Evidence map›Paper›PMID 42416314›Full record

ArticleTranslational and clinical pharmacology2026

Implementation of decentralized clinical trials in Korea from a resource-based perspective.

Ki Young Huh, Gaeun Kang, Kye Hun Kim

Abstract read
In one paragraph

Article in Translational and clinical pharmacology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

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

3 authors.

Ki Young HuhDepartment of Clinical Pharmacology and Therapeutics, Seoul National University Hospital, Seoul National University College of Medicine, Seoul 03080, Korea.ORCID https://orcid.org/0000-0002-1872-9954
Gaeun KangDepartment of Pharmacology, Chonnam National University Medical School, Hwasun 58128, Korea.ORCID https://orcid.org/0000-0001-9841-1139
Kye Hun KimDepartment of Cardiology, Chonnam National University Medical School, Hwasun 58128, Korea.ORCID https://orcid.org/0000-0002-6885-1501

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Clinical trials in South Korea are heavily concentrated in Seoul, limiting patient access in other regions. We conducted a cross-sectional ecological study of 17 Korean administrative divisions to assess regional infrastructure readiness for decentralized clinical trial (DCT) implementation, using data from the Health Insurance Review and Assessment Service (2024), the National Health Insurance Service (2024), and the Ministry of Food and Drug Safety (2024 to 2025). Provincial densities for four resource domains (specialists, nurses, beds, and medical equipment) were calculated per 100,000 patients and normalized to Seoul (= 1.00). Area-specific composite indices for four therapeutic areas were computed as the capped geometric mean of specialist and equipment densities, and an overall infrastructure index as the capped geometric mean of all four domain densities. Trial density was derived from 1,924 approved trials yielding 7,760 trial-center pairs (99% mapping rate). Among the 16 non-Seoul provinces, bed density was the most dispersed (coefficient of variation [CV] = 0.39, range 0.58 to 2.91), whereas specialist density was the most Seoul-concentrated of the four domains: no non-Seoul province reached 80% of Seoul's level (CV = 0.23, range 0.42 to 0.79). The four therapeutic-area composite indices showed comparable dispersion (CV 0.15 to 0.23; composite infrastructure CV 0.16; Pearson

Indexed as

Clinical TrialHealthcare DisparitiesHealth ResourcesRepublic of KoreaResource Allocation

Identifiers

PMID42416314
PMCPMC13338760

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.