Faced with rising patient populations and nurse shortages, healthcare systems are moving beyond basic VMS technology to orchestrated, data-driven workforce strategies.

By Debbie Bolla

Today’s healthcare organizations face numerous staffing challenges, causing a high level of friction between meeting patient needs and achieving business goals. Demand for care is projected to be on a steady upswing, with the U.S. Census Bureau reporting the number of older Americans to increase from 58 million in 2022 to 82 million by 2050. At the same time, the Bureau of Labor Statistics finds that nearly half of hospitals report registered nursing shortages increasing, with vacancy rates above 10%. But through technology-enabled talent acquisition and management approaches, healthcare systems can deliver more savvy workforce strategies, while navigating the complexity of today’s realities.

“Healthcare workforce strategy is entering a new phase,” says David Durbin, President of Trio Workforce Solutions. “The conversation is moving beyond implementation and adoption. Organizations are looking for an integrated solution that presents all of the necessary information in a very orchestrated way.”

The industry is evolving at an unprecedented pace, driven by changing workforce expectations and an AI and technology explosion. Just a few years ago, a vendor management system was the main vehicle that enabled a staffing-led fulfillment model for healthcare systems. The focus was on vendor neutrality, maintaining compliance, and reducing costs. Today’s market calls for more sophisticated technology, driven by different staffing and business needs. TA teams are citing friction throughout the entire process, including submission, credentialing, and advancing the bottom line. Here is where an integrated approach can be a gamechanger. Healthcare systems operating with a maturity model that has transformed into an integrated platform will deliver a more analytical, dashboard-driven view into healthcare staffing needs and spending.

Durbin says that healthcare organizations that take this approach can experience many key differentiators, including:

• real-time feedback on candidates to boost overall quality and speed to hire;
• increased visibility into job needs;
• transparency and benchmarking around agency performance;
• automated auditing to maintain costs and margin; and
• market intelligence for better overall decision-making.

What is AI’s Role?

Research from McKinsey and Company finds that globally, 78% to 88% of organizations use AI in at least one business function. From job descriptions and submission scoring to scheduling and travel reimbursement, healthcare systems are ripe with opportunities for adoption.

“We’ve taken an intentional approach to look at where are points of friction and how can AI support it,” says Durbin. “We are analyzing where to deploy AI against policies to help avoid unnecessary costs as well as using AI in ways to improve efficiency.”

Take, for example, submission scoring. Durbin says when time is invested on the front end between TA teams and health systems to outline the specific requirements of the role (nurse, allied health professional, physician etc.) and the details of the background and experience, a sound profile can be created. Armed with this information, an AI-based digital worker can effectively review submissions and analyze candidates against the profile to produce an overall score that takes into account both strengths and deficiencies. While a TA leader will make the final decision based on the analysis, thousands of hours will be saved in this tech-driven submission scoring process.

An AI-enabled approach can also spot candidate requirements that might be hindering fulfillment. With this insight, making slight adjustments can greatly increase candidate pools and speed up time to hire. “As you build the process out, you can help both sides of that equation to take the friction out. It’s easy to do because it’s very prescriptive,” says Durbin.

Another process that can be improved through AI is a travel or expense reimbursement policy. Durbin provides the example of a healthcare system with 60 facilities across their footprint, which equates to 60 different travel expense and reimbursement policies. A digital worker can be trained to understand each of these 60 policies in the matter of four minutes. It can easily pinpoint outliners in the policy, like if an employee exceeds the number of approved trips per month. But like with many things, there are exceptions that call for human intervention. The digital worker increases efficiency by flagging outliners while HR leaders spend time making strategic final decisions.

“Digital workers are trained to find those problem statements that require human intervention,” says Durbin. “So 95% of what AI can do with expense policies is trap, capture, and identify information and exceptions. It’s the 5 percent that calls for human decision-making.”

As changes in the market move quickly, organizations need solutions to help them get ahead. By leveraging technology and AI-enabled practices, healthcare systems can gain efficiencies, reduce costs, hire faster, and achieve better business outcomes.