Evidence map›Paper›PMID 33059636›Full record

ArticleBMC palliative care2020

Impact on place of death in cancer patients: a causal exploration in southern Switzerland.

Heidi Kern, Giorgio Corani, David Huber, Nicola Vermes, Marco Zaffalon, Marco Varini, Claudia Wenzel, André Fringer

Abstract read
In one paragraph

Article in BMC palliative care, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed, 1 pooled it
–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

8 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Review
  3. Review
  4. Article
  5. Article
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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.

Heidi KernTriangolo Association, In Sceresòra 4, CH-6528, Camorino, Switzerland. heidi.kern@triangolo.ch.ORCID http://orcid.org/0000-0003-0292-2888
Giorgio CoraniIDSIA, Dalle Molle Institute for Artificial Intelligence, Galleria 2, Via Cantonale 2c, CH-6928, Manno, Switzerland.ORCID https://orcid.org/0000-0002-1541-8384
David HuberIDSIA, Dalle Molle Institute for Artificial Intelligence, Galleria 2, Via Cantonale 2c, CH-6928, Manno, Switzerland.ORCID https://orcid.org/0000-0002-2892-7348
Nicola VermesIDSIA, Dalle Molle Institute for Artificial Intelligence, Galleria 2, Via Cantonale 2c, CH-6928, Manno, Switzerland.
Marco ZaffalonIDSIA, Dalle Molle Institute for Artificial Intelligence, Galleria 2, Via Cantonale 2c, CH-6928, Manno, Switzerland.ORCID https://orcid.org/0000-0001-8908-1502
Marco VariniTriangolo Association, In Sceresòra 4, CH-6528, Camorino, Switzerland.
Claudia WenzelDepartment Health Sciences (Institute for Therapeutic Sciences), KREMS, IMC University of Applied Sciences, Piaristengasse 1, A-3500, Krems, Austria.ORCID https://orcid.org/0000-0002-3617-1317
André FringerDepartment Health, Institute of Nursing, Zurich University of Applied Sciences ZHAW, Katharina-Sulzer-Platz 9, Postfach, CH-8401, Winterthur, Switzerland.ORCID https://orcid.org/0000-0003-4950-7788

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMost terminally ill cancer patients prefer to die at home, but a majority die in institutional settings. Research questions about this discrepancy have not been fully answered. This study applies artificial intelligence and machine learning techniques to explore the complex network of factors and the cause-effect relationships affecting the place of death, with the ultimate aim of developing policies favouring home-based end-of-life care.

methodsA data mining algorithm and a causal probabilistic model for data analysis were developed with information derived from expert knowledge that was merged with data from 116 deceased cancer patients in southern Switzerland. This data set was obtained via a retrospective clinical chart review.

resultsDependencies of disease and treatment-related decisions demonstrate an influence on the place of death of 13%. Anticancer treatment in advanced disease prevents or delays communication about the end of life between oncologists, patients and families. Unknown preferences for the place of death represent a great barrier to a home death. A further barrier is the limited availability of family caregivers for terminal home care. The family's preference for the last place of care has a high impact on the place of death of 51%, while the influence of the patient's preference is low, at 14%. Approximately one-third of family systems can be empowered by health care professionals to provide home care through open end-of-life communication and good symptom management. Such intervention has an influence on the place of death of 17%. If families express a convincing preference for home care, the involvement of a specialist palliative home care service can increase the probability of home deaths by 24%.

conclusionConcerning death at home, open communication about death and dying is essential. Furthermore, for the patient preference for home care to be respected, the family's decision for the last place of care seems to be key. The early initiation of family-centred palliative care and the provision of specialist palliative home care for patients who wish to die at home are suggested.

Indexed as

Attitude to DeathAdultAgedAged, 80 and overArtificial IntelligenceData Interpretation, StatisticalData MiningFemaleHome Care ServicesHospitalizationHumansMachine LearningMaleMiddle AgedModels, StatisticalNeoplasmsBayesian classifiersBayesian networksCancerCommunicationCredal networksEnd-of-life careFamily caregiversPalliative home carePatient preferencePlace of death

Identifiers

PMID33059636
PMCPMC7566155

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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.