Evidence map›Paper›PMID 31259177›Full record

ArticleKidney diseases (Basel, Switzerland)2019

Association of US Dialysis Facility Staffing with Profiling of Hospital-Wide 30-Day Unplanned Readmission.

Yanjun Chen, Connie Rhee, Damla Senturk, Esra Kurum, Luis Campos, Yihao Li, Kamyar Kalantar-Zadeh, Danh Nguyen

Abstract read
In one paragraph

Article in Kidney diseases (Basel, Switzerland), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

11 citing papers in PubMed.

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  9. Fixed Effects High-Dimensional Profiling Models in Low Information Context.International journal of statistics in medical research · 2021
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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

8 authors.

Yanjun ChenInstitute for Clinical and Translational Science, University of California, Irvine, California, USA.
Connie RheeHarold Simmons Center for Chronic Disease Research and Epidemiology, University of California Irvine School of Medicine, Orange, California, USA.
Damla SenturkDepartment of Biostatistics, University of California, Los Angeles, California, USA.
Esra KurumDepartment of Statistics, University of California, Riverside, California, USA.
Luis CamposDepartment of Statistics, Harvard University, Cambridge, Massachusetts, USA.
Yihao LiDepartment of Biostatistics, University of California, Los Angeles, California, USA.
Kamyar Kalantar-ZadehHarold Simmons Center for Chronic Disease Research and Epidemiology, University of California Irvine School of Medicine, Orange, California, USA.
Danh NguyenDepartment of Medicine, University of California Irvine, Orange, California, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundUnplanned hospital readmissions are a major source of morbidity among dialysis patients, in whom the risk of hospital readmission is exceptionally high. The contribution of dialysis facility staffing to hospital readmission has been largely overlooked.

methodsUsing annual data of dialysis patients from the United States Renal Data System from 2010 to 2013, we assessed dialysis facilities with a significantly worse (SW) and facilities with a nonsignificant (NS) standardized readmission ratio (SRR). SRR estimates were risk adjusted for patient factors, past year comorbidities, and index hospitalization characteristics. Facility staffing variables were compared between 2 exposure groups: facilities with SW and NS SRRs. Four measures of staffing, including patient-to-staffing ratio, were compared between SW and matched NS facilities.

resultsAbout 136,000-148,000 dialysis patients with 269,000-319,000 index hospital discharges were used to identify facilities with SW and facilities with NS SRR annually. Approximately 3-4% of facilities were identified as having SW SRR among > 5,000 facilities annually. The percent of nurses-to-total staff was significantly lower in 2010 for SW facilities than in matched NS facilities (42.5 vs. 45.6%,

conclusionsThis study found that dialysis facilities with SW 30-day readmission rates had lower proportions of nurses-to-total staff and higher patient-to-nurse ratios, but this disparity improved in recent years. Additional research is warranted focusing on how evidence-based staffing at dialysis facilities can contribute to reduction of hospital readmission, and this knowledge is needed to inform clinical practice guidelines and policy decisions regarding optimal dialysis patient staffing.

Indexed as

Dialysis facilityEnd-stage renal diseaseHospital readmissionProfilingStaffing

Identifiers

PMID31259177
PMCPMC6587206

What OpenQuestion holds

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Registered trials

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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.