Evidence map›Paper›PMID 31216286›Full record

Observational studyPloS one2019

A challenge to all. A primer on inter-country differences of high-need, high-cost patients.

Marit A C Tanke, Yevgeniy Feyman, Enrique Bernal-Delgado, Sarah R Deeny, Yuichi Imanaka, Patrick Jeurissen, Laura Lange, Alexander Pimperl, Noriko Sasaki, Michael Schull and 3 more

Abstract readMulticenter StudyObservational Study
In one paragraph

Observational study in PloS one, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
28citing papers in PubMed, 2 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

28 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
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  8. Can patient-reported data improve predictions about who will be a high-need, high-cost patient in British Columbia?Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation · 2025
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  10. Multimorbidity Management: A Scoping Review of Interventions and Health Outcomes.International journal of environmental research and public health · 2025
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  16. Observational
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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

13 authors.

Marit A C TankeHarvard T.H. Chan School of Public Health, Boston, Massachusetts, United States of America.ORCID 0000-0002-2105-197X
Yevgeniy FeymanHarvard T.H. Chan School of Public Health, Boston, Massachusetts, United States of America.
Enrique Bernal-DelgadoInstitute for Health Sciences in Aragon, Zaragoza, Aragon, Spain.
Sarah R DeenyThe Health Foundation, London, United Kingdom.
Yuichi ImanakaKyoto University Graduate School of Medicine, Kyoto, Japan.ORCID 0000-0003-4613-2159
Patrick JeurissenRadboudumc, Nijmegen, the Netherlands.
Laura LangeOptiMedis AG, Hamburg, Germany.
Alexander PimperlOptiMedis AG, Hamburg, Germany.
Noriko SasakiKyoto University Graduate School of Medicine, Kyoto, Japan.
Michael SchullSunnybrook Research Institute, Toronto, Ontario, Canada.
Joost J G WammesRadboudumc, Nijmegen, the Netherlands.
Walter P WodchisUniversity of Toronto, Toronto, Ontario, Canada.
Gregg S MeyerPartners Healthcare System, Boston, Massachusetts, United States of America.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAcross countries, a small group of patients accounts for the majority of health care spending. These patients are more likely than other patients to experience problems with quality and safety in their care, suggesting that efforts targeting efficiency and quality among this population might have significant payoffs for health systems. Better understanding of similarities and differences in patient characteristics and health care use in different countries may ultimately inform further efforts to improve care for HNHC patients in these health systems.

methodsWe conducted a cross-sectional descriptive study using one year of patient-level data on high-cost patients in seven high-income OECD member countries. Countries were selected based on availability of detailed information (large enough samples of claims, administrative, and survey data of high-cost patients). We studied concentration of spending among high-cost patients, characteristics of high-cost patients, and per capita spending on high-cost patients.

findingsCost-concentration of the top 5% of patients varied across countries, from 41% in Japan to 60% in Canada, driven primarily by variation in the top 1% of spenders. In general, high-cost patients were more likely to be female (57.7% on average), had a significant number of multi-morbidities (up to on average 10 major diagnostic categories (ICD chapters), and had a lower socioeconomic status. Characteristics of high-cost patients varied as well: median age ranged from 62 in the Netherlands to 75 in Germany and the difference in socioeconomic status is particularly stark in the US. Lastly, utilization, particularly for inpatient care, varied with an average number of inpatient days ranging from 6.6 nights (US) to 97.7 nights in Japan.

interpretationIn this descriptive study, there is substantial variation in the cost concentration, characteristics, and per capita spending on high-cost patient populations across high-income countries. Differences in the way that health systems are structured likely explains some of this variation, which suggests the potential of cross-system learning opportunities. Our findings highlight the need for further studies including comparable performance metrics and institutional analysis.

Indexed as

AgedCosts and Cost AnalysisCross-Sectional StudiesDelivery of Health CareFemaleHumansJapanMaleMiddle AgedQuality of Health CareRetrospective StudiesSpain

Identifiers

PMID31216286
PMCPMC6583982

What OpenQuestion holds

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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.