1c:{"metadata":[["$","title","0",{"children":"NIH VideoCast - Sensors, motion tracking, and data science: the quest to train MD’s like elite athletes"}],["$","meta","1",{"name":"description","content":"NIH Director’s Wednesday Afternoon Lecture Series\n

\nThe current gold standard for evaluating physician competency for hands-on clinical skills involves the use of observer-based checklists. However, a known weakness in this approach is that certain skills, important to overall performance, cannot be reliably tracked by a human observer. This fault allows the possibility of rating clinicians as competent despite having critical performance deficits. What if sensors and motion tracking could be used to quantify physician performance? This WALS presentation will explore new research demonstrating the relationship between movement metrics, data science, and physician excellence.\n

For more information go to https://oir.nih.gov/wals"}],["$","meta","2",{"name":"publisher","content":"National Institutes of Health"}],["$","meta","3",{"property":"og:title","content":"NIH VideoCast - Sensors, motion tracking, and data science: the quest to train MD’s like elite athletes"}],["$","meta","4",{"property":"og:description","content":"NIH Director’s Wednesday Afternoon Lecture Series\n

\nThe current gold standard for evaluating physician competency for hands-on clinical skills involves the use of observer-based checklists. However, a known weakness in this approach is that certain skills, important to overall performance, cannot be reliably tracked by a human observer. This fault allows the possibility of rating clinicians as competent despite having critical performance deficits. What if sensors and motion tracking could be used to quantify physician performance? This WALS presentation will explore new research demonstrating the relationship between movement metrics, data science, and physician excellence.\n

For more information go to https://oir.nih.gov/wals"}],["$","meta","5",{"property":"og:url","content":"https://uat.d1rkikwu4q8tg.amplifyapp.com/watch/b0d17810-d5db-11f0-9cf9-12c45c580ad9"}],["$","meta","6",{"property":"og:site_name","content":"NIH VideoCast"}],["$","meta","7",{"property":"og:image","content":"https://nihcit.rev.vbrick.com/api/v2/media/videos/thumbnails/ed5995a8-2402-49f0-a460-e46e194bf79b.jpg"}],["$","meta","8",{"property":"og:type","content":"website"}],["$","meta","9",{"name":"twitter:card","content":"summary_large_image"}],["$","meta","10",{"name":"twitter:title","content":"NIH VideoCast - Sensors, motion tracking, and data science: the quest to train MD’s like elite athletes"}],["$","meta","11",{"name":"twitter:description","content":"NIH Director’s Wednesday Afternoon Lecture Series\n

\nThe current gold standard for evaluating physician competency for hands-on clinical skills involves the use of observer-based checklists. However, a known weakness in this approach is that certain skills, important to overall performance, cannot be reliably tracked by a human observer. This fault allows the possibility of rating clinicians as competent despite having critical performance deficits. What if sensors and motion tracking could be used to quantify physician performance? This WALS presentation will explore new research demonstrating the relationship between movement metrics, data science, and physician excellence.\n

For more information go to https://oir.nih.gov/wals"}],"$L22","$L23","$L24"],"error":null,"digest":"$undefined"}