What's Really Behind the Nursing Shortage?

Introduction: AI is Coming

In an annual meeting to an audience of over 40,000 people, medical records software company, Epic Systems, announced a plethora of new AI technologies the company has in development, including numerous applications for ChatGPT-like generative AI. Epic’s software is used throughout thousands of healthcare facilities, primarily as a system for electronic health records (i.e. patient charts). The company has over 100 AI projects in the works with many set to launch in the next few years and some launching immediately with a new open source code already being made freely available for healthcare companies to use in order to assist with the validation process.

Epic isn’t the only healthcare company shifting its focus towards AI. Even public sector healthcare centers are developing their own AI software to assist not only with medical records but also for predictive staffing and patient care models. Many healthcare companies are looking to AI to improve ‘operational efficiency’ and cut costs, namely through replacing the workforce. Nearly 1 in 5 healthcare CEOs believe that generative AI will help replace up to 5% of their workforce, which is often touted as a necessary solution to the problem of a “nursing shortage”.

How many times have you heard that there is a “nursing shortage,” especially since the onset of the COVID-19 pandemic? Even the American Nurses Association, a professional organization for nurses and their bosses, claims there is a nursing shortage caused primarily by increasing demand for nurses outpacing supply, and nurses are retiring at a rate that is outpacing the number of new nurses. Of the over 5 million actively licensed registered nurses, only 89% are employed in nursing, meaning there are over a half a million registered nurses holding active licenses that are not currently working in the nursing field.

Throughout the healthcare industry, AI is being viewed increasingly as a beacon of hope, one which will reduce the historically high healthcare costs by improving efficiencies, and address the nursing shortage that healthcare CEO’s are portraying as a natural phenomenon, out of their hands. But this isn’t the whole story, to understand why AI has become such a popular ‘solution’ to the “nursing shortage,” let’s take a look back through history, to see the true causes of the “nursing shortage” and why the for-profit hospital industry is pushing AI solutions so heavily.

History of Nursing Shortage

A “nursing shortage” is, more or less, any time there is a significant demand for nurses. Arguably, the first recorded “nursing shortage” in the USA started 1936, and this narrative has taken one form or another since then. . “During the 1930s, increased hospital use, more technologically complex patient care requirements, and a reduction in the working hours for nurses all necessitated an increased number of nurses to deliver bedside care.” As a result, hospitals attempted to implement two main solutions:

1. Increasing the number of students admitted to nursing schools and shortening the educational period required for nurse training.

2. Increase the use of less educated and trained personnel either to substitute for or to extend the work of professional nurses.

During this period patients saw an increased role of nurses aides and the creation of a Licensed Practical Nurses (LPN). An LPN is a nurse who can do some of the tasks of an RN, but require less training, and in most states work under the license of an RN or MD. In addition to the creation of LPNs, patients saw an increasing amount of their care being completed by nurse aides. Because nurse aides were unlicensed at the time, hospitals felt free to use them as they saw best. Although intended to extend the work of nurses by serving in an assistive capacity, both LPNs and nurse aides were frequently, and often inappropriately, used as less expensive nurse substitutes. The main solution to the nursing shortage of the 1930’s and 40’s was to both deskill nurses by expanding the work of lower-paid wage workers, and to reduce the overall need for RN’s.

Studies into nurses’ working conditions, pay and experience in the 1920’s and 30’s documented consistent “poor working conditions and inadequate compensatory schemes.” Notably employers of the past chose the solutions above rather than increasing wages or improving working conditions. These findings were consistent in 1947 when the United States Department of Labor conducted a study on The Economic Status of Registered Professional Nurses, which came to the same conclusion. In many ways, the nursing shortage of the 1930’s and present day are mirror images of each other. Both had documented poor working conditions, poor wages, and yet employers decided to find a third route to solve the problem of the nursing shortage. In the 1930’s they created LPNs and nurses aids (CNAs), as well as increased the number of nursing school programs and shortened the time frame which it took to complete nurse training. In 2024 the “solution” is instead Artificial Intelligence.

The modern day “nursing shortage” made the news during the COVID-19 pandemic. In 2022, almost 100,000 nurses left the profession, and in 2023 more than half of nurses reported an increase in their workload during the COVID-19 pandemic. Similarly about half of nurses reported feeling “emotionally drained”, “used up”, “fatigued” and “burned out”. The extreme burnout that nurses feel on the job, combined with wages that aren’t keeping up with inflation, it is no wonder why in 2023 one in four nurses said they plan to leave the profession within the next 3 years.

