"How long should this take?" is a deceptively hard question in healthcare staffing, because the honest answer varies by an order of magnitude depending on role and specialty. But there is a real, widely cited national benchmark — and it's worth knowing exactly what it measures before deciding whether your own fill times are actually a problem.
What is the RN Recruitment Difficulty Index, exactly?
It's NSI Nursing Solutions' national benchmark for the average number of days it takes to fill an RN vacancy, currently standing at 83 days — down 3 days year-over-year, but still, as NSI itself puts it, "approximately 3 months" to recruit an experienced RN (2025 NSI National Health Care Retention & RN Staffing Report). AACN's own fact sheet cites a somewhat wider range — 56 to 102 days to recruit an experienced RN — reflecting real variation by specialty, geography, and facility type rather than a single fixed number (AACN Fact Sheet).
How does healthcare compare to other industries on time-to-fill?
Poorly — healthcare consistently ranks among the slowest sectors to fill roles. Staftr's 2025 Staffing Speed Report finds general healthcare roles average 49 days to fill direct-hire, against a 36-44 day U.S. market average across all industries, while specialized clinical positions can stretch to a striking 250 days. Staffing agencies compress general healthcare roles to 17-20 days, but that 250-day tail for hard-to-fill clinical specialties persists even when working through an agency (The 2025 Staffing Speed Report, Staftr). That gap between the 17-20 day agency-compressed figure and the 250-day tail is a useful diagnostic: if a facility's actual fill times cluster toward the long end, the bottleneck is very likely candidate specialization and credentialing, not general sourcing capacity.
What does a day of delay actually cost?
More than most facilities model explicitly. Every RN successfully hired — versus left vacant or covered by contract labor — saves an institution an estimated $79,100 (2025 NSI Report). At scale, the math compounds fast: one institution modeled replacing 20 travel nurses with permanent or contract-agency staff and found $1,582,000 in savings (2025 NSI Report). Turnover compounds this further: each departing bedside RN costs a hospital $61,110 on average, and each 1-percentage-point change in RN turnover costs or saves the average hospital an additional $289,000 per year (2025 NSI Report).
Is speed the only lever, or does quality matter just as much?
Quality matters at least as much, and arguably more, given the clinical stakes. Peer-reviewed nurse-staffing research cited by AACN found a 10-percentage-point reduction in RN staffing is associated with 7% higher odds of in-hospital death and 1% higher odds of readmission, and a study of nearly 