Video Analysis of Errors and Technical Performance Within Minimally Invasive Surgery
试验速览
- 阶段
- 不适用
- 状态
- 招募中
- 入组人数
- 100
- 试验地点
- 5
- 主要终点
- Number of errors in an operation using validated methodology- Objective Clinical Human Reliability Analysis (OCHRA)
研究概览
简要总结
Despite the high volumes, advanced minimally invasive surgery is non-standardised and variations often occur in surgical technique, performance, delivery, team communication, and surgical approach. Such variations can result in errors and complications that can potentially be avoided.
This project aims to analyse surgical phases (stage of the operation), skill and errors to anonymised, surgical video data through Medtronic's Touch Surgery™ Enterprise DS1 Computer which can capture video data anonymously in any minimally invasive (key hole) procedure in the operating room, allowing immediate, upload of data to a platform for immediate feedback and assessment to surgeons. The investigators hypothesise that understanding technical performance and surgical processes, may reduce unwarranted variations, errors and near misses, and improve the performance of the entire surgical team that is ultimately hoped to enhance patient safety and outcomes. Investigators plan to develop assessment tools with the hope to improve feedback, learning and ultimately surgeons' performances. The latest methodology of manual (OCHRA) and automated assessment (artificial intelligence) will be applied. Investigators aim to validate these methods by correlating video "scores" of skill/errors to patient outcomes e.g. complications, cancer outcome.
详细描述
There are 2.5 million people who have cancer in the UK, projected to increase to 4M by 2030. Over the past three decades, there has been a rapid uptake of minimally invasive (keyhole) surgery i.e. laparoscopic and robotic techniques, to treat cancer across different specialties. Robotic surgery is a well-established modality; the most commonly used robot for surgery (da Vinci) has been used in more than 8.5 million procedures, 1.25 million of which were in 2020.
Previous research from our group developed valid methods to accurately assess surgical skill and errors in laparoscopic procedures using video analysis of rectal cancer surgery. The methods and tools developed were able to link surgeons' technical skill, including errors made, to patient outcome i.e. those who scored better had better outcomes. Investigators hypothesise that understanding and optimising surgical processes and errors will reduce unwarranted variations and improve the performance of the entire surgical team that is ultimately hoped to enhance patient safety and outcomes.
With an increasing use of robotic systems across different specialties, there is an need to standardize training, assessment, testing and sign-off as a competent robotic surgeon in order to improve patient safety. A study from the 1990s estimated that more than 250,000 people die in the USA every year from medical error. Another study from the USA reported between 2000-2013 10,624 adverse events relating to robotic procedures. Experts raised concerns over surgical curricula being random and insufficient to ensure patient safety, leading to the development of EAU Robotic Urology Section Curriculum (ERUS). In addition, an independent review by the Emergency Care Research Institute (ECRI) on health technology hazards identified a lack of robotic surgical training as one of the top 10 risks to patients. Comparisons are frequently made between the aviation industry and surgery in terms of adverse event analysis and non-technical skills. The aviation industry, however, has mandatory, recurrent, reassessment and requalification throughout the career pathway and an internationally agreed standard for training, which robotic surgery does not.
Our research group has a track record in developing objecting assessment tools to aid training and accredit laparoscopic surgery and will utilise this expertise to enrichen assessment tools in robotic surgery.
Given the link between surgical skill and error counts to patient outcome, this research team aims to analyse surgical video within robotic surgery in different procedures to further understand the surgical process and errors made.
研究设计
- 研究类型
- Observational
- 观察模型
- Cohort
- 时间视角
- Prospective
入排标准
- 年龄范围
- 18 Years 至 —(Adult, Older Adult)
- 性别
- All
- 接受健康志愿者
- 是
入选标准
- •Patient undergoing elective minimally-invasive urological/gastrointestinal surgery
- •18 years old or over
- •Have capacity to provide informed consent
排除标准
- •Surgery performed with palliative intent or under unplanned/emergency settings
- •Under 18 years old
- •Cannot consent
结局指标
主要结局
Number of errors in an operation using validated methodology- Objective Clinical Human Reliability Analysis (OCHRA)
时间窗: 2 years of video data will be recorded prospectively
Objective Clinical Human Reliability Analysis (OCHRA) methodology will be applied to video visual data to assess number, type and severity of errors within the operation.
次要结局
- Secondary outcome measure- Age(Up to 5 years, the normal time period of follow-up for cancer related outcomes)
- Secondary outcome measure- ASA grade(Up to 2 years and 6 months, duration of the study)
- Application of Machine learning and Artificial Intelligence to video analysis(Up to 2 years and 6 months, duration of the study)
- Secondary outcome measure -BMI(Up to 2 years and 6 months, duration of the study)
- Secondary outcome measure(Up to 2 years and 6 months, duration of the study)
研究者
Matthew Boal
Surgical PhD Research Fellow
The Griffin Institute
