While innovation in surgery has been driven by advances in anatomy, physiology, pathology, and engineering, future progress in surgery will be driven by how data is used. Surgical Data Science (SDS) brings together engineering to capture this data and techniques to analyze it to develop products that support surgeons and help patients.
Large amounts of data are now readily available that capture surgical care in its entirety – before, during, and after surgery. This availability in data is only expected to increase with growing sophistication in surgical care technology.
All science can be described as a process of gradual progress towards effective solutions. A new review published in the open access journal Innovative Surgical Sciences shows how the combination of data science and surgery known as Surgical/intervention Data Science (SDS) can provide scalable solutions to optimize value in care by enhancing safety, efficiency and effectiveness.
SDS in a nutshell
What is SDS? It involves creating tools to measure, model and optimize patient care processes using data. This includes collecting and analyzing complex data in various forms, such as video and other imaging, laboratory tests, patient narratives and doctors’ notes. SDS aims to build tools with this data that augment surgeons’ performance and their learning and to improve quality of care and smart technology.
SDS has multiple current and potential uses. First, it is used to acquire and store information. Second, it can be used to judge if the methods used to evaluate a procedure are adequate. Third, it can support surgeons significantly by improving surgical techniques, by enabling cooperation between surgeons and technology, and by enriching medical education.
Solving real world problems
What kind of real world problems can SDS solve? Three hundred and twelve million surgical procedures were performed around the world in 2012. Two hundred and eighty-eight million people in developing countries suffer from conditions which could be solved with surgeries.
If those surgeries were performed, 5.6 million deaths could be avoided, and the quality of life for the rest of those patients would be improved. Lack of access to skillful surgeons is one of the main reasons why these procedures are not performed. Training surgeons is expensive, especially in countries that can only dedicate modest resources to its health service.
A further problem is the multitude of complications that can occur before, during and after surgery.
Errors can have severe consequences
“Caring for surgical patients is complex, and insufficient care or errors can have severe consequences for patients. Errors or insufficient care are most commonly the result of errors in judgement, poor technical skill, or miscommunication,” said author of the review Dr. S. Swaroop Vedula of Johns Hopkins University.
The solution to both of these problems can be the application and interpretation of the information that modern technology allows scientists to gather.
Tools to model procedures prior to surgery
Many applications are being developed using SDS, including tools which will be able to measure the “dose of surgery” and effectiveness of a given procedure.
Furthermore, there are tools which will be able to model a new procedure before it is used on a patient. This will help predict and avoid complications before, during, and after surgery. Similar tools will be able to help a surgeon make real time decisions during an operation.
In addition to improvements to surgery, SDS can also improve the training that surgeons receive by developing applications that objectively evaluate surgical performance, automate individualized feedback, and lead to robots that can teach and work with surgeons. These new technologies can make training surgeons efficient and appropriate care accessible to people all around the world.
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