Evidence map›Paper›PMID 29540161›Full record

ArticleBMC health services research2018

Death at no cost? Persons with no health insurance claims in the last year of life in Switzerland.

Radoslaw Panczak, Viktor von Wyl, Oliver Reich, Xhyljeta Luta, Maud Maessen, Andreas E Stuck, Claudia Berlin, Kurt Schmidlin, David C Goodman, Matthias Egger and 2 more

Abstract read
In one paragraph

Article in BMC health services research, 2018. 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. 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

12 authors.

Radoslaw PanczakInstitute of Social and Preventive Medicine, University of Bern, Finkenhubelweg 11, 3012, Bern, Switzerland. r.panczak@gmail.com.ORCID 0000-0001-5141-683X
Viktor von WylEpidemiology, Biostatistics & Prevention Institute, University of Zürich, Hirschengraben 84, 8001, Zurich, Switzerland.
Oliver ReichDepartment of Health Sciences, Helsana Insurance Group, Palmstrasse 26b, 8401, Winterthur, Switzerland.
Xhyljeta LutaInstitute of Social and Preventive Medicine, University of Bern, Finkenhubelweg 11, 3012, Bern, Switzerland.
Maud MaessenInstitute of Social and Preventive Medicine, University of Bern, Finkenhubelweg 11, 3012, Bern, Switzerland.
Andreas E StuckDepartment of Geriatrics, Inselspital, Bern University Hospital, and University of Bern, Freiburgstrasse, 3010, Bern, Switzerland.
Claudia BerlinInstitute of Social and Preventive Medicine, University of Bern, Finkenhubelweg 11, 3012, Bern, Switzerland.
Kurt SchmidlinInstitute of Social and Preventive Medicine, University of Bern, Finkenhubelweg 11, 3012, Bern, Switzerland.
David C GoodmanInstitute of Social and Preventive Medicine, University of Bern, Finkenhubelweg 11, 3012, Bern, Switzerland.
Matthias EggerInstitute of Social and Preventive Medicine, University of Bern, Finkenhubelweg 11, 3012, Bern, Switzerland.
Kerri Clough-GorrInstitute of Social and Preventive Medicine, University of Bern, Finkenhubelweg 11, 3012, Bern, Switzerland.
Marcel ZwahlenInstitute of Social and Preventive Medicine, University of Bern, Finkenhubelweg 11, 3012, Bern, Switzerland.

Funding

Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung 406740_1393333
6 · The paper itself

Abstract

backgroundLack of health insurance claims (HIC) in the last year of life might indicate suboptimal end-of-life care, but reasons for no HIC are not fully understood because information on causes of death is often missing. We investigated association of no HIC with characteristics of individuals and their place of residence.

methodsWe analysed HIC of persons who died between 2008 and 2010, which were obtained from six providers of mandatory Swiss health insurance. We probabilistically linked these persons to death certificates to get cause of death information and analysed data using sex-stratified, multivariable logistic regression. Supplementary analyses looked at selected subgroups of persons according to the primary cause of death.

resultsThe study population included 113,277 persons (46% males). Among these persons, 1199 (proportion 0.022, 95% CI: 0.021-0.024) males and 803 (0.013, 95% CI: 0.012-0.014) females had no HIC during the last year of life. We found sociodemographic and health differentials in the lack of HIC at the last year of life among these 2002 persons. The likelihood of having no HIC decreased steeply with older age. Those who died of cancer were more likely to have HIC (adjusted odds ratio for males 0.17, 95% CI: 0.13-0.22; females 0.19, 95% CI: 0.12-0.28) whereas those dying of mental and behavioural disorders (AOR males 1.83, 95% CI:1.42-2.37; females 1.65, 95% CI: 1.27-2.14), and males dying of suicide (AOR 2.15, 95% CI: 1.72-2.69) and accidents (AOR 2.41, 95% CI: 1.96-2.97) were more likely to have none. Single, widowed, and divorced persons also were more likely to have no HIC (AORs in range of 1.29-1.80). There was little or no association between the lack of HIC and characteristics of region of residence. Patterns of no HIC differed across main causes of death. Associations with age and civil status differed in particular for persons who died of cancer, suicide, accidents and assaults, and mental and behavioural disorders.

conclusionsParticular groups might be more likely to not seek care or not report health insurance costs to insurers. Researchers should be aware of this aspect of health insurance data and account for persons who lack HIC.

Indexed as

AdultAgedFemaleHealth ExpendituresHealth Services ResearchHumansInsurance Claim ReviewMaleMiddle AgedSwitzerlandTerminal CareDelivery of health careEnd-of-lifeHealth care costHealth insuranceSwitzerland

Identifiers

PMID29540161
PMCPMC5853076

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.