ArticleJournal of robotic surgery2026
The promises and challenges of robotic-assisted surgery in regional Australia.
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. Cited by 3 papers, 1 of them a synthesis that pooled 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.
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.
Who cites it
3 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Robotic versus laparoscopic low anterior resection for rectal cancer: an updated systematic review and meta-analysis.Journal of robotic surgery · 2026Pooled it
- Failure modes of robotic-assisted arthroplasty platforms in Australia: a descriptive analysis of TGA adverse event reports.Journal of robotic surgery · 2026Article
- Establishing a sustainable and high-utilization robot-assisted surgery platform in a regional cancer center: insights from a multidisciplinary, break-even-guided operational strategy.Journal of robotic surgery · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
This perspective examines the introduction of robotic-assisted surgery (RAS) in rural and regional Australia, using the experience of a single regional public hospital as a case exemplar. It explores potential benefits, implementation challenges, and broader implications for surgical equity, workforce sustainability, and health-system planning. Rural Australians face persistent disparities in healthcare access, surgical outcomes, and specialist availability. Robotic-Assisted Surgery offers superior visualisation, precision, and patient recovery compared to traditional approaches, but remains largely concentrated in metropolitan centres. The inequitable distribution of RAS risks exacerbating urban–rural health divides unless deliberately addressed. The paper synthesises emerging evidence on RAS implementation across specialties, including colorectal, thoracic, urology, and gynaecology. It explores workforce implications, economic modelling, and training infrastructure challenges in the context of regional deployment. The Ballarat program is profiled in detail, including procedure volumes, workforce upskilling, and local system impact. Key enablers and barriers to sustainable RAS integration are mapped, with reference to training models, policy frameworks, and funding structures. The introduction of RAS in regional centres supports decentralisation of complex surgical care, and attracting a modern surgical workforce in turn contribute to reducing geographic healthcare inequity. While promising in terms of clinical outcomes and economic value, challenges remain around cost, training accessibility, and long-term sustainability. National strategies, investment in regional training pipelines, and equitable funding models are critical to ensure RAS becomes a scalable and inclusive solution for rural surgical care in Australia.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.