3 Essential Components for AI and Virtual Nursing Adoption

Adopting virtual nursing and AI starts at the bedside, say these nurse leaders.

AI and virtual nursing aren’t just on the horizon for many health systems, they've arrived.

Both AI and virtual nursing come with challenges with staff buy-in and infrastructure, and pose challenges to patient safety and nurse workflows. However, as these technologies become industry standards, CNOs and other healthcare leaders must develop strategies to overcome obstacles and ensure the sustainability of the technology.

The Winning Edge for Overcoming Key Barriers to Virtual Nursing Adoption webinar included three experts on the subject: Laura Rashleger, VP Nursing Operations and Virtual Nursing at Advocate Health, Yuri Mykoo, SVP and CNO at Tampa General Hospital, and Dr. Christine Gall, CNO at Collette Health.

The panel included three key points about AI and virtual nursing adoption and implementation.

Beginning at the bedside

According to the panelists, the most effective approach to adopting virtual nursing and AI starts at the bedside. Rather than making assumptions, CNOs should first ask their nurses and frontline staff what pain points they experience in their daily workflows that could be addressed with technology. Bedside nurses will know what they need and where the gaps in their workflows are, and it's critical that leaders tune into those insights.

CNOs must also consider patients and how these technologies will have an impact on their communities outside of the hospital. Virtual nursing and AI provide many opportunities for care outside the hospital setting, including hospital at home programs. Patient safety must also be a top priority for leadership.

Next, CNOs should focus their vision and clearly outline their implementation strategy, and communicate that clearly to their teams. Establishing early wins can help with adoption as well, so that staff can further understand the 'why' behind the change. Leaders should rely on staff champions who are early adopters and can help build trust and confidence throughout the rest of the workforce.

Overcoming skepticism

One of the biggest barriers that CNOs face with any introduction of new technology is staff skepticism. When it comes to virtual nursing and especially AI, there is a healthy fear that the technology will create more work, or that it will eventually become a replacement for nurses. According to the panelists, CNOs must listen to staff concerns and ease staff worries with clear strategies and defined metrics. Transparency about outcomes is key, in both positive and negative scenarios.

Additionally, CNOs should focus on change management and communicating the reason behind why the technology is being added to the workflow. Ideally, AI and virtual nursing should take away documentation burdens and give nurses more time back at the bedside, and it should allow nurses to practice at the top of their license.

Defining ROI

Lastly, it's essential that CNOs and other leaders have defined metrics for measuring the success of virtual nursing and AI in their health systems, the panelists explained. The metrics should be people-focused and center on how the nursing workforce is doing, before and after adoption.

The panelists recommended measuring retention and turnover, readmissions, length of stay, throughput, and nurse-sensitive indicators. Efficiency metrics like decreased documentation time and discharge time can also be useful to measure productivity.

From the patient perspective, CNOs should measure patient safety, experience, and outcomes, along with operational metrics that might point to potential harm. Ultimately, the goal is to implement virtual nursing and AI in a manner that doesn't exacerbate problems or create new ones in other areas, and keeping track of data is necessary to avoid those outcomes.

This webinar is sponsored by Collette Health.