MAUDE data represents reports of adverse events involving medical devices. The data consists of all voluntary reports since June, 1993, user facility reports since 1991, distributor reports since 1993, and manufacturer reports since August, 1996.

The adverse events reports related to robotic surgical systems and instruments, submitted to the publicly available FDA MAUDE database between January 2000 and December 2013.We extracted this data by searching the MAUDE records which are available on the FDA website at: http://www.fda.gov/MedicalDevices/DeviceRegulationandGuidance/PostmarketRequirements/ReportingAdverseEvents/ucm127891.htmThe structured data generated by our natural language parsing tool, after analysis of unstructured fields in the FDA MAUDE records. The new information (fields) extracted from the data include: • Patient injury (such as burns, cuts, or damage to organs) and death events that were reported under another Event Type, such as “Malfunction” or “Other”. • Surgical specialty and type of robotic procedure during which the adverse events occurred. • Major types of device or instrument malfunctions (e.g., falling of burnt/broken pieces of instruments into patients’ bodies or electrical arcing of instruments) • Adverse events that caused an interruption in the progress of surgery, by leading the surgical team to troubleshoot technical problems (e.g., restarting the system), convert the procedure to non-robotic surgical approaches (e.g., laparoscopy or open surgery), or abort the procedure and reschedule it to a later time.

BackgroundUse of robotic systems for minimally invasive surgery has rapidly increased during the last decade. Understanding the causes of adverse events and their impact on patients in robot-assisted surgery will help improve systems and operational practices to avoid incidents in the future.MethodsBy developing an automated natural language processing tool, we performed a comprehensive analysis of the adverse events reported to the publicly available MAUDE database (maintained by the U.S. Food and Drug Administration) from 2000 to 2013. We determined the number of events reported per procedure and per surgical specialty, the most common types of device malfunctions and their impact on patients, and the potential causes for catastrophic events such as patient injuries and deaths.ResultsDuring 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 (mean = 83.4, 95% confidence interval (CI), 74.2–92.7 per 100,000 procedures) over the years. Surgical specialties for which robots are extensively used, such as gynecology and urology, had lower numbers of injuries, deaths, and conversions per procedure than more complex surgeries, such as cardiothoracic and head and neck (106.3 vs. 232.9 per 100,000 procedures, Risk Ratio = 2.2, 95% CI, 1.9–2.6). 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 all 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 (2.5%).ConclusionsDespite widespread adoption of robotic systems for minimally invasive surgery in the U.S., a non-negligible number of technical difficulties and complications are still being experienced during procedures. Adoption of advanced techniques in design and operation of robotic surgical systems and enhanced mechanisms for adverse event reporting may reduce these preventable incidents in the future.

This data note presents valuable insights into reported failures related to autoinjectors, as recorded in the Manufacturer and User Facility Device Experience (MAUDE) database. Autoinjectors play a pivotal role in modern medical treatments, facilitating self-administration of medications. However, understanding the nature of failures and associated risks is essential for enhancing their safety and reliability. By analysing the MAUDE database, this data note sheds light on the types of failures, contributing factors, and potential implications for patient care.

Related work on analysis of the FDA adverse event reports on robotic surgical systems.

(Note that the malfunction and surgical team action categories are not mutually exclusive, i.e., in many cases more than one malfunction or action were reported in a single event.)

Summary of death and injury reports (2000–2012).

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