Poor working conditions and decreasing real wages explain why in 2024 there are at least half a million nurses with active licenses who are choosing to no longer work as a nurse. There is a problem retaining nurses and filling open positions, that much is true, but it is not the result of a natural phenomenon. It is the result of poor working conditions and decreasing real wages, both things that can be addressed if hospital executives were serious about attracting more nurses and keeping them, but they aren’t. In fact, since the pandemic and current "nursing shortage," hospitals have made record profits, which gives us a window as to why hospital executives aren’t very interested in improving working conditions or increasing wages, but instead promoting AI. Just as hospital executives a century ago looked to the LPN role to deskill and replace RNs, our 21st century executives are looking to AI with the same goals in mind .

Recent Developments: Consolidation and Profit Motive Over Patient Care

Instead of addressing the burnout and stress experienced by their staff during COVID-19, hospital executives focused on consolidating their power and wealth through mergers and acquisitions. Many healthcare systems were forced to drastically change the flow of care and even cancel elective surgeries during the COVID-19 pandemic, and larger hospital systems took advantage of this by buying up the smaller ones. The rate of mergers and acquisitions had already been on steady incline for decades prior to the pandemic, with 1,164 mergers took place among the country's 5,000 acute-care hospitals between 2000 and 2020 and more recently, over 65 mergers were announced in 2023 alone. Often, the smaller institutions are being sold to larger ones due to ‘financial distress’ caused by increased operating expenditures. This is despite hospitals claiming, on average, a 1% month over month increase in total revenue. As the larger hospital systems consolidate their ownership and wealth, hospital ownership is now approaching monopoly levels meaning there are fewer companies owning an increasingly greater proportion of the hospitals. The rate of market monopolization is worse in some states, as of 2022, the three hospital corporations held almost 70% of the healthcare market in Colorado.

As fewer companies own a greater proportion of the healthcare market, they have more power to set the prices without any benefit to the patients. When hospitals consolidate, there is less competition between hospitals and less diversity in options for the patients, resulting in more power and control to set a high price for care without significantly improving the quality of care. Hospital mergers have been associated with lower patient care quality scores and increased prices.Cross-market hospital acquisitions have been associated with a nearly 13% price increase at the acquiring hospital and a $204 million increase in national health spending after each merger.

Unfortunately, neither the patients or the healthcare workers are reaping the benefits of higher costs, in fact one study found reduced wage growth following mergers. So, while the quality of care worsens, prices increase, and wage growth is reduced, who is actually benefiting from these mergers and acquisitions? Hospital CEOs - who often already make hundreds of times that of their employees - get higher salaries when they lead larger healthcares systems. Although CEOs rarely share their wealth with the workers they rely on to make the hospitals run, they do create new executive roles and many of those roles are focused on technology and Artificial Intelligence. Most companies, including those in the healthcare field, have adopted a new C-Suite role - Chief Artificial Intelligence Officer (CAIO) - with the main focus of adopting new technologies like AI to increase productivity of staff and increase profits.

Current Applications of New Technologies, Including AI

The nursing profession is familiar with technological changes - from the replacement of paper charting with electronic health records (EHRs) to the adoption of digital monitors - sometimes these technologies improve patient care and nurses’ workload. On the other hand, the profit-driven healthcare industry will always seek ways to utilize technology in order to reduce labor costs, often under the guise that they will solve the alleged nursing shortage or improve accessibility to care.

Take for instance, Uber for Nurses, which is startup that claims to allow nurses and other healthcare staff to “be in charge of their own schedules,” by essentially gigifying the nursing industry in the same way Uber gigified the passenger driver industry. Companies like Uber for Nurses promote flexibility and independence by turning the nurses into 1099 employees with no benefits or protections. In contrast to W-2 employees, 1099 employees are considered to be independent contractors, which are notoriously difficult to organize into unions, and places the liability onto the workers. Schemes like “Uber for Nurses” will take advantage of the burnout nurses are facing while reducing their power to organize collectively for better conditions, which could be detrimental to both workers and patients in the long run.

