Evidence map›Paper›PMID 34405278›Full record

ArticleArchives of osteoporosis2021

Examining trajectories of hospital readmission in older adults hospitalised with hip fracture from residential aged care and the community.

Vu Quang Do, Brian Draper, Lara Harvey, Tim Driscoll, Jeffrey Braithwaite, Henry Brodaty, Rebecca Mitchell

Abstract read
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In one paragraph

Article in Archives of osteoporosis, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed, 1 pooled it
0.8field-weighted citation impact, top 27% 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

3 citing papers in PubMed, 1 synthesis or guideline pooled it, 4 citations in OpenAlex.

  1. Pooled it
  2. Group-based trajectories of potentially preventable hospitalisations among older adults after a hip fracture.Osteoporosis international : a journal established as result of cooperation between the European Foundation for Osteoporosis and the National Osteoporosis Foundation of the USA · 2024
    Article
  3. 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 2 institutions in 1 country.

Vu Quang DoAustralian Institute of Health Innovation, Macquarie University, Level 6, 75 Talavera Road, Macquarie Park, NSW, 2109, Australia. vu.do@mq.edu.au.ORCID http://orcid.org/0000-0002-3883-3353
Brian DraperPrince of Wales Clinical School, University of New South Wales, Sydney, Australia.
Lara HarveyCentre for Healthy Brain Ageing, School of Psychiatry, University of New South Wales, Sydney, Australia.
Tim DriscollFalls, Balance and Injury Research Centre, Neuroscience Research Australia, University of New South Wales, Sydney, Australia.
Jeffrey BraithwaiteAustralian Institute of Health Innovation, Macquarie University, Level 6, 75 Talavera Road, Macquarie Park, NSW, 2109, Australia.
Henry BrodatyPrince of Wales Clinical School, University of New South Wales, Sydney, Australia.
Rebecca MitchellAustralian Institute of Health Innovation, Macquarie University, Level 6, 75 Talavera Road, Macquarie Park, NSW, 2109, Australia.
UNSW Sydney · AUMacquarie University · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Hip fracture trajectories have not been examined for older adults in aged care or living in the community. Trajectories of health care use were defined by distinct predictive factors. These results can inform the development of targeted strategies to reduce health service use following hip fracture.

objectiveTo examine hospital service use trajectories of older adults who were hospitalised for hip fracture and living in a residential aged care facility (RACF) or the community, and to identify factors predictive of trajectory group membership. These findings may inform future programmes aimed at reducing unexpected hospitalisations and subsequently reduce health care costs.

methodsA group-based trajectory analysis of hospitalisations was conducted for adults aged ≥ 65 years hospitalised for hip fracture during 2008-2009 in New South Wales, Australia. Linked hospitalisation and RACF data were examined for a 5-year period. Group-based trajectory models were derived for RACF and community-dwelling older adults based on the number of subsequent hospital admissions following the index hip fracture. Multinomial logistic regression examined predictors of trajectory group membership for subsequent hospital admissions.

resultsThere were 5752 hip fracture hospitalisations, with two-thirds of hip fractures occurring in community-dwellers. Key predictors of trajectory group membership for both RACF residents and community-dwellers were age group, sex, hospital length of stay and cognitive impairment. Assistance with activities of daily living and complex health care needs were also predictive of group membership in RACF residents. Location of residence and time to move to a RACF were additional predictors of group membership for community-dwellers.

conclusionHealth service use trajectories differed for RACF residents and community-dwellers; however, there were similar patient characteristics that defined trajectory group membership. Low users of hospital services living in RACFs or the community included older adults with generally unfavourable health conditions, potentially indicating that palliative care or advanced care directives and community-care initiatives, respectively, have played a part in the lowered frequency of rehospitalisation.

Indexed as

Hip FracturesPatient ReadmissionActivities of Daily LivingAgedDelivery of Health CareHospitalizationHumansHip fractureHospitalisationHospital readmissionInjuryResidential aged care

Identifiers

PMID34405278
OpenAlexW3195887862

What OpenQuestion holds

Textmetadata
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.