The healthcare industry is grappling with significant challenges, including staffing shortages, nurse burnout, and the need to manage more acute patients without additional resources. One remedy for these challenges is AI video monitoring, which offers a transformative solution by using continuous patient monitoring to enhance communication and situational awareness of patients and their care.
This innovative technology employs computer vision to constantly observe patients, enabling clinical staff to make well-informed decisions and promptly address changes in patients’ conditions.
As healthcare providers navigate the balance between patient care and financial constraints, embracing AI video monitoring not only helps tackle these pressing issues but also paves the way for a more efficient and positive patient experience.
What is AI video monitoring?
While telemedicine enables nurses, doctors, and other staff members to virtually visit and observe patients, AI video monitoring ‘sees’ what is happening every second in the patient’s room. This capability allows AI to detect and analyze key patterns and actions related to the patient, their care and environment. The system can then alert clinical staff to key changes in a patient’s location (e.g. getting out of bed), movement (e.g. erratic overnight) and actions (e.g. eating). Paired with virtual team members, this enhances the overall quality of patient care and supports healthcare professionals in delivering timely, effective treatments.
Improving hospital efficiencies with AI and video
AI video monitoring systems offer hospitals a powerful tool to create workflows that reduce staff pressure and enhance overall efficiency. By continuously monitoring patients, these systems can become a trusted part of the bedside team – reducing clinician anxiety that comes from the unknown of what is happening with one patient while occupied with others.
The “human + AI” model delivers benefits of strong integration, scalability and flexible staff communications to all patients in the hospital. Rather than replace nursing staff, AI video monitoring systems enable a team-based approach to patient care that leverages a foundation of strong virtual support. In fact, team concepts have been supported by experts as better for patients and staff but have previously been difficult to deploy due to cost and complexity.
Monitoring at-risk patients with virtual teams
AI video monitoring systems can be particularly valuable in monitoring at-risk patients. By working alongside a virtual team that consists of virtual nurses and AI algorithms, patients get the value of near continuous observation and timely intervention of bedside clinical teams.
Virtual nurses review observations made by the computer vision AI (e.g. this patient is lying in bed all day and not moving very much), add additional context from the EHR (e.g. medication changed) and then decide on next steps either directly or in collaboration with the bedside team (e.g. please check in on the patient, or I’ve ordered a pressure bundle for them).
This collaborative approach ensures the bedside team receives accurate and timely information, allowing them to make well-informed decisions regarding patient care.
Enhancing patient experience with AI video monitoring
The implementation of AI video monitoring can lead to a better patient experience in several ways. Through continuous monitoring, patients can feel reassured that their condition is being closely observed and that any changes will be promptly addressed. In addition, the same technology that allows the hospital to observe the patient can be extended to patient families – without further burdening the nursing staff.
Overcoming reimbursement challenges
At first glance, the lack of general reimbursement for AI enhanced video monitoring appears to be a gap in how we currently measure innovation and value in the hospital. Yet it is precisely because the technology is not directly reimbursable that it must independently generate a return on investment for both patients and hospital finances; in turn, this will make it more likely to achieve widespread adoption.
This return takes the form of reduced administrative monitoring; reduction in turnover and burnout; impact on travel nursing levels; and patient satisfaction scores. It also can impact patient care metrics related to never events, like falls or pressure injuries, for example. In fact, falls alone represent the largest category of preventable harm in the hospital – costing billions of dollars each year. Further, the ROI ensures alignment of clinical and financial drivers from the onset and ultimately ensures the long-term ascent of AI video monitoring as a strategic component of hospital care delivery.
Conclusion
AI video monitoring presents a promising solution to some of the most pressing challenges faced by hospitals today. Balancing the scope of patient care and financial constraints of resourcing may be the paramount question for hospitals over the next decade.
By harnessing the power of computer vision and AI technology, hospitals can improve efficiencies, support nursing staff, monitor at-risk patients and foster a better patient experience. Embracing this new frontier will allow the healthcare industry to provide exceptional care while addressing staffing challenges and reducing costs.