New technological developments may sometimes seem innocuous at first glance, but upon investigation many of these new technologies are not only built to exploit workers, but may exacerbate already large inequities. One example of this is in the field of machine learning and AI algorithms to diagnose, predict, and treat patients. AI algorithms rely on large datasets to analyze and predict things like the future of a patient’s status or even the need for staff in a hospital, however, given disparities in access to health and individual human biases, these datasets are highly susceptible and prone to various forms of biasness. One study points out that “AI systems may reflect and amplify human bias, and reduce the quality of their performance in historically under-served populations such as female patients, Black patients, or patients of low socioeconomic status.” Similarly, research, development, and implementation of AI technologies often have a high price that not every healthcare institution can afford, which will further exacerbate the disparities in care provided to certain communities: “The AI 'have-nots' will be health systems like county hospitals, federally qualified health centers, and rural hospitals that lack the infrastructure or expertise to deploy these technologies effectively, or that do so without fully understanding their capabilities and limitations." Until healthcare is accessible to all, AI will continue to exacerbate inequities across underserved populations.

A Vision for AI in Healthcare

While there are legitimate reasons for us to be cautious about new technological developments in healthcare, artificial Intelligence and machine learning are exciting new technologies that have the potential to positively impact the lives of workers and patients around the world. Technology has been integral in improving the lives and outcomes of patients at different points in history. From the invention of antibiotics, vaccines, antiseptics and heart surgery, to real-time monitoring and MRI image post-processing in the hospital. Historically, when technological advancements coincide with healthcare industry profits, we have seen technology rolled out vigorously. Much like implantable continuous glucose monitors.

A person with type 1 diabetics can be required to check their blood sugar four to ten times a day, and depending on the results, calculate and inject themselves with insulin. From a young age, this practice becomes a time-consuming and necessary daily task. However, in 1999 researchers introduced the first implantable glucose monitor, easing the lives of 2.4 million of people with diabetes who use implantable continuous glucose monitors who no longer need to do a self-check by finger lancet multiple times a day.

The Continuous Glucose Monitoring Market is expected to reach $31.41 billion by 2031. If this life improving technology wasn’t as profitable as it is, would 2.4 million people have access to it? The history of hospital acquired infections (HAI’s), suggests not. Hospital acquired infections were rapidly rising for decades, until in 2013 the Centers for Medicaid Services tied hospital reimbursement to the reduction of HAI’s. Since then, there has been a rapid decrease in hospital acquired infections. However, in 2024 1 in 31 hospital patients still have a HAI, and a 2018 study found that while hospitals have the capacity to reduce HAI to near zero, they will not because it is simply not profitable enough.

There is a great potential for AI to be used in the rapid invention of new drugs for difficult to treat conditions, but it is creating a ‘double-edged sword’ for pharmaceutical companies due to the difficulties arising in getting patents for their new, AI-generated drugs. What positive, life-altering, drugs have not had the success that continuous glucose monitors have because pharmaceutical companies couldn’t patent them? Like any technology, artificial intelligence has the potential to improve the lives of patients, workers and society at large. But will we see the full potential of this emerging technology realized if left in the hands of the for-profit healthcare executives? As we’ve seen historically if it is left up to them, we will see more of what we have already seen; healthcare created crises like the present day “nursing shortage,” being leveraged to introduce new profit-driven technology, many times implemented at the expense of quality patient care, to simultaneously increase profits while de-skilling and replacing workers.

Conclusion

As a society and as workers, we must now decide. Should healthcare be a for-profit industry? Lining the pockets of owners and bosses? Or, should healthcare be a human right, where innovation and resources are put towards maximizing the social good, rather than profit for a few?

Workers are on the leading edge of this struggle. Not only are workers the ones creating the technological advancements that have the potential to better the lives of millions of people, healthcare workers are fighting for the rights of their patients and themselves to live dignified lives. Union workers enjoy higher pay and better working conditions than their non-union colleagues. Collective action by unionized workers has proven to be an effective vehicle for empowering workers to demand protections against corporate use of new technologies to replace workers. During the “hot labor summer” of 2023, when both the WGA and SAG-AFTRA went on months-long strikes, society witnessed the lengths unionized workers in the entertainment industry had to go through to defend their professions from the use of AI to replace workers, and ultimately they won. Similarly, in the healthcare industry, unions like California Nurses Association, with their AI Bill of Rights, are leading the way to ensure AI is introduced to the benefit of patients and workers. This includes rights to safety, privacy and ensuring workers retain their collective rights to advocacy for worker and patient rights. AI is advancing at a rapid speed, and workers need to be organized and ready to assert themselves into the rollout of these new technologies.

Ultimately, so long as we have for-profit healthcare, hospitals will work within the imposed confines to maximize profits rather than the well-being of workers and patients. We saw that with hospital acquired infections. Ultimately, removing the profit motive from healthcare, and empowering workers to control over their workplace, is the only way to ensure AI and all technology is implemented to benefit the many rather than enriching the few.