Evidence map›Paper›PMID 40668261›Full record

ArticleJournal of robotic surgery2025

The institutional impact of robotic surgery adoption: evidence from prostate and thyroid cancers in South Korea.

Junsoo Ro, Young Kyung Do

Abstract read
In one paragraph

Article in Journal of robotic surgery, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Article
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.

Junsoo RoDepartment of Preventive Medicine & Public Health, Ajou University School of Medicine, Suwon, Republic of Korea.ORCID http://orcid.org/0000-0002-8156-5294
Young Kyung DoDepartment of Health Policy and Management, Seoul National University College of Medicine, Seoul, Republic of Korea. ykdo89@snu.ac.kr.ORCID http://orcid.org/0000-0001-5024-8264

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The adoption of robotic surgery has significantly impacted various levels of the health system. However, previous studies lack evidence of causality regarding the impact at the institutional level. This study explores the effects of robotic surgery adoption on prostate and thyroid cancer treatments in South Korea, using the National Health Insurance Service (NHIS) data from 2005 to 2017. We applied interrupted time series analysis (ITSA) to examine changes in the number of inpatient admissions and volume of surgery at institutions before and after robotic surgery adoption. For prostate cancer, robotic surgery adoption resulted in an immediate increase of approximately 4.9 surgeries per quarter, with a substantial rise in inpatient admissions. For thyroid cancer, inpatient admissions showed a significant upward trend post-adoption. The increase in service volumes after the adoption of robotic surgery may reflect strategic institutional efforts to expand service delivery, supplier-induced demand to meet performance targets, or the advertising effects of robotic surgery adoption, which likely attracted patients from surrounding areas. This study highlights the broader implications of high-cost medical technologies on healthcare delivery, institutional strategies, and potential increases in healthcare costs. Future research should investigate other conditions treated with robotic surgery to fully understand its system-wide effects.

Indexed as

Prostatic NeoplasmsRobotic Surgical ProceduresThyroid NeoplasmsFemaleHospitalizationHumansInterrupted Time Series AnalysisMaleMiddle AgedRepublic of KoreaInstitutional impactInterrupted time series analysis (ITSA)Robotic surgeryTechnology Adoption

Identifiers

PMID40668261
PMCPMC12267340

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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.