Evidence map›Paper›PMID 27662830›Full record

ArticleBMC palliative care2016

Dying among older adults in Switzerland: who dies in hospital, who dies in a nursing home?

Xhyljeta Luta, Radoslaw Panczak, Maud Maessen, Matthias Egger, David C Goodman, Marcel Zwahlen, Andreas E Stuck, Kerri Clough-Gorr

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in BMC palliative care, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed, 1 pooled it
2.1field-weighted citation impact, top 11% 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

10 citing papers in PubMed, 1 synthesis or guideline pooled it, 15 citations in OpenAlex.

  1. Pooled it
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  5. Review
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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 at 5 institutions in 2 countries.

Xhyljeta LutaInstitute of Social and Preventive Medicine, University of Bern, Finkeubelweg 11, CH-3012, Bern, Switzerland.
Radoslaw PanczakInstitute of Social and Preventive Medicine, University of Bern, Finkeubelweg 11, CH-3012, Bern, Switzerland.
Maud MaessenInstitute of Social and Preventive Medicine, University of Bern, Finkeubelweg 11, CH-3012, Bern, Switzerland.
Matthias EggerInstitute of Social and Preventive Medicine, University of Bern, Finkeubelweg 11, CH-3012, Bern, Switzerland.
David C GoodmanInstitute of Social and Preventive Medicine, University of Bern, Finkeubelweg 11, CH-3012, Bern, Switzerland.
Marcel ZwahlenInstitute of Social and Preventive Medicine, University of Bern, Finkeubelweg 11, CH-3012, Bern, Switzerland.
Andreas E StuckInstitute of Social and Preventive Medicine, University of Bern, Finkeubelweg 11, CH-3012, Bern, Switzerland.
Kerri Clough-GorrInstitute of Social and Preventive Medicine, University of Bern, Finkeubelweg 11, CH-3012, Bern, Switzerland. kerri.clough@ispm.unibe.ch.
University of Bern · CHInstitute of Social and Preventive Medicine · CHBoston University · USDartmouth Institute for Health Policy and Clinical Practice · USUniversity Hospital of Bern · CH

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundInstitutional deaths (hospitals and nursing homes) are an important issue because they are often at odds with patient preference and associated with high healthcare costs. The aim of this study was to examine deaths in institutions and the role of individual, regional, and healthcare supply characteristics in explaining variation across Swiss Hospital Service Areas (HSAs).

methodsRetrospective study of individuals ≥66 years old who died in a Swiss institution (hospital or nursing homes) in 2010. Using a two-level logistic regression analysis we examined the amount of variation across HSAs adjusting for individual, regional and healthcare supply measures. The outcome was place of death, defined as death in hospital or nursing homes.

resultsIn 2010, 41,275 individuals ≥66 years old died in a Swiss institution; 54 % in nursing homes and 46 % in hospitals. The probability of dying in hospital decreased with increasing age. The OR was 0.07 (95 % CI: 0.05-0.07) for age 91+ years compared to those 66-70 years. Living in peri-urban areas (OR = 1.06 95 % CI: 1.00-1.11) and French speaking region (OR = 1.43 95 % CI: 1.22-1.65) was associated with higher probability of hospital death. Females had lower probability of death in hospital (OR = 0.54 95 % CI: 0.51-0.56). The density of ambulatory care physicians (OR = 0.81 95 % CI: 0.67-0.97) and nursing homes beds (OR = 0.67 95 % CI: 0.56-0.79) was negatively associated with hospital death. The proportion of dying in hospital varied from 38 % in HSAs with lowest proportion of hospital deaths to 60 % in HSAs with highest proportion of hospital deaths (1.6-fold variation).

conclusionsWe found evidence for variation across regions in Switzerland in dying in hospital versus nursing homes, indicating possible overuse and underuse of end of life (EOL) services.

Indexed as

End of lifeHospital service areasInstitutional deathsSmall area analysisSwitzerlandVariation

Identifiers

PMID27662830
PMCPMC5035491
OpenAlexW2521636139

What OpenQuestion holds

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LicenceCC BY
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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.