Evidence map›Paper›PMID 42860510›Full record

ArticleJournal of robotic surgery2026

Unveiling the Chasm in Japanese robot-assisted surgery diffusion: the interplay of surgical volume and intra-specialty spillover.

Yusuke Natsume, Shingo Kano

Abstract read
In one paragraph

Article in Journal of robotic surgery, 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

2 authors.

Yusuke NatsumeBio-Innovation Policy Unit, Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, 5-1-5 Kashiwanoha, Chiba, 277-8562, Kashiwa City, Japan. 5006956474@edu.k.u-tokyo.ac.jp.ORCID http://orcid.org/0009-0007-9566-9776
Shingo KanoBio-Innovation Policy Unit, Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, 5-1-5 Kashiwanoha, Chiba, 277-8562, Kashiwa City, Japan.ORCID http://orcid.org/0000-0002-6625-2644

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

To examine structural factors associated with the diffusion of robot-assisted surgery (RAS) in Japan, this study examined the associations of annual surgical volume, defined as the sum of open, conventional laparoscopic, and RAS cases, and prior intra-specialty experience with adoption speed. Using the 1st to 10th editions of the National Database of Health Insurance Claims and Specific Health Checkups of Japan (NDB) Open Data across fiscal years 2014-2023, diffusion trajectories were visualized for 21 procedures approved for insurance coverage by 2020 through bivariate plots of annual surgical volume versus RAS replacement rates. RAS diffusion exhibited non-linear dynamics associated with annual procedure volume. In niche markets with < 6,000 annual cases (n = 9), six procedures demonstrated high growth in RAS replacement rate. Conversely, among 12 procedures with ≥ 6,000 annual cases, four did not cross the 16.0% chasm threshold through FY2023, and three required 6 years to surpass it. These patterns were thought to reflect challenges in the transition from specialized centers to general hospitals. Furthermore, a trend consistent with "intra-specialty spillover" was observed, wherein procedures approved in FY2020 achieved higher initial adoption than those in FY2018; although inseparable from the overall expansion of RAS since 2018, this suggests that accumulated infrastructure and expertise may facilitate the uptake of subsequent techniques. These findings suggest that RAS diffusion is associated with annual procedure volume, organizational readiness, and specialty‑specific infrastructure alongside technical factors. Future implementation strategies may benefit from infrastructure sharing within and across specialties and resource optimization to bridge the observed diffusion chasm.

Indexed as

Diffusion of InnovationRobotic Surgical ProceduresHumansJapanChasmCross-specialty analysisDiffusion of innovationNDB Open DataRobot-assisted surgerySpillover effect

Identifiers

PMID42860510
PMCPMC13654899

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.