Given the importance of the overnight period in inpatient care, it remains challenging to get objective, quantitative data on whether or not a patient had a good night. And, to be provocative: how do we even define what is meant by a “good night?” While there is growing awareness that patients very often have sleepless […]
Inpatient telemedicine in hospitals is expanding rapidly for many reasons. Yet older solutions running on old operating systems represent a fundamental threat to the security of the hospital environment. In the next 12-24 months, it is very likely that a major hospital outage or ransomware attack will have come through their telemedicine solution. Hospital CEOs […]
This work builds on our initial research in AI computer vision in the Duke medical intensive care unit. This research demonstrated several compelling data-driven readouts of patient activity and room environment, highlighting its potential utility in sleep, sedation, agitation, and delirium
Why computer vision can help better observe patients and set the foundation for better hospital financials.
“We are excited about our collaboration with LookDeep to use AI to expand virtual safety, nursing and medical services to support our staff and improve patient care,” said Dr. Paul DePriest, Executive Vice President and Chief Operating Officer for Baptist Memorial Health Care.
How Computer Vision and AI can create help create a virtual guardian angel for nurses.
The use of video in the hospital creates a unique set of security challenges, and it is crucial that these challenges are met head-on to ensure the safety and privacy of patients and staff. As its usage grows, yesterday’s security through anonymity is no longer an option.
In this blog post, I review LookDeep Health’s IRB-approved collaboration with Oregon Health Sciences University (OHSU) on AI-enabled computer vision monitoring of trauma patients at-risk for delirium.
Inpatient video has massive potential as a new form of patient monitoring and as a new kind of medical data type. One obstacle to overcome to realize this potential is the fact that video generates massive amounts of data, way more than any human can interpret (much less clinicians who are pressed for time taking care of sick patients).
Monitoring patient activity in the ICU is essential for sedation management, identifying agitation, and diagnosing delirium. Despite its importance in ICU care, activity monitoring is intermittent, subjective, and qualitative.
