, Germany.ORCID http://orcid.org/0000-0002-4580-7444
Michael Becker-PethRotterdam School of Management, Burg. Oudlaan 50, 3062 PA, Rotterdam, The Netherlands.ORCID http://orcid.org/0000-0002-4496-7702
Bernhard RothDepartment of Neonatology and Paediatric Intensive Care, Children's Hospital, University Hospital Cologne, Kerpener Str. 62, 50937, Cologne, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Faced by a severe shortage of nurses and increasing demand for care, hospitals need to optimally determine their staffing levels. Ideally, nurses should be staffed to those shifts where they generate the highest positive value for the quality of healthcare. This paper develops an approach that identifies the incremental benefit of staffing an additional nurse depending on the patient mix. Based on the reasoning that timely fulfillment of care demand is essential for the healthcare process and its quality in the critical care setting, we propose to measure the incremental benefit of staffing an additional nurse through reductions in time until care arrives (TUCA). We determine TUCA by relying on queuing theory and parametrize the model with real data collected through an observational study. The study indicates that using the TUCA concept and applying queuing theory at the care event level has the potential to improve quality of care for a given nurse capacity by efficiently trading situations of high versus low workload.

Indexed as

Intensive Care Units, NeonatalNursing Staff, HospitalPersonnel Staffing and SchedulingQuality of Health CareWorkloadHumansInfant, NewbornTime FactorsFlexibilityNursing demandOperations managementOperations researchQualityQueuingStaffing

Identifiers

PMID38286888
PMCPMC11637038

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.