Artificial intelligence (AI) is transforming the way healthcare operates, from front-office tasks and financial workflows to clinical decision-making and executive strategy. In this article, we’ll focus on the way AI enables efficiencies and advancements in nurse staffing. Read on to discover the key benefits of AI for nurse staffing and get tips for incorporating AI into the way you manage your nurse workforce.  

Table of Contents

• How is AI transforming the nurse staffing industry?
• What are the potential benefits of AI for the nurse staffing industry?
• Should my facility be utilizing AI in our nurse staffing operations?
• What is the right AI solution for my organization?
• Works brings AI to your nurse staffing practices

AI is a broad category of technology-enabled cognitive processing that includes machine learning, deep learning, and generative models—all of which have potential to influence the nursing sphere. We want to reinforce up front that AI is not a substitute or replacement for human cognitive processing. Rather, it is a supportive tool that can be massively helpful to humans, when designed and implemented correctly.   

AI serves a wide array of purposes in nurse education, operations, and clinical practice, but in this article, we will focus on its application to nurse staffing and management. It’s well known that the pandemic transformed nurse staffing forever, exacerbating existing issues such as short staffing and spurring new ones like skyrocketing travel labor costs. Today, nurse turnover rates remain far higher than pre-pandemic levels, as demonstrated in the following chart from the 2023 NSI National Health Care Retention & RN Staffing Report. The nurse vacancy rate is also dangerously high, with over 75% of hospitals reporting rates higher than 10%.  

Ensuring a sustainable nurse staffing market for the future requires innovation, and AI has emerged as an essential tool to comprehensively reinvent nurse staffing and repair five key staffing processes in nursing.  

1. Compensation

‍AI can help you determine nurse payment rates and nurse shift pricing by collecting and considering data on multiple variables: 

• Historical patient data (e.g., volume, admissions, census): determines seasonal patterns and demand throughout the year  
• Staff preferences: shows shift desirability and available staff supply 
• Real-time monitoring: takes in current situational information  
• Performance: accounts for importance of quality metrics and patient outcomes 
• Market comparisons: benchmarks against local and national staffing compensation rates 
• Associated costs: factors in components such as overtime expenses, agency fees, and penalties for understaffing 

The algorithmic and analytic capabilities of AI-powered nurse staffing turn information into insight, allowing organizations to better determine base pay for typical shifts, design incentives for times of low supply or high demand, and adequately reward excellent performance.  

2. Scheduling‍

AI-powered platforms can use historical data to predict scheduling needs AND use staff information and preferences to match available nurses with open shifts based on their skills, certifications, and availability. AI will also factor in optimal nurse-to-patient ratios and current patient acuity to recommend a well-balanced schedule.  

3. Recruiting

‍Staffing is not all about filling shifts; it is about filling them with the right people for your organization’s needs. AI tools can help you find the best-fit staff for your organization by automating various parts of resume screening, interview scheduling, skill assessment, and other recruitment processes. It can also help remove bias from these processes.

4. Retention

‍By analyzing data on nurse workload, scheduling patterns, and job satisfaction surveys, AI systems can flag potential burnout risks and suggest strategies for workload redistribution, scheduling optimization, and culture shifts.  

5. Performance

‍AI-powered systems can monitor and analyze nurse performance metrics, such as patient outcomes, medication administration accuracy, and adherence to best practices. These tools can help identify areas for improvement, provide feedback, and support ongoing professional development for nurses.

The changes spurred by AI nursing are meaningful and measurable. Organizations leveraging AI to support nurse staffing see impressive results. While this is not an exhaustive list, these are six of the top results of infusing AI in nurse staffing practices:

1. Efficiency: Streamlining and automating tasks including screening, scheduling, and shift assignments saves time and reduces manual effort, allowing organizations to operate more efficiently.  

2. Accuracy: With a better grasp of supply and demand, organizations can better anticipate the required staffing levels for different shifts, reducing the likelihood of understaffing or overstaffing situations.  

3. Clinical outcomes: By using demand forecasting to set shifts and scheduling assignments, organizations can ensure patient safety, augment access to care, improve quality of care, and advance community health overall.  

4. Satisfaction: Using AI to achieve better compensation structures, recruiting procedures, and retention management helps improve overall satisfaction among nursing staff. When nurses are feeling happier, more fulfilled, and less burnt out, everyone wins—patients most of all.  

5. Cost: AI helps organizations more effectively balance supply and demand, determine appropriate payment, and allocate resources more wisely—all of which are critical to preserving financial health and limiting waste.  

6. Culture: When organizations have the right clinicians in the right place at the right time and for the right price, they are building a strong culture of collaboration. When staff are part of a positive, supportive environment, turnover rates can also improve significantly.  

AI can be a useful tool for nurse staffing and dynamic pricing in healthcare regardless of size, specialty, or location. It can also support the agencies that provide nurse staffing services to healthcare facilities.  

Large Hospitals and Multi-Family Healthcare Systems

Larger hospitals and multi-facility healthcare systems benefit from AI’s ability to consolidate, coordinate, and streamline staffing practices and procedures across many departments or sites of care. These organizations typically have massive amounts of data to sort through, so AI is especially impactful to reduce manual labor, automate basic processes, and create far-reaching efficiencies.  

Hospitals and Facilities in Rural or Underserved Areas

Organizations in rural locations or underserved areas are often stretched very thin on time and resources—and have more trouble than most with nurse recruitment and staffing. AI can aid in addressing these challenges by predicting demand, optimizing resource allocation, and minimizing unnecessary spending.   

Speciality Care Facilities  

A few areas particularly prime for AI support include specialty care facilities, such as oncology, critical care, or pediatric care because they often require nurses with specialized skills and certifications. AI can assist in matching nurses with the appropriate expertise to these specialized units, ensuring the availability of qualified staff and maintaining high-quality care. 

Internal and External Nurse Staffing Agencies

Finally, both internal and external staffing agencies can also find immense value in AI, as it can assist in matching available nurses with open shifts, optimizing assignments based on skills and preferences, and streamlining scheduling processes, resulting in more efficient and effective nurse placements. 

While many organizations can benefit from applying various AI solutions to staffing processes and procedures, AI is not one-size-fits-all. Organizations must fully assess their own requirements, resources, and potential challenges—as well as the quality and viability of available solutions—before implementing AI to address staffing needs.  

AI and machine learning are transforming nursing, but not all AI solutions are created equal. AI experts from MIT wrote in a 2023 article, “The quality of an AI tool — and the value it can bring your organization — is enabled by the quality of the ground truth used to train and validate it.” Be sure to complete a rigorous evaluation of any AI solution you consider and note how it is trained and validated.  

Questions to ask during your evaluation process should include: 

• How does the AI solution integrate with our existing staffing processes and systems? Will it require significant changes to our workflows or infrastructure? 
• What data sources does the AI solution utilize, and how does it handle data privacy and security? 
• Can the AI solution effectively handle the unique characteristics of nurse staffing, such as varying certifications, shift preferences, and skill requirements? 
• What level of customization and flexibility does the AI solution offer? Can it adapt to our specific staffing needs, policies, and preferences? 
• What is the implementation process for the AI solution? How long does it take to set up, train, and integrate into our operations? Are there any potential disruptions during implementation? 
• How user-friendly is the AI solution? Will our staff require extensive training or technical expertise to utilize and navigate the system effectively? 
• What level of technical support and maintenance does the AI solution provider offer? Is there ongoing support available for troubleshooting, updates, and system enhancements? 
• Does the AI solution provider have experience and expertise in the healthcare and nurse staffing industry? Can they provide references or testimonials from other clients? 
• What is the scalability and future development roadmap for the AI solution? Can it adapt to changing needs, evolving technology, and industry advancements? 
• How does the AI solution address ethical considerations and biases in staffing decisions? Is there transparency in the algorithms and decision-making processes? 
• Can the AI solution integrate with other healthcare systems, such as EHRs or workforce management systems, to ensure seamless data exchange and interoperability? 
• What are the potential risks and challenges associated with implementing the AI solution? How does the provider mitigate those risks and support a smooth transition? 

You will have additional questions and considerations based on your specific needs, regulations, communities, and resources. Engage stakeholders across your organization when determining your specific goals and expectations of potential AI solutions.

Cultivating and maintaining operational and sustainable nurse staffing systems requires innovation. AI has already demonstrated its immense potential to overcome persistent challenges in nurse recruitment, retention, compensation, scheduling, and other staffing processes.  

Learn how your organization can leverage Works’ artificial intelligence engine to modernize and automate the way you manage every level of your clinical workforce. Works’ shift matching technology can help you match open needs with the most qualified, cost-effective, interested, and available workers. The result is less administrative burden on your staff, a more engaged and empowered clinical workforce, and reduced total labor cost and premium spend for your organization.

Request a workforce consultation today to learn how Works can help you!