Robotic Surgery linked with 144 Deaths in last 14 Year in US

Robotic Surgery linked with 144 Deaths in last 14 Year in US

The use of robotic systems for minimally invasive surgery has exponentially increased during the last decade. Between 2007 and 2013, over 1.74 million robotic procedures were performed in the US. So the safety and reliability of surgical robots are very critical requirements.

US Researchers team focuses on analysis of all the adverse events related to robotic surgical systems to determine the frequency, causes, and patient impact of adverse events in robotic procedures across different surgical specialties. The data is collected by the FDA MAUDE database during the 14-year period of 2000–2013. It covers the events experienced during the robotic procedures in six major surgical specialties: gynecology, urology, general, colorectal, cardiothoracic, and head and neck surgery.

The motivation behind this data analysis is the understanding the causes and patient impacts of surgical adverse events will help improve systems and operational practices to avoid incidents in the future. Researcher’s main focus was the number of adverse events reported per procedure and per surgical specialty, the most common types of device malfunctions and their impact on patients, and the causes for catastrophic events such as major complications, patient injuries, and deaths.

Data Sources for robotic surgery adverse events:

The Manufacturer and User Facility Device Experience (“MAUDE”) database is a publicly available collection of suspected medical device-related adverse event reports, submitted by mandatory (user facilities, manufacturers, and distributors) and voluntary (health care professionals, patients, and customers) reporters to the FDA.

Manufacturers and the FDA regularly monitor these reports to detect and correct device-related safety issues in a timely manner. While the MAUDE database, as a spontaneous reporting system, suffers from under reporting and inconsistencies, it provides valuable insights on real incidents that occurred during the robotic procedures and impacted patient safety.


During the study period, 144 deaths (1.4% of the 10,624 reports), 1,391 patient injuries (13.1%), and 8,061 device malfunctions (75.9%) were reported. The numbers of injury and death events per procedure have stayed relatively constant since 2007 (mean=83.4, 95% CI, 74.2–92.7). Surgical specialties, for which robots are extensively used, such as gynecology and urology, had lower number of injuries, deaths, and conversions per procedure than more complex surgeries, such as cardiothoracic and head and neck (106.3 vs. 232.9, Risk Ratio = 2.2, 95% CI, 1.9-2.6).

Robotic surgery
Cumulative rates of malfunctions per procedure (Image: arXiv)

Device and instrument malfunctions, such as falling of burnt/broken pieces of instruments into the patient (14.7%), electrical arcing of instruments (10.5%), unintended operation of instruments (8.6%), system errors (5%), and video/imaging problems (2.6%), constituted a major part of the reports. Device malfunctions impacted patients in terms of injuries or procedure interruptions. In 1,104 (10.4%) of the events, the procedure was interrupted to restart the system (3.1%), to convert the procedure to non-robotic techniques (7.3%), or to reschedule it to a later time (2.5%).

While the robotic surgical systems have been successfully adopted in many different specialties, this study demonstrates several important findings: (1) the overall numbers of injury and death events per procedure have stayed relatively constant over the years, (2) the probability of events in complex surgical specialties of cardiothoracic and head and neck surgery has been higher than other specialties, (3) device and instrument malfunctions have affected thousands of patients and surgical teams by causing complications and prolonged procedure times.

 Reference:  “Adverse Events in Robotic Surgery: A Retrospective Study of 14 Years of FDA Data”, Homa Alemzadeh, Ravishankar K. Iyer, Zbigniew Kalbarczyk, Nancy Leveson, Jai Raman. arXiv:1507.03518

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