How Generative AI Can Alleviate the Nurse Staffing Shortage

By Lora Sparkman, MHA, BSN, RN, Partner, Clinical Solutions, Relias
X: @relias

The nurse staffing shortage crisis is reaching a new high, increasing pressure on current nurses, prospective nurses, and the healthcare system as a whole. Nursing school enrollment is down as entry-level baccalaureate nursing programs experienced a 1.4% decline last year. Similarly, master’s nursing programs and Ph.D. nursing programs experienced declines of 9.4% and 4.1%, respectively. With fewer nurses entering the profession, veteran nurses are experiencing worsening labor conditions, causing heightened stress and burnout.

Due to these issues, 29% of nurses across all license types considered leaving the profession post-pandemic in 2021. Given the growing demand for care and current state of the industry, 1.2 million new nurses will be needed by 2030 in order to address the current shortage and meet patient needs. In addition to increasing the pressure on remaining nurses causing many to leave the workforce, inadequate staffing ratios jeopardize quality of care and patient safety. Unfortunately, the worst of the nursing shortage is yet to come, and it is imperative for healthcare organizations to prioritize nursing recruitment, retention, and assuring and growing competency efforts to ensure the industry is equipped for future patient needs.

Like many other industries experiencing the pains of labor shortages, the healthcare industry is embracing new technology as a potential solution. Specifically, healthcare organizations are adopting generative AI, a form of artificial intelligence that learns patterns from existing data to produce unique content ranging from text and images to other forms of media. The innovative tool is specifically designed to address challenges resulting from labor shortages.

Technology can help alleviate nurses’ administrative burden, allowing them to focus their time and energy on patient care. In addition to reducing stress, generative AI can make training for new nurses more personalized, streamlining the onboarding process and helping them achieve clinical competency faster. Not only does this technology improve learning outcomes, it attracts a younger demographic of nurses who are enticed by innovation and modern approaches to training and care delivery.

Here are a few ways generative AI-assisted training content can combat the nursing shortage:

Reduce the burden on on-site nurse educators

As a result of workforce shortages, healthcare organizations employ fewer nursing educators, many of whom already bear heavy workloads. Among those considering leaving the profession, 55% of nurses said they would be motivated to stay if they had more reasonable workloads. However, many organizations still manage training assignments manually with nurse educators who evaluate learners’ performances to determine the best training approach for each. This archaic process is extremely time-consuming and unrealistic given staff numbers. Nurse educators are burned out and new nurses aren’t able to transition into their positions until they receive proper training.

Technology can modernize and expedite this process. Research suggests that AI can support or augment 40% of working hours for healthcare workers. The use of generative AI can reduce the burden on nursing educators by generating lesson plans automatically based on assessment results, saving nurse educators’ time and swiftly providing new nurses with training.

Improve competency with personalized learning

It can take months and thousands of dollars to properly train and onboard new nurses. With the estimated cost of nurse turnover between $40,200 and $64,500 per nurse, it is vital to hospital operations that nurses receive thorough yet efficient onboarding to ensure they are best prepared for their roles as soon as possible and will stay at the organization long term. With generative AI, the processes of evaluating performance, generating training, and tracking completed tasks are all automated, ensuring that costly training is as productive and comprehensive as possible.

In the absence of technology, nurse educators are responsible for tracking these items manually in spreadsheets or binders, slowing down the assessment and learning process. Without these barriers, new nurses have access to a timely onboarding process to help build the skills and confidence needed to successfully perform their tasks and responsibilities. Generative AI training can even be used as ongoing competency training for more experienced nurses to refresh and expand their existing skills.

Every learner has different strengths, interests, and learning styles which are often overlooked when educational content is too generalized. Generative AI can tailor educational content to individual learners based on previous evaluations and performance metrics. A learner can take an assessment to determine his or her clinical competency and based on the score and overall job performance, generative AI will produce tailored, automatically-assigned recommendations for learning content that can help nurses gain the knowledge needed to be productive and clinically competent.

Attract new nurses with innovation

New nurses are looking for roles at healthcare organizations that promote innovation, with 92% of Gen Z workers eager to use generative AI. Healthcare organizations who use outdated, low-tech, unproductive approaches to care and education will be less attractive to nurse candidates and have trouble retaining employees. However, only 6% of healthcare organizations have a generative AI strategy plan in place. Although generative AI offers many opportunities for recent nurse graduates to make their learning more immersive, self-directed, and experience-driven, many organizations have yet to adopt it. With the power technology holds in attracting and retaining staff, it is a valuable asset for any healthcare organization to adopt.

Technology is continuing to modernize many aspects within the healthcare industry. Generative AI is not replacing healthcare workers, but supporting them in their roles by alleviating administrative burden, reducing burnout, and preparing them for their roles. Healthcare organizations must listen to their employees to address their needs, interests, and help them best serve patients.