Evidence map›Paper›PMID 37580711›Full record

ArticleBMC medicine2023

Healthcare fragmentation, multimorbidity, potentially inappropriate medication, and mortality: a Danish nationwide cohort study.

Anders Prior, Claus Høstrup Vestergaard, Peter Vedsted, Susan M Smith, Line Flytkjær Virgilsen, Linda Aagaard Rasmussen, Morten Fenger-Grøn

Abstract read
In one paragraph

Article in BMC medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 100 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
100citing papers in PubMed, 3 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

100 citing papers in PubMed, 3 syntheses or guidelines pooled it.

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  19. From Integrated Care to Learning Systems.Healthcare (Basel, Switzerland) · 2026
    Review
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40 more citing papers are in PubMed but not listed here.

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

7 authors.

Anders PriorResearch Unit for General Practice, Bartholins Allé 2, 8000, Aarhus C, Denmark. anders.prior@ph.au.dk.ORCID http://orcid.org/0000-0003-4053-3701
Claus Høstrup VestergaardResearch Unit for General Practice, Bartholins Allé 2, 8000, Aarhus C, Denmark.ORCID http://orcid.org/0000-0003-2916-1548
Peter VedstedResearch Unit for General Practice, Bartholins Allé 2, 8000, Aarhus C, Denmark.ORCID http://orcid.org/0000-0003-2113-5599
Susan M SmithDiscipline of Public Health and Primary Care, Trinity College, University of Dublin, Dublin, Ireland.ORCID http://orcid.org/0000-0001-6027-2727
Line Flytkjær VirgilsenResearch Unit for General Practice, Bartholins Allé 2, 8000, Aarhus C, Denmark.ORCID http://orcid.org/0000-0002-4877-2697
Linda Aagaard RasmussenResearch Unit for General Practice, Bartholins Allé 2, 8000, Aarhus C, Denmark.ORCID http://orcid.org/0000-0002-9753-2008
Morten Fenger-GrønResearch Unit for General Practice, Bartholins Allé 2, 8000, Aarhus C, Denmark.ORCID http://orcid.org/0000-0002-6354-5871

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPatients with multimorbidity are frequent users of healthcare, but fragmented care may lead to suboptimal treatment. Yet, this has never been examined across healthcare sectors on a national scale. We aimed to quantify care fragmentation using various measures and to analyze the associations with patient outcomes.

methodsWe conducted a register-based nationwide cohort study with 4.7 million Danish adult citizens. All healthcare contacts to primary care and hospitals during 2018 were recorded. Clinical fragmentation indicators included number of healthcare contacts, involved providers, provider transitions, and hospital trajectories. Formal fragmentation indices assessed care concentration, dispersion, and contact sequence. The patient outcomes were potentially inappropriate medication and all-cause mortality adjusted for demographics, socioeconomic factors, and morbidity level.

resultsThe number of involved healthcare providers, provider transitions, and hospital trajectories rose with increasing morbidity levels. Patients with 3 versus 6 conditions had a mean of 4.0 versus 6.9 involved providers and 6.6 versus 13.7 provider transitions. The proportion of contacts to the patient's own general practice remained stable across morbidity levels. High levels of care fragmentation were associated with higher rates of potentially inappropriate medication and increased mortality on all fragmentation measures after adjusting for demographic characteristics, socioeconomic factors, and morbidity. The strongest associations with potentially inappropriate medication and mortality were found for ≥ 20 contacts versus none (incidence rate ratio 2.83, 95% CI 2.77-2.90) and ≥ 20 hospital trajectories versus none (hazard ratio 10.8, 95% CI 9.48-12.4), respectively. Having less than 25% of contacts with your usual provider was associated with an incidence rate ratio of potentially inappropriate medication of 1.49 (95% CI 1.40-1.58) and a mortality hazard ratio of 2.59 (95% CI 2.36-2.84) compared with full continuity. For the associations between fragmentation measures and patient outcomes, there were no clear interactions with number of conditions.

conclusionsSeveral clinical indicators of care fragmentation were associated with morbidity level. Care fragmentation was associated with higher rates of potentially inappropriate medication and increased mortality even when adjusting for the most important confounders. Frequent contact to the usual provider, fewer transitions, and better coordination were associated with better patient outcomes regardless of morbidity level.

Indexed as

MultimorbidityPotentially Inappropriate Medication ListAdultCohort StudiesDelivery of Health CareDenmarkHumansContinuity of careFragmentationHealthcare utilizationMultimorbidityPrimary care

Identifiers

PMID37580711
PMCPMC10426166

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.