Applying AI to Reduce Labor Costs in Healthcare

As median operating margins continue to sink toward -7%, hospitals need new solutions with a quick return on investment. But with so many purported strategies in the mix, how can a senior leader determine which approach will impact the bottom line?

The most effective solution takes aim at the No. 1 budget line – labor – by optimizing the hiring of staff in order to reduce turnover.

Even before the pandemic, healthcare workers had an increasingly tough job. They must comply with ever-increasing administrative and regulatory requirements, carry larger patient loads, and, regularly, work longer hours on under-staffed days and nights.

Full-time staff across the nation are finding 12 hour shifts stretched to 15 hour shifts and 40 hour-per-week jobs becoming 50 hour-per-week. This dangerous trend continues despite numerous studies concluding:

“…too much overtime has been linked to costly problems including medical errors and other threats to patient safety, declining patient satisfaction, clinician fatigue and burnout, depressed staff morale and rising turnover.”

(Health Affairs)

Increasing trends in turnover and vacancy rates

It is no surprise that Advisory Board surveys reveal significant turnover rates for new hires (depicted below). Arena’s data – derived from multiple organizations with more than 500,000 employees combined – corroborates the Advisory Board’s findings, with acute-care facilities’ annual turnover at 35%, and senior living/long-term care facilities’ averaging 65% churn annually. 

As a by-product of staff turnover, over half (55.3%) of all hospitals have a RN vacancy rate higher than 7.5%. This is up from 39.9% in 2015. In addition, RNs increasingly opt for retirement and become traveling nurses.

The future looks even more ominous. By 2026, the U.S. Bureau of Labor Statistics projects the generation of aging baby boomers will create an influx of older patients and a simultaneous retirement of those available to care for them – resulting in a need for 15% more RNs than today. 

Temporary Staff = Costly Solution

Temporary nurses are frequently used by hospitals to cover unexpected staffing shortages. A 2010 study of 2,840 nursing homes found that, across all quality measures, an increase in NA (nursing assistant) agency staff is associated with an increase in quality of care concerns.

The monetary impact of temporary staff is also significant. For every 20 travel RNs eliminated, a hospital saves about $1.4 million. Each percent change in RN turnover will cost/save the average hospital an additional $328,400. (NSI 2019 National Health Care Retention & RN Staffing Report)

Arena’s Analytics AI = Cost Cutting Solution

Analytics Arena helps reverse the negative impact of all these trends.

Recent Data from an Acute Care Health Systems Client

Arena is the only company working across healthcare that delivers measurable value to the talent acquisition process. Its solution analyzes data from multiple sources – recent hires, applicants, organizations, local and regional market factors. It then builds predictive models that identify applicants who will thrive at a specific job, unit, and shift, and under a specific manager. This algorithmic method is far more precise and reliable than traditional screening, and continues to improve over time due to machine learning. 

Without such a tool, healthcare providers make the same mistakes over and over again. 

Humans tend to hire people like themselves. They may be guided by bias – whether unconscious or malicious. 

Assessments may determine whether job candidates have the ability to perform a job function, but cannot reveal whether the individual will be committed to performing the job. 

Hundreds of organizations across the country, including Mount Sinai Health System in New York, RWJBarnabas Health in New Jersey, Regional One Health in Memphis, HCR ManorCare, Sunrise Senior Living, and many other post-acute providers, are using Arena to lower staff turnover, save money and improve patient care.

Arena’s results, like its algorithms, are improving every year. Contact us to learn more.