Evidence map›Paper›PMID 35538575›Full record

ArticleBMC health services research2022

Repeat hospital transfers among long stay nursing home residents: a mixed methods analysis of age, race, code status and clinical complexity.

Amy Vogelsmeier, Lori Popejoy, Elizabeth Fritz, Kelli Canada, Bin Ge, Lea Brandt, Marilyn Rantz

Open access · goldAbstract read
In one paragraph

Article in BMC health services research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
1.7field-weighted citation impact, top 16% of its field
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

5 citing papers in PubMed, 6 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Untangling the complex web of avoidable nursing home-to-hospital transfers of residents with dementia.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2024
    Article
  5. 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 at 1 institution in 1 country.

Amy VogelsmeierSinclair School of Nursing, University of Missouri, Columbia, MO, USA. vogelsmeiera@missouri.edu.
Lori PopejoySinclair School of Nursing, University of Missouri, Columbia, MO, USA.
Elizabeth FritzSinclair School of Nursing, University of Missouri, Columbia, MO, USA.
Kelli CanadaSchool of Social Work, University of Missouri, Columbia, MO, USA.
Bin GeSchool of Medicine, University of Missouri, Columbia, MO, USA.
Lea BrandtSchool of Medicine, University of Missouri, Columbia, MO, USA.
Marilyn RantzSinclair School of Nursing, University of Missouri, Columbia, MO, USA.
University of Missouri · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundNursing home residents are at increased risk for hospital transfers resulting in emergency department visits, observation stays, and hospital admissions; transfers that can also result in adverse resident outcomes. Many nursing home to hospital transfers are potentially avoidable. Residents who experience repeat transfers are particularly vulnerable to adverse outcomes, yet characteristics of nursing home residents who experience repeat transfers are poorly understood. Understanding these characteristics more fully will help identify appropriate intervention efforts needed to reduce repeat transfers.

methodsThis is a mixed-methods study using hospital transfer data, collected between 2017 and 2019, from long-stay nursing home residents residing in 16 Midwestern nursing homes who transferred four or more times within a 12-month timeframe. Data were obtained from an acute care transfer tool used in the Missouri Quality Initiative containing closed- and open-ended questions regarding hospital transfers. The Missouri Quality Initiative was a Centers for Medicare and Medicaid demonstration project focused on reducing avoidable hospital transfers for long stay nursing home residents. The purpose of the analysis presented here is to describe characteristics of residents from that project who experienced repeat transfers including resident age, race, and code status. Clinical, resident/family, and organizational factors that influenced transfers were also described.

resultsFindings indicate that younger residents (less than 65 years of age), those who were full-code status, and those who were Black were statistically more likely to experience repeat transfers. Clinical complexity, resident/family requests to transfer, and lack of nursing home resources to manage complex clinical conditions underlie repeat transfers, many of which were considered potentially avoidable.

conclusionsImproved nursing home resources are needed to manage complex conditions in the NH and to help residents and families set realistic goals of care and plan for end of life thus reducing potentially avoidable transfers.

Indexed as

MedicareNursing HomesAgedEmergency Service, HospitalHospitalizationHospitalsHumansPatient TransferUnited StatesAdvanced practice registered nursesHospital transfersNursing home residentsNursing homes

Identifiers

PMID35538575
PMCPMC9087933
OpenAlexW4280500360

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.