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Article of the week: Surgical safety checklist for robotic surgery

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Every week the Editor-in-Chief selects the Article of the Week from the current issue of BJUI. The abstract is reproduced below and you can click on the button to read the full article, which is freely available to all readers for at least 30 days from the time of this post.

In addition to the article itself, there is an accompanying editorial written by a prominent member of the urological community. This blog is intended to provoke comment and discussion and we invite you to use the comment tools at the bottom of each post to join the conversation.

If you only have time to read one article this week, it should be this one.

Development and content validation of a surgical safety checklist for operating theatres that use robotic technology

Kamran Ahmed, Nuzhath Khan, Mohammed Shamim Khan and Prokar Dasgupta

MRC Centre for Transplantation, King’s College London, King’s Health Partners, Department of Urology, Guy’s Hospital, London, UK

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OBJECTIVES

• To identify and assess potential hazards in robot-assisted urological surgery.

• To develop a comprehensive checklist to be used in operating theatres with robotic technology.

METHODS

• Healthcare Failure Mode and Effects Analysis (HFMEA), a risk assessment tool, was used in a urology operating theatre with innovative robotic technology in a UK teaching hospital between June and December 2011.

• A 15-member multidisciplinary team identified ‘failure modes’ through process mapping and flow diagrams.

• Potential hazards were rated according to severity and frequency and scored using a ‘hazard score matrix’.

• All hazards scoring ≥8 were considered for ‘decision tree’ analysis, which produced a list of hazards to be included in a surgical safety checklist.

RESULTS

• Process mapping highlighted three main phases: the anaesthesia phase, the operating phase and the postoperative handover to recovery phase.

• A total of 51 failure modes were identified, 61% of which had a hazard score ≥8.

• A total of 22 hazards were finalised via decision tree analysis and were included in the checklist.

• The focus was on hazards specific to robotic urological procedures such as patient positioning (hazard score 12), port placement (hazard score 9) and robot docking/de-docking (hazard score 12).

CONCLUSIONS

• HFMEA identified hazards in an operating theatre with innovative robotic technologies which has led to the development of a surgical safety checklist.

• Further work will involve validation and implementation of the checklist.

 

Read Previous Articles of the Week

 

Editorial: Sergeant, do you copy?

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In the Institute of Medicine report published in 1999, it was estimated that 44 000–98 000 patients died annually from preventable medical errors. It was further reported that the annual burden on economy due to preventable medical errors was anywhere between 17–29 billion American dollars. In the USA federal budget 2000–2001, the entire federal resources devoted to general science, space and technology was 19.2 billion American dollars: ≈10 billion less than the cost of medical errors (Fig. 1).

Figure 1. The magnitude of problem caused by medical errors. USDs, American dollars.

On root cause analysis of the errors identified in the Joint Commission on Accreditation and Certification database (2011), it was reported that most of these errors are non-technical, i.e. human factors (72%), leadership (65%), communication breakdown (61%), etc. Furthermore, Greenberg et al. studied the patterns of communication breakdown on the Malpractice Insurers’ Medical Error Prevention Study (MIMEPS) database and concluded that breakdown patterns were similar preoperatively (38%), intraoperatively (30%) and postoperatively (32%). Most errors were due to miscommunication within a single department (78%), as compared with across departments (19%) or institutions (3%). In 49% of the cases, the information was never relayed and in 44% the information relayed was not comprehended appropriately. In all, 29% of these errors involved a surgery attending at transmitting end and 56% at the receiving end of information. In all, 85% of these communications were verbal.

In this issue of BJUI, Ahmed et al. have used the Healthcare Failure Mode and Effect Analysis (HFMEA) model to design a safety checklist specifically for robotic procedures. Checklists have been heavily used in high-risk environments that involve complex technology, e.g. aerospace and nuclear engineering. Robotic surgery is another such high-risk environment, where intraoperative communication is critical. When a surgeon performs a robotic surgery, (s)he is not standing next to the patient (and occasionally not even in the same room!) and relies heavily on his/her assistant. Additionally, the bulky robot takes most of the space around the patient. Small movements of the instruments can cause abrupt and exaggerated movements of the robotic arms, which might injure the bedside assistant, anaesthesiologist, or the patient himself. Last, but not the least, there is a memory clutch on the robotic arms, and its purpose is to ‘remember’ the position of the arms while exchanging the instruments. However, if this clutch is pressed by mistake, all memory is lost and careless insertion of an instrument at this time, making an assumption of memory, can be dangerous and can cause serious injury. The safety checklist described by Ahmed et al. is one of the first checklists specific to robotic surgery. In parallel to this, the Fundamentals of Robotic Surgery (FRS) inter-disciplinary consortium led by Dr Richard Satava has also developed a checklist, specifically for robotic surgery. It will be interesting to study the actual impact of these checklists on prevention of medical errors in robotic surgery. Similar checklists have been validated showing significant clinical correlation using in situ simulation for obstetric emergencies.

Although checklists do help to a certain extent to prevent serious errors, the basics of communications must not be forgotten while communicating to a colleague about patient care. There should be no ambiguity about who is the ‘transmitter’ and who is the ‘receiver’ of information. Both the ‘transmitter’ and ‘receiver’ should have a shared mental model about the purpose of communication (‘transmitter’ is seeking guidance, giving orders, asking for an opinion, referring a case, etc.). Finally, closed-loop communication should be a part of protocol where both the ‘receiver’ and ‘transmitter’ acknowledge the receipt of information, e.g.

Console Surgeon: ‘Please replace the scissors in the right arm with the needle driver’.

Assistant: ‘OK, I am replacing the scissors in your right arm with a needle driver’.

Console Surgeon: ‘Go ahead’.

Assistant: ‘Needle driver coming in’.

Console Surgeon: ‘Perfect. Thank you’.

 

Sanket Chauhan and Robert M. Sweet
Department of Urology, University of Minnesota Medical School, Minneapolis, MN, USA

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