Key takeaways:
- After an offer is accepted, credentialing often slows healthcare placements.
- Tracking the time between key stages can pinpoint the delays and give clients a more accurate start date.
- AI can take on document intake and checklist matching, but a person should still cover final verification and client clearance.
Your recruiter successfully found a candidate for a med/surg nurse position, with the client expecting her start date in just two weeks. While the team celebrates the placement, time is running out to put all the pieces in place.
Often, the holdup comes from credentialing. In a recent episode of our Staffing Show podcast, KarmaCheck CEO Eric Ly noted that credentialing specialists can spend up to an hour per placement just comparing what a candidate submitted to the requirements list. “And sometimes they even get it wrong, even the most trained person,” he said.
An hour doesn’t sound like much. But at 40 placements a week, it adds up to 20 to 40 hours of checklist review, the equivalent of a part- or full-time job.
Speed after job acceptance secures hospital business
Hospitals want to use fewer agencies. In NSI’s 2026 National Health Care Retention & RN Staffing Report, 70.7% of hospitals said they want less reliance on travel and agency staff. Yet, during shortages, agency staffing remains a top strategy.
Their in-house alternative is slow. NSI found that the average time to recruit an experienced RN is 78 days. A staffing partner who starts clinicians on the promised date will be well ahead of that timeframe. But repeatedly missing start dates risks losing clients, especially as hospitals cut back on agency use.
That makes credentialing speed a growth lever.
Every facility has its own checklist
While a commercial background check may cover a few items, clinician credentialing can have dozens, according to Ly, and the list changes with every assignment. The hospital, the managed service provider (MSP), accreditors like The Joint Commission, and your own agency all have their own set of requirements.
“That’s different in every case for literally down to the place where the clinician is going to be working,” Ly said. We recently covered how this caps locums growth, and the same friction slows every healthcare desk.
Candidates add friction too. Well-meaning clinicians often send the wrong document or an expired one, and each time, it starts another round of back-and-forth emails and texts. Busy nurses also tend to handle paperwork late at night or on the drive somewhere, Ly noted.
How to pinpoint the cause of missed start dates
Most firms know when an offer was accepted and when a clinician started, but it’s important to measure the time between the steps in the middle, too, including when documents were requested, when they were complete, and when the client has cleared the candidate to start.
Measure how much time each step takes over a quarter or so. You can sort results by specialty, facility, and document type.
In Ly’s experience, much of a credentialing specialist’s time is spent handling documents from candidates and from verification sources. If your data agrees, work on shortening the time between when you request documents and when they’re complete. It may be that one document type, like a specific immunization record or certification, causes most of the delay.
This process will also help answer client questions about why you had to push back a start date. You can tell them the file status and what’s missing. It’s easier to build trust if you can give a more specific answer.
How to find a solution that works
Every solution comes with a price, and most credentialing teams are already stretched thin. So focus on the slowest point first:
- If sheer volume is the cause, a dedicated credentialing coordinator may be the answer. Track their hours against your data to see when a second hire pays off.
- Slow outside sources call for a different solution. A verification service makes sense when license boards, past employers, or schools take too long to respond.
- For specialties you place regularly, consider pre-credentialing. Collect and verify the standard documents before a clinician accepts an assignment. Then you’ll only have to worry about the facility-specific items after the offer.
To inform the decision, multiply weekly placements by credentialing hours per file and compare this to each option’s cost and potential revenue from faster starts. Choose options that generate more gross profit than they cost.
AI can help with document management, but needs a human sign-off
Requirements often arrive as PDFs, spreadsheets, or even photos. Ly said large language models can read those messy formats and turn them into a structured checklist. That takes the guesswork out of matching submissions to facility requirements and significantly speeds up the process.
AI can also follow up with candidates by text or email at hours that suit them. It can flag an incorrect or expired document before a specialist opens the file, too.
But keep people on final verification and client clearance. Gartner predicts that by 2028, one in four candidate profiles worldwide will be fake. Ly expects people to keep reviewing AI recommendations for now. Over time, he sees that shifting toward one-click approval as the tools earn trust.
Before you buy, consider whether the tool will work inside your existing systems and workflows and how you’ll measure the return. Just handing your team ChatGPT isn’t enough to see results. You need a target to work toward and a definition of success.
Since credentialing happens after the candidate accepts a job, it tends not to come in a sales meeting. But if you don’t shorten the time it takes, the client’s next order might go to a competitor.
