Analysis recently performed by PINC AI, the technology platform of the Charlotte-based Premier Inc. health alliance, has determined that hospitals and health systems in the U.S. are paying $24 billion more per year for qualified clinician labor than they did prior to the onset of the COVID-19 pandemic; and that, as of late September, overtime hours were up 52 percent over pre-pandemic levels.
As noted in an October 6 press release posted to Premier’s website, “As the delta variant pushes COVID-19 caseloads to all-time highs, hospitals and health systems across the country are paying $24 billion more per year for qualified clinical labor than they did pre-pandemic, according to a new PINC AI analysis. The analysis found that clinical labor costs are up by an average of 8 percent per patient day when compared to a pre-pandemic baseline period in 2019. For the average 500 bed facility, this translates to $17M in additional annual labor expenses since the pandemic began.”
Further, “According to PINC AI data, overtime hours are up 52 percent as of September of 2021 when compared to a pre-pandemic baseline. At the same time, use of agency and temporary labor is up 132 percent for full-time and 131 percent for part-time workers. Use of contingency labor (or positions created to complete a temporary project or work function) is up nearly 126 percent.” And, the press release notes, “Overtime and use of agency staff are the most expensive labor choices for hospitals - typically adding 50 percent or more to a typical employee’s hourly rate.”
The problem? “Hospital workers aren’t just putting in more hours, they are also working harder than ever before. The PINC AI analysis shows that productivity, measured in worked hours per unit of departmental volume, increased by an average of 7 percent to 14 percent year-over-year across the intensive care, nursing and emergency department units. Observing increased overall staffing cost during a period of improved staff productivity highlights just how significant the increases in cost-per-hour have become.”
And there’s still more bad news here: “Hospital employees are more exposed to COVID than many other workers, with quarantines and recoveries requiring use of sick time. 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. In fact, PINC AI data shows that clinical staff turnover is reaching record highs in key departments like Emergency, ICU, and Nursing. Since the start of the pandemic, the annual rate of turnover across these departments has increased from 18 percent to 30 percent. This means nearly one-third of all employees in these departments are now turning over each year, which is almost double the rate from two years ago.”
What’s more, the press release notes, “This is a number that could increase as new vaccination mandates take effect. Already, one midwestern system reported a loss of 125 employees who chose not to be vaccinated. A New York facility reported another 90 resignations, and overall, staffing agencies are predicting up to a 5 percent resignation rate once vaccine mandates kick in. 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.”
Why should senior leaders in hospitals and health systems be concerned? The press release notes that, “According to the American Hospital Association, hospitals nationwide will lose an estimated $54 billion in net income over the course of the year, even taking into account the $176B in federal Coronavirus Aid, Relief, and Economic Security (CARES) Act funding from last year. Added staffing costs were not addressed as part of CARES and are further eating into hospital finances. As a result, some are now predicting that more than half of all hospitals will have negative margins by the end of 2021 – a trend that could be dire for some community hospitals.”
The press release noted that, “Using data from over 650 acute care facilities nationwide, PINC AI leverages machine learning to predict whether a specific department will face a critical shortage of clinical staff within the next eight weeks. Considering that it often takes 30-45 days to fully onboard new clinical staff members, this predictive model could provide an early warning system, enabling health system leaders to take staffing action before a shortage occurs. The model may also be used to identify departments where current staffing is likely sufficient over the near term, enabling excess resources to be aligned with the areas of greatest need. The model has thus far achieved an 83 percent accuracy score with an AUC of 86 percent when tested on a random 10 percent data sample withheld from model training. This is strong performance according to two standard model evaluation techniques; however, it should be noted that true performance in the future for any predictive model can only be estimated.”
Shortly after the PINC data was released, Premier Inc.’s president and CEO Mike Alkire spoke with Healthcare Innovation Editor-in-Chief Mark Hagland regarding what’s been learned. Below are excerpts from that interview.
From a 40,000-feet-up view, what does this landscape look like to you?
