Knot promotes learning and eases the reporting burden of surgical residency requirements for residents by efficiently logging surgical cases via a mobile app.
Project Overview
Knot is a mobile platform that utilizes optical character recognition and EMR extraction to improve recording accuracy and reduce the time required to log a case.
The platform enables quick and easy reporting and allows residents to review their cases to help supplement their hands-on training. Residents can quickly review relevant cases when prepping for upcoming surgeries by leveraging the platform’s searchable log and analytics.
Residency programs and hospitals also benefit from a high-fidelity case log. Programs can use the surgical track records to run analytics on resident performance and use the number of surgeries completed as justification for additional surgical residents.
Healthcare Context
There are currently 43,000 residents in the U.S. that are required to log their cases with the Accreditation Council for Graduate Medical Education (ACGME) for residency graduation and for program certification.
The process is entirely manual and time-consuming. Approximately 1.6 million hours are spent annually on this manual task, equivalent to $121 million per year. From a clinical learning perspective, that is ~2 million appendectomies that the residents could have worked on instead. Even with the amount of the time and energy spent on case logging, studies show that the logged cases are not entirely accurate, with a fidelity of only 71%. Other than the loss of educational value and time, documentation is the leading cause of burnout according to 59% of physicians.
Interested in learning more about Knot?
Send us an email at accelerator@childrens.harvard.edu