Integrating artificial intelligence (AI) into healthcare transforms how frontline workers, especially nurses, experience their day-to-day responsibilities. As discussed by Mercy's Chief Nurse Executive, Betty Jo Rocchio, leveraging AI technology has yielded significant benefits, including improved workforce retention, enhanced efficiency, and reduced cognitive load. However, this journey has not been without its challenges. The rewards are evident, but the process involves overcoming many obstacles, both technical and organisational. A keynote at the HIMSS AI in Healthcare Forum explored the critical elements of Mercy's AI transformation and its impact on nursing staff, focusing on mobile charting, automated credentialing, and the use of AI to streamline handoffs.
A Technology-Enabled Workforce: The Need for Innovation
The healthcare sector faces persistent challenges, including a growing gap in skilled clinical workers. According to HIMSS President Hal Wolf, this challenge will only intensify over the coming years, with an expected global shortage of 18 million clinicians by 2035. In response, Mercy has placed a significant emphasis on using AI to improve the work environment and retain staff. Rocchio highlighted that technology reduces workflow friction and improves nurse satisfaction.
Mercy’s approach to addressing these challenges centres on streamlining workflows and improving the work environment through AI. From flexible work schedules to mobile-based charting, Mercy uses technology to empower its nursing staff, enabling them to work more efficiently while maintaining a better work-life balance. AI has not only improved efficiency but also increased workforce retention, helping Mercy save $52 million in talent retention and achieve a 17% increase in nurse efficiency. This technology-driven strategy underscores the importance of addressing healthcare’s skilled worker shortage with innovative tools.
Reducing the Cognitive Load: Enhancing Workflows and Environment
One of the significant issues healthcare systems face is the cognitive overload nurses experience due to excessive administrative tasks. Nurses can spend up to 240 minutes per shift working within electronic health records (EHRs), adding mental strain and contributing to burnout. Rocchio pointed out that reducing this cognitive load is essential to keep nurses at the bedside without driving them away due to overwhelming tasks.
Mercy’s digital transformation includes implementing Epic’s mobile-first solution, Rover, to minimise the time nurses spend on desktop EHRs. By enabling nurses to chart and access critical patient information from their mobile devices, Mercy has decreased the time nurses spend on non-patient-facing tasks, thus improving their efficiency. Additionally, AI-enhanced systems have been introduced to streamline patient handoffs from emergency departments to inpatient units. These systems scrape across various EHR elements, providing nurses with the most critical information at their fingertips, further reducing cognitive load and enabling them to focus on patient care.
Automating Credentialing and Scheduling: Creating a Resilient Workforce
Another significant aspect of Mercy’s AI transformation is the development of an automated nurse-credentialing system. This system has been crucial in reducing the time and effort required for staffing and scheduling by 25% while allowing nurses to architect their shifts based on their preferences. In the past, nurse managers expressed concerns about filling open shifts, but the data has shown that nurses will voluntarily pick up available shifts when given control over their schedules.
This automated system leverages AI to optimise staffing, addressing the supply-demand challenges that have long existed in healthcare. By removing much of the administrative burden related to scheduling, Mercy has enhanced its workforce’s flexibility and created a more resilient staffing model. This, in turn, has contributed to increased retention rates and decreased the overall stress on nurse managers, further demonstrating the benefits of adopting AI in healthcare.
Conclusion
Mercy’s use of AI to improve the experience of frontline staff, particularly nurses, demonstrates the potential rewards of embracing innovative technology in healthcare. Despite the challenges, including the initial resistance from nurse managers and the need to clean up existing processes, the results have been overwhelmingly positive. From reducing cognitive workload to enhancing workforce retention and efficiency, AI has enabled Mercy to create a more resilient and engaged nursing staff. As the global shortage of skilled clinicians continues to grow, healthcare systems must prioritise the implementation of AI and other technologies to build a sustainable, technology-enabled workforce. In the long run, the pain of adopting AI is far outweighed by the rewards of a more efficient, effective, and satisfied healthcare workforce.
Source Credit: HIMSS
Image Credit: iStock