I’ll start with the data. If you think about Premier, we were developed to literally be that innovation incubator, as well as performance improvement support for our healthcare systems; that’s how we came about. In terms of this issue, we’ve been hearing of significant issues with labor costs; and we have a board advisory committee where we have about 35-40 members represented. We’re consistently hearing about both labor shortages and labor costs, during this COVID pandemic, as they’re trying to get back to some sort of normalcy.
So we decided to run some data; and that’s how we came up with this number of $24 billion of true costs associated with labor shortages and dealing with COVID. And it’s important to create awareness of the issue. And because we’ve invested in next-generation technology with machine learning and AI, we’ve got some predictive capability within our PINC platform where we can predict potential, emerging labor shortages. And we can look at comorbidities and predict whether certain types of patients might end up in the hospital and possibly need intensive care.
What have been the impacts to healthcare leaders in terms of managing labor, costs?
It’s very complicated. Two significant tragedies are associated with COVID. Obviously, the first and biggest is just the loss of life and the loss of health involved. The second tragedy is the fact that our healthcare systems are obviously being stressed to care for their populations. They’re stressed in terms of obtaining adequate labor, and adequate supplies. And as this virus progresses, there will be deficits to work out of. The first will be the financial deficit related to the costs of caring for these patients. And the second is really the physical and emotional toll on the caregivers who have been on the front lines for roughly 20 months now. And that toll is yet to be fully understood, but we’re beginning to see it in terms of the number of caregivers who are retiring, who are moving more towards part-time, and who are burning out. Now, the healthcare systems are very resilient; they’re mission-driven, as is Premier, and they know that they’ve got to figure out ways to work this out.
And even in the early days of the pandemic, we were working with them through our collaboratives and our advisory services, to help them to try to develop greater agility. And we’ve taken that agility mindset and have moved to a focus on labor, using our PINC-AI predictive technology, to identify where they’re going to have larger labor issues or burdens. We’re trying to help them to utilize their workforces to reduce the level of burnout as much possible.
The pandemic has intensified the nurse aging crisis in our country. What can be done?
We don’t necessarily look at it as a nurse aging issue, because regardless as to whether you’re 34 or 48, when you’re looking at overtime hours, they’re up 52 percent, as of September, versus pre-pandemic levels. So the point is, so, short-term, we believe that there are opportunities to work with the Biden administration, to fast-track visa and other approvals for international nurses, to help on the front lines. We’ve been really focused on working through that channel. That’s number one, and that’s short-term. Medium- and long-term, they’re doing all sorts of programs, to include reviewing and looking for nurses who have retired and see if they’d be interested in coming back to work for periods of time. They’ve been working with universities to look at educating qualified nurses and filling up more nursing programs and literally facilitating some of that training and on-premises work with those universities.
You’ve got to have this multi-pronged approach. Short-term, let’s see if we can get access to international nurses. Medium-term, there might be labor in the market that are fulfilling other roles, whom we might be able to attract back to bedside care; and long-term, we need to get as many nurses through the educational and training process, appropriately, to get ready to provide care as soon as possible.
What’s your overall sense of the nursing shortage situation nationwide?
It’s incredibly regional. In some of our regions, it’s an 8 or a 9; and in others, it’s a 3 or a 4. There are regions that lend themselves better to long-term labor that’s efficiently and effectively within those geographic areas. And in some areas, because of COVID or other macro issues, significant shortages exist. And therefore, they’re in the middle of trying to get access to labor; but it’s very, very regional.
Looking a few years out, what does this picture look like to you?
I think we’ve got to be able to use data and analytics, and our ability to predict whether or not there’s going to be high levels of utilization of the HC system, or specifically of intensive care or other types of care. But it really comes back to our ability to harness data and to use machine learning and AI. We have these systems at our disposal; it’s important to create more agility, more resiliency—to make sure that we’re using labor appropriately, effectively, and at the highest end of their license.