ArticleSurgical endoscopy2024
Consensus guidelines on the bedside assistant skills required in robotic surgery.
Article in Surgical endoscopy, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 2 of them syntheses that pooled 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.
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.
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Who cites it
6 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Bedside assistant models in robotic abdominal and pelvic surgery: a systematic review of operative efficiency, training exposure, and perioperative safety.Journal of robotic surgery · 2026Pooled it
- Remote robotic surgery: a systematic review.Surgical endoscopy · 2026Pooled it
- The robotic PIANO: a critical narrative review of surgeon-controlled operative polyphony, human factors, and robotic training.Journal of robotic surgery · 2026Review
- A modified Delphi consensus on fusion (laparoscopic and robotic) approaches to colorectal surgery in Asia-Pacific.Journal of gastroenterology · 2026Article
- Team-based recovery from unexpected events beyond bleeding control in robot-assisted thoracic surgery.General thoracic and cardiovascular surgery · 2026Article
- Is high-quality robotic surgery a solo performance by the console surgeon?Gastroenterology report · 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
6 authors.
Funding
Abstract
backgroundWhile bedside assistants play a critical role in many robotic operations, substantial heterogeneity remains in bedside assistant training pathways. As such, this study aimed to develop consensus guidelines for bedside assistant skills required for team members in robotic operations.
methodsWe designed a study using the Delphi process to develop consensus guidelines around bedside assistant skills. We generated an initial list of bedside assistant skills from the literature, training materials, and expert input. We selected experts for the Delphi process based on prior scholarship in the area of robotic bedside assistant education and experience facilitating robotic bedside assistant training. For each item, respondents specified which robotic team members should have the skill from a list of "basic" bedside assistants, "advanced" bedside assistants, surgeons, surgical technologists, and circulating nurses. We conducted two rounds of the Delphi process and defined 80% agreement as sufficient for consensus.
resultsFourteen experts participated in two rounds of the Delphi process. By the end of the second round, the group had reached consensus on 253 of 305 items (83%). The group determined that "basic" bedside assistants should have 52 skills and that "advanced" bedside assistants should have 60 skills. The group also determined that surgeons should have 54 skills, surgical technologists should have 25 skills, and circulating nurses should have 17 skills. Experts agreed that all participants should have certain communication skills and basic knowledge of aspects of the robotic system.
conclusionsWe developed consensus guidelines on the skills required during robotic surgery by bedside assistants and other team members using the Delphi process. These findings can be used to design training around bedside assistant skills and assess team members to ensure that each team member has the appropriate skills. Hospitals can also use these guidelines to standardize expectations for robotic team members.
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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.