Evidence map›Paper›PMID 27613597›Full record

ArticleBMC health services research2016

End of life hospitalisations differ for older Australian women according to death trajectory: a longitudinal data linkage study.

Melissa L Harris, Xenia Dolja-Gore, Hal Kendig, Julie E Byles

Abstract read
In one paragraph

Article in BMC health services research, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Observational
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.

Melissa L HarrisResearch Centre for Generational Health and Ageing, Faculty of Health and Medicine, University of Newcastle, University Drive, Callaghan, NSW, 2308, Australia. Melissa.Harris@newcastle.edu.au.
Xenia Dolja-GoreResearch Centre for Generational Health and Ageing, Faculty of Health and Medicine, University of Newcastle, University Drive, Callaghan, NSW, 2308, Australia.
Hal KendigCentre for Research on Ageing, Health and Wellbeing, College of Medicine, Biology and Environment, Australian National University, Mills Road, Acton, ACT, Australia.
Julie E BylesResearch Centre for Generational Health and Ageing, Faculty of Health and Medicine, University of Newcastle, University Drive, Callaghan, NSW, 2308, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundHospitalisations are the prime contributor to healthcare expenditure, with older adults often identified as high hospital users. Despite the apparent high use of hospitals at the end of life, limited evidence currently exists regarding reasons for hospitalisation. Understanding complex end of life care needs is required for future health care planning as the global population ages. This study aimed to investigate patterns of hospitalisation in the last year of life by cause of death (COD) as well as reasons for admission and short-term predictors of hospital use.

methodsSurvey data from 1,205 decedents from the 1921-1926 cohort of the Australian Longitudinal Study on Women's Health were matched with the state-based hospital records and the National Death Index. Hospital patterns based on COD were graphically summarised and multivariate logistic regression models examined the impact of short-term predictors of length of stay (LOS).

results85 % of women had at least one admission in the last year of life; and 8 % had their first observed admission during this time. Reasons for hospitalisation, timing of admissions and LOS differed by COD. Women who died of cancer, diabetes and 'other' causes were admitted earlier than women who died of organ failure, dementia and influenza. Women who died of organ failure overall spent the longest time in hospital, and women with cancer had the highest median LOS. Longer LOS was associated with previous short- and medium-term- hospitalisations and type of hospital separation.

conclusionsReducing acute care admissions and LOS at the end of life is complex and requires a shift in perceptions and treatment regarding end of life care and chronic disease management.

Indexed as

AdultAgedAged, 80 and overAustraliaChronic DiseaseCritical CareDementiaEpidemiologic MethodsFemaleHospitalizationHospitalsHumansInfluenza, HumanInformation Storage and RetrievalLength of StayMiddle AgedAdmissionsChronic diseaseEnd of lifeHospitalOld ageWomen

Identifiers

PMID27613597
PMCPMC5017050

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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.