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How workforce intelligence can help combat the staffing shortage in healthcare

Since the pandemic began, health systems have faced severe medical supply shortages for everything from personal protective equipment and ventilators to testing kits. However, those issues pale in comparison to a growing workforce shortage that is touching nearly every aspect of the health ecosystem.

As we prepare to enter the third year of this once-in-a-century pandemic, the supply and demand challenge within healthcare continues to take center stage.

Healthcare leaders are all too familiar with these problems, as short- and long-term shortages continue to plague the space, from personal protective equipment and ventilators to testing kits and other medical supplies. However, those issues pale in comparison to a growing workforce shortage that is touching nearly every aspect of the health ecosystem.

That shortage existed long before the pandemic and has pushed health systems to the brink of their capacity. In fact, hospital CEOs recently reported that staffing has overtaken financial challenges as the top concern for the first time since 2004, according to the American College of Healthcare Executives.

While there’s no single solution that can solve this challenge overnight, there is some positive news. Namely, healthcare organizations are beginning to realize how data and analytics can be applied across the provider community to help solve this problem through an emerging practice: workforce intelligence.

Let’s explore the reasons why workforce intelligence has become essential in healthcare.

Providing the chance to analyze and plan

The pandemic has certainly tested supply and demand limits. But evolving delivery channels, healthcare consumerism and an aging population are forcing leaders to rethink how they plan, engage and onboard their clinical workforce. As a result, staffing shortages, skyrocketing contract labor costs and clinician burnout at levels not seen before have created a perfect storm.

By providing health systems with comprehensive, real-time insight into their current and future clinical workforce, leaders can better navigate the increasing challenges of care logistics. It enables leaders to leverage real-time data to address gaps in workforce supply, distribute precious resources more efficiently and optimize their care networks.

Addressing the burnout crisis

Staffing shortages and inefficient deployment models drive the overutilization of clinicians, a key driver of frustration and attrition. According to Deloitte’s 2022 Global Health Care Outlook, an alarming 55% of frontline healthcare workers reported burnout, with the highest rate (69%) among the youngest staff. Therefore, reducing unnecessary steps in the workflow and accelerating information to make better decisions can profoundly affect morale and the bottom line.

Reducing the friction within clinician deployment

No task is more bemoaned by clinicians than credentialing.

Clinician information is expensive and tedious to obtain and confirm, especially if it requires manual effort by the already overwhelmed administrative staff. Connecting into provider data networks and applying workforce intelligence can dramatically improve this process for administrators and clinicians alike, decreasing deployment time and easing the burden on overstretched clinical staff waiting to be relieved.

This difference isn’t just eliminating the burden of more paperwork, it’s empowering clinicians to manage the most important documents of their careers: their credentials.

Allowing health systems to always be ready

In this challenging environment, it is crucial for health systems to be efficient and flexible. Real-time updates ensure an always-ready workforce that can be quickly deployed where they’re most needed, all while meeting credentialing and privileging regulations at the same time.

This, historically, has been a daunting task, but thanks to big data, information related to a practitioner’s credentials, skills and capabilities can easily be collected. This provides multiple benefits to clinician teams, including:

  • Enabling care collaboration: Leveraging digitally verified provider data to cross credential across locations and care partners empowers organizations to expand services and revenue. This enables healthcare systems to more easily share providers in support of community care collaboratives and national telehealth networks.
  • Optimizing economics: Physicians produce thousands of dollars a day in revenue for healthcare systems, offsetting rising costs elsewhere in the organization. Reducing unnecessary delays is key to revenue capture. By enabling teams to make faster decisions about how and where to deploy clinical resources and with the privileging regulations already met, administrators can cut weeks, and sometimes even months, out of a labor-intensive problem that also improves patient access to care.

Looking ahead: the future of workforce intelligence

While the U.S healthcare workforce shortage has been recently thrust into the spotlight, the pandemic only worsened a trend long in the making. The problem is only expected to get much worse over the next decade due to an aging population, longer lifespans, an increase in chronic conditions and alarming rates of burnout, among other issues. We can’t pretend there’s any simple off-the-shelf solution that can be used to solve this incredible challenge.

But by applying big data and workforce intelligence as a solution to the staffing challenge, healthcare leaders can begin to build better networks, eliminate deployment delays, meet patient demand, improve outcomes and ultimately improve the bottom line — a win for all stakeholders.

Photo: PeopleImages, Getty Images


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Charlie Lougheed

Charlie Lougheed is the CEO and co-founder of Axuall. Built with leading healthcare systems, Axuall is a workforce intelligence company built on top of a national real-time practitioner data network that enables healthcare systems, staffing firms, telehealth, and health plans to dramatically reduce onboarding and enrollment time while also providing unique, powerful data insights for network planning, analytics, and reporting. He previously co-founded Explorys in partnership with the Cleveland Clinic that was acquired by IBM in 2015. Explorys became the leader in healthcare big data and value-based-care analytics, spanning hundreds of thousands of healthcare providers and over 60 million patients across the United States.

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