OBJECTIVE: To examine the Manufacturer and User Facility Device Experience Database (MAUDE) database to capture adverse events experienced with the Da Vinci Surgical System. In addition, to design a standardized classification system to categorize the complications and machine failures associated with the device. SUMMARY BACKGROUND DATA: Overall, 1,057,000 DaVinci procedures were performed in the United States between 2009 and 2012. Currently, no system exists for classifying and comparing device-related errors and complications with which to evaluate adverse events associated with the Da Vinci Surgical System. METHODS: The MAUDE database was queried for events reports related to the DaVinci Surgical System between the years 2009 and 2012. A classification system was developed and tested among 14 robotic surgeons to associate a level of severity with each event and its relationship to the DaVinci Surgical System. Events were then classified according to this system and examined by using Chi-square analysis. RESULTS: Two thousand eight hundred thirty-seven events were identified, of which 34% were obstetrics and gynecology (Ob/Gyn); 19%, urology; 11%, other; and 36%, not specified. Our classification system had moderate agreement with a Kappa score of 0.52. Using our classification system, we identified 75% of the events as mild, 18% as moderate, 4% as severe, and 3% as life threatening or resulting in death. Seventy-seven percent were classified as definitely related to the device, 15% as possibly related, and 8% as not related. Urology procedures compared with Ob/Gyn were associated with more severe events (38% vs 26%, p < 0.0001). Energy instruments were associated with less severe events compared with the surgical system (8% vs 87%, p < 0.0001). Events that were definitely associated with the device tended to be less severe (81% vs 19%, p < 0.0001). CONCLUSIONS: Our classification system is a valid tool with moderate inter-rater agreement that can be used to better understand device-related adverse events. The majority of robotic related events were mild but associated with the device.
OBJECTIVE: To examine the Manufacturer and User Facility Device Experience Database (MAUDE) database to capture adverse events experienced with the Da Vinci Surgical System. In addition, to design a standardized classification system to categorize the complications and machine failures associated with the device. SUMMARY BACKGROUND DATA: Overall, 1,057,000 DaVinci procedures were performed in the United States between 2009 and 2012. Currently, no system exists for classifying and comparing device-related errors and complications with which to evaluate adverse events associated with the Da Vinci Surgical System. METHODS: The MAUDE database was queried for events reports related to the DaVinci Surgical System between the years 2009 and 2012. A classification system was developed and tested among 14 robotic surgeons to associate a level of severity with each event and its relationship to the DaVinci Surgical System. Events were then classified according to this system and examined by using Chi-square analysis. RESULTS: Two thousand eight hundred thirty-seven events were identified, of which 34% were obstetrics and gynecology (Ob/Gyn); 19%, urology; 11%, other; and 36%, not specified. Our classification system had moderate agreement with a Kappa score of 0.52. Using our classification system, we identified 75% of the events as mild, 18% as moderate, 4% as severe, and 3% as life threatening or resulting in death. Seventy-seven percent were classified as definitely related to the device, 15% as possibly related, and 8% as not related. Urology procedures compared with Ob/Gyn were associated with more severe events (38% vs 26%, p < 0.0001). Energy instruments were associated with less severe events compared with the surgical system (8% vs 87%, p < 0.0001). Events that were definitely associated with the device tended to be less severe (81% vs 19%, p < 0.0001). CONCLUSIONS: Our classification system is a valid tool with moderate inter-rater agreement that can be used to better understand device-related adverse events. The majority of robotic related events were mild but associated with the device.
Entities:
Keywords:
FDA MAUDE; classification of adverse events; robotic surgery
Authors: Neel H Patel; Nikil Uppaluri; Michael Iorga; Ariel Schulman; Jonathan B Bloom; John Phillips; Sean Fullerton; Sensuke Konno; Muhammad Choudhury; Majid Eshghi Journal: J Endourol Date: 2019-05-24 Impact factor: 2.942
Authors: Hani J Marcus; Vejay N Vakharia; Sebastien Ourselin; John Duncan; Martin Tisdall; Kristian Aquilina Journal: Childs Nerv Syst Date: 2018-05-10 Impact factor: 1.475