Practice Management News

Clinical Labor Costs Increased by $24B During Pandemic

Yearly clinical labor costs are soaring for hospitals and health systems desperately seeking qualified talent to treat rising COVID-19 cases and other patients.

Clinical labor costs rise

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By Jacqueline LaPointe

- Hospitals and health systems are spending about 8 percent more per patient day on clinical labor costs compared to pre-pandemic times, according to a recent analysis from Premier Inc.

For the average hospital with 500 beds, that means clinical labor costs have increased by about $17 million since the start of the pandemic. In total, the expenses have risen by $24 billion this year for qualified clinical labor compared to a pre-pandemic baseline in 2019, Premier reported using data from its PINC AI platform.

The platform included healthcare workforce daily data from approximately 250 hospitals, bi-weekly data for 650 hospitals, and quarterly data for 500 hospitals, representing most geographic and demographic segments. The workforce data only included points related to clinical employees working in the emergency department, ICU, or nursing areas.

Hospitals and health systems are spending more on clinical labor due to overtime and agency staff costs, explained the analysis’ authors, including Michael J. Alkire, president and CEO of Premier Inc.

“Hospital employees are more exposed to COVID than many other workers, with quarantines and recoveries requiring use of sick time,” Alkire et al. explained. “PINC AI data shows that use of sick time, particularly among FTEs in the intensive care unit, is up 50 percent for full-time clinical staff and more than 60 percent for part-time employees when compared to the pre-pandemic baseline.”

Additionally, the analysis found that clinical stuff turnover reached record levels during the pandemic, especially in the emergency department and ICU, as well as among nursing staff. The annual rate of turnover across the three areas increased from 18 percent to 30 percent, according to the analysis.

Analysis authors warned that clinical staff turnover may continue to increase as organizations implement COVID-19 vaccine mandates.

Several hospitals and health systems have already required their staff to get vaccinated against the virus. However, one facility in the Midwest reported losing 125 employees, the analysis found. Another facility in New York had 90 staff resign after implementing the mandate.

Healthcare organizations are worried that COVID-19 vaccines mandates will exacerbate healthcare workforce challenges, such as labor shortages. But soon, most organizations will not have a choice but to require the vaccine, as the federal government plans to tie vaccine mandates to Medicare and Medicaid participation. Nursing homes are already required by CMS to mandate the vaccine.

“While a minority of the overall workforce, losses of even a few employees during times of extreme stress can have a ripple effect on hospital operations and costs,” the analysis stated.

The mandates will also impact staffing agencies, which hospitals and health systems have leaned on during the pandemic to fill clinical labor gaps. Staffing agencies are predicting up to a 5 percent resignation rate once the vaccine mandates take effect, Alkire et al. reported.

The healthcare workforce challenges are not new to hospitals and health systems, especially considering how long they have been fighting COVID-19. However, some organizations have found new ways to overcome the challenges, including leveraging technology to predict staffing shortages and get ahead of workforce issues.

One of those health systems was Nebraska Medicine. The organization took a look at its productivity data using an analytics tool to identify workforce trends and solve workforce disruptions caused by the pandemic. For example, Nebraska Medicine was able to pull from areas that were experiencing lower productivity during the initial COVID-19 surge and move certain staff to areas expecting high productivity because of the surge.  

Premier Inc. also found that predictive models for staffing can be extremely accurate, resulting in better support for hospitals and health systems.