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Improving Patient Outcomes with Big Data
Big data is reshaping industries at an alarming rate, allowing businesses and organisations to better understand their customers. But big data isn’t just the reserve of the corporations. In fact, with more and more robotics systems making their way into the operating theatre, patient and procedure data has never been easier to capture.
But what kind of data is being collected? How is it being gathered? And what use could it be to patients, trainees and qualified surgeons?
In this episode of Surgical Robo-Talks, Jessica and co-host Fahad Ullah (Colorectal Trainee and ASiT Past Robotic Lead) are joined by Associate Medical Director at CMR Surgical and Consultant Urologist at University College London Hospitals, Justin Collins.
They’ll explore discuss how surgeons and educators can make sense of the tremendous amount of information being gathered and look at how this data could improve procedures and patient outcomes. Plus, they’ll explore how technologies such as computer-vision and tele-mentoring are being used to improve training and ask if there’s a place for AI in robotic-assisted surgery.
We’ll also ask:
- (2:57) – What kind of data is being collected through robotic assisted surgery and how is it being used?
- (4:24) – How do surgeons get access to their instrument data?
- (5:23) – What is computer vision?
- (6:44) – How can we determine which data is relevant and useful?
- (8:49) – What kind of robotics data could be useful to patients? And when could patient access to that data become a reality?
- (10:00) – How could robotics data be used to decrease the learning curve for trainees?
- (11:31) - How should surgeons and educators process big data sets to make sure they draw the right conclusions concerning best practice guidelines?
- (13:23) – How will big data help consultants beyond education?
- (15:37) – What is the current state of registries in the UK?
- (17:53) – What role could AI play in healthcare in the future?
- (19:59) – What are the opportunities and limitations of tele-mentoring?
- (21:29) – What can operating and remote surgeons do to set themselves up for success when working together for the first time?
- (23:12) – Is tele-mentoring suitable for all trainees at every stage of the learning curve?
- (24:49) - How can robotics-derived data help surgeons and trainees to meet performance metrics?
- (26:29) – How can surgical robotics data be used to help trainees benchmark their progress?
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By CMR Surgical and Association of Surgeons in TrainingBig data is reshaping industries at an alarming rate, allowing businesses and organisations to better understand their customers. But big data isn’t just the reserve of the corporations. In fact, with more and more robotics systems making their way into the operating theatre, patient and procedure data has never been easier to capture.
But what kind of data is being collected? How is it being gathered? And what use could it be to patients, trainees and qualified surgeons?
In this episode of Surgical Robo-Talks, Jessica and co-host Fahad Ullah (Colorectal Trainee and ASiT Past Robotic Lead) are joined by Associate Medical Director at CMR Surgical and Consultant Urologist at University College London Hospitals, Justin Collins.
They’ll explore discuss how surgeons and educators can make sense of the tremendous amount of information being gathered and look at how this data could improve procedures and patient outcomes. Plus, they’ll explore how technologies such as computer-vision and tele-mentoring are being used to improve training and ask if there’s a place for AI in robotic-assisted surgery.
We’ll also ask:
- (2:57) – What kind of data is being collected through robotic assisted surgery and how is it being used?
- (4:24) – How do surgeons get access to their instrument data?
- (5:23) – What is computer vision?
- (6:44) – How can we determine which data is relevant and useful?
- (8:49) – What kind of robotics data could be useful to patients? And when could patient access to that data become a reality?
- (10:00) – How could robotics data be used to decrease the learning curve for trainees?
- (11:31) - How should surgeons and educators process big data sets to make sure they draw the right conclusions concerning best practice guidelines?
- (13:23) – How will big data help consultants beyond education?
- (15:37) – What is the current state of registries in the UK?
- (17:53) – What role could AI play in healthcare in the future?
- (19:59) – What are the opportunities and limitations of tele-mentoring?
- (21:29) – What can operating and remote surgeons do to set themselves up for success when working together for the first time?
- (23:12) – Is tele-mentoring suitable for all trainees at every stage of the learning curve?
- (24:49) - How can robotics-derived data help surgeons and trainees to meet performance metrics?
- (26:29) – How can surgical robotics data be used to help trainees benchmark their progress?