There is a nursing shortage in the United States. This is due to several factors, including an aging population, a decrease in the number of people entering the nursing profession, and increasing burnout rates, reaching 60% during COVID-19.

One way to address this shortage is to use AI-assisted care. AI can help with several tasks, including scheduling, charting, and patient care. Using AI to assist with some nurses' duties, we can free up nurses to provide direct patient care.

Nursing staff shortage trends

In a 2022 study¹, Dr. David Auerbach and colleagues found that the total supply of RNs had its most significant drop that has been observed over the past four decades. A substantial number of nurses who left the workforce were under the age of 35, and most of them were employed in hospitals.

As the population in the United States continues to age, there is an increasing need for nurses to care for this population. The aging population is more likely to have chronic health conditions that require more frequent and specialized care. In addition, the aging population is also more likely to live alone and be isolated from family and friends, making them more vulnerable to health problems requiring hospital admission.

Impact of nurse staffing on patient care

Inadequate nurse staffing can lead to longer wait times, a decline in the quality of care, and increased medical errors and mortality rates.

In a 2013 study, researcher Heather L. Tubbs-Cooley² found that the likelihood of hospital readmissions increased significantly when more than four patients were assigned to an RN in pediatric hospitals. This suggests that higher patient loads are associated with higher hospital readmission rates.

Helping nurse efficiency with AI

Undoubtedly, nurses are some of the most influential people in the medical field. They are the ones who are responsible for the care of patients and often have to work long hours. However, their job can be made easier with the help of artificial intelligence.

Using AI, nurses can be alerted to potential patient problems sooner. They can also be given information about the best course of treatment. This can save time and ultimately improve patient care. In addition, AI can also automate some of the daily tasks that nurses have to do. This can free up their time to focus on more critical duties.

Addressing inpatient complications with AI

Inpatient complications can be challenging to predict and manage. However, AI can help identify patterns and trends that may be difficult for humans to see. This information can then be used to develop protocols and procedures to reduce the risk of complications.

By analyzing data from past injuries, AI can identify risk factors and develop strategies to prevent future injuries like falls, sepsis shock and more. For example, suppose a specific type of fall is commonly seen in a certain kind of patient. In that case, AI can help develop early mobilization protocols to strengthen recently treated tissue and prevent that type of injury in that population. This information can help nurses tailor their care to each patient and reduce the chances of complications.

Steps to implement AI in hospitals

The first step is to gather data from as many sources as possible, including electronic health records, clinical decision support systems, and patient surveys. This data can train machine learning models to predict patient outcomes and disease progression. Synthetic data can help bridge the gap where patient data is not available.

Next, you must select the right AI technology for the task. There are many different types of AI, each with its own strengths and weaknesses. For example, deep learning is well-suited for analyzing complex medical data. At the same time, rule-based systems may be better for simple tasks like identifying potential drug interactions.

Finally, you need to implement the AI system in the hospital. This requires selecting a vendor who is capable of providing an end-to-end offering, working with your IT staff to ensure that the system can access and integrate the necessary data into existing workflows.

Conclusion

There is no question that the nursing profession is in the midst of a staffing crisis. The need to address this shortage is urgent, and one potential solution is using artificial intelligence (AI) in nursing. AI can help nurses perform their tasks more efficiently and effectively, freeing time to care for more patients. AI can also help to identify and predict staffing needs, allowing hospitals and other healthcare organizations to better allocate their resources. While AI is not a silver bullet for the nursing shortage, it has the potential to help ease the burden on nurses and improve patient care.