Evidence map›Paper›PMID 42497224›Full record

Observational studyPloS one2026

Long-term care hospitals as end-of-life care settings in South Korea: A nationwide analysis of utilization patterns and clinical trajectories.

Haein Kim, Seungwon Shin

Abstract readObservational Study
In one paragraph

Observational study in PloS one, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0cells of the map it votes in
0citing papers in PubMed
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1 · What the graph read from it

What it found

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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

2 authors.

Haein KimCollege of Korean Medicine, Sangji University, Wonju, Republic of Korea.
Seungwon ShinCollege of Korean Medicine, Sangji University, Wonju, Republic of Korea.ORCID https://orcid.org/0000-0002-6160-0339

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesThis study aimed to investigate the utilization patterns and end-of-life trajectories of older adults in Korean long-term care hospitals (LTCHs) using nationwide population-based data.

methodsThis retrospective observational study analyzed National Health Insurance Service claims data (2014-2023). We constructed three analytical groups: an annual inpatient group to examine longitudinal trends in volume and mortality; a newly admitted inpatient group to assess the sociodemographic profile at the time of LTCH entry; and a decedent group to reconstruct the clinical trajectory and cumulative resource use from initial admission to death.

resultsWhile the volume of older inpatients increased, the annual number of deaths involving LTCH use increased from 68,357 in 2014 to 112,157 in 2023 over the decade. Patients were newly admitted to LTCHs in their early 80s (median age 81 years, IQR 75-86) and were predominantly female (62.1%). In addition, Medical Aid beneficiaries (13.7%) and individuals with registered disabilities (28.0%) were overrepresented, indicating high sociodemographic vulnerability. Decedents spent a median of 79 days (IQR 22-299) as LTCH inpatients. While 30.1% stayed for <30 days, 22.2% remained hospitalized for ≥ 360 days, indicating substantial variation in length of stay. Overall, 68.5% of decedents died during LTCH stay. While admissions were driven by chronic geriatric syndromes, the end-of-life phase was dominated by a surge in acute infectious and systemic conditions (e.g., pneumonia, 10.2% to 22.3%; sepsis, 3.3% to 11.9%).

conclusionsLTCHs in Korea have played an increasingly important role as a setting for end-of-life care, managing a distinct trajectory from chronic frailty to acute deterioration. Given that these institutions are functioning as end-of-life care settings, policy reforms should strengthen palliative care integration, advance care planning, workforce training, and end-of-life care capacity within LTCHs.

Indexed as

Long-Term CareTerminal CareAgedAged, 80 and overFemaleHospitalizationHumansLength of StayMaleRepublic of KoreaRetrospective Studies

Identifiers

PMID42497224
PMCPMC13399523

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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.