Evidence map›Paper›PMID 27508499›Full record

ArticlePloS one2016

Quality Indicators but Not Admission Volumes of Neonatal Intensive Care Units Are Effective in Reducing Mortality Rates of Preterm Infants.

Niels Rochow, Erin Landau-Crangle, Sauyoung Lee, Holger Schünemann, Christoph Fusch

Abstract read
In one paragraph

Article in PloS one, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Article
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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

5 authors.

Niels RochowDivision of Neonatology, Department of Pediatrics, McMaster University, Hamilton, Canada.
Erin Landau-CrangleDivision of Neonatology, Department of Pediatrics, McMaster University, Hamilton, Canada.ORCID http://orcid.org/0000-0003-3512-732X
Sauyoung LeeDivision of Neonatology, Department of Pediatrics, McMaster University, Hamilton, Canada.
Holger SchünemannDepartment of Clinical Epidemiology & Biostatistics, McMaster University, Hamilton, Canada.
Christoph FuschDivision of Neonatology, Department of Pediatrics, McMaster University, Hamilton, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

aimTo investigate how two different strategies to form larger neonatal intensive care units (NICU) impact neonatal mortality rates.

methodsCross-sectional study modeling admission volumes and mortality rates of 177,086 VLBW infants aggregated into 862 NICUs. Cumulative 3-year data was abstracted from Vermont Oxford Network. The model simulated a reduction in number of NICUs by stepwise exclusion using either admission volume (VOL) or quality (QUAL) cut-offs. After randomly redirecting infants of excluded to remaining NICUs resulting system mortality rates were calculated with and without adjusting for effects of experience levels (EL) using published data to reflect effects of different team-to-patient exposure.

resultsThe quality-based strategy is more effective in reducing mortality; while VOL alone was not able to reduce system mortality, QUAL already achieved a 5% improvement after reducing 8% of NICUs and redirecting 6% of infants. Including "EL", a 5% improvement of mortality was achieved by reducing 77% (VOL) vs. 7% (QUAL) of NICUs and redirecting 54% (VOL) vs. 5% (QUAL) of VLBW infants, respectively.

conclusionWhile a critical number of admissions is needed to maintain skills this study emphasizes the importance of including quality parameters to restructure neonatal care. The findings can be generalized to other medical fields.

Indexed as

Infant MortalityInfant, PrematureQuality Indicators, Health CareCross-Sectional StudiesHumansInfantInfant, NewbornInfant, Very Low Birth WeightIntensive Care, NeonatalMortalityPatient AdmissionVermont

Identifiers

PMID27508499
PMCPMC4980039

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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.