AMN Healthcare

Before partnering with Textkernel by Bullhorn, AMN Healthcare had a homegrown matching system. According to Mark Hagan, AMN Healthcare Chief Information and Digital Officer, this system had limitations, and his team was struggling to quickly find candidates within their physician staffing business that matched job opportunities.

“We had a homegrown matching algorithm,” explained Hagan. “However, it was less of an algorithm and more of a traditional search functionality that didn’t have any advanced capabilities or ability to match clinicians.”

According to Hagan, continuing to use, maintain, and scale an in-house solution was deemed too costly and slow to market. With an increased demand for clinicians, AMN Healthcare needed a faster, more efficient solution that could integrate seamlessly with Salesforce and scale to their needs.

“We had an increased demand for a process that would scale. It became a priority for the business to find an AI-powered source and match solution,” said Hagan.

Enhanced Matching Accuracy and Efficiency – Textkernel’s AI-driven matching algorithms provided a significant upgrade over AMN Healthcare’s previous search functionality. By integrating Textkernel’s extensive taxonomy with AMN Healthcare’s data, the matching process became more precise and efficient.

“Our goal was a 10% percent increase in candidate matches and a 5% increase in recruiter productivity,” explained Hagan. “What we’ve seen is our candidate matching has increased by 18%, placements are up 14%, and productivity is up close to 20%.”

This advancement allowed AMN Healthcare to scale up operations to meet increasing staffing demands while fitting seamlessly into their Salesforce workflow, a critical integration feature noted by Hagan.

However, despite the success the team has already seen, Hagan believes there’s still more to come. “We believe that there’s still opportunity for increase in productivity, candidate interactions, and placements because we haven’t scratched the surface of the platform’s capabilities.”

Customizable taxonomy for specialized needs – According to Hagan, the combination of AMN Healthcare’s taxonomy with Textkernel’s healthcare taxonomy enabled more effective skill matching across various roles, from internal physicians to emergency roles, without the need to start from scratch. This alignment streamlined processes, decreased redundancy, and enhanced overall efficiency.

Textkernel’s comprehensive taxonomy served as a robust foundation that AMN Healthcare could further customize to meet their specific recruitment requirements.

“I think the first thing that Textkernel came to the table with was solid right away, but it wasn’t necessarily specific to physicians and locals,” said Hagan. “Because Textkernel is so customizable, we were able to bring our taxonomy, and make it effective for our team. This was especially important when it comes to physicians, because skill sets can match several different specialities. So, the ability to sort of bring those systems together and not have to start from scratch, was huge for us.”

According to Hagan, this flexibility allowed AMN Healthcare to address the unique demands of different healthcare roles, leveraging Textkernel’s extensive database and advanced algorithms to pair candidates with suitable job opportunities quickly and accurately.

Partnership with Textkernel – With any implementation, it’s essential to have a partner that can get you set up for success from the very beginning. According to Hagan, his team had a great partnership with their partners at Textkernel.
“The feedback from my team has all been extremely positive, with both the support team as well as the training team. They were very complimentary of the service that they received,” said Hagan. “Anytime there’s been an issue or question, it’s been quickly resolved.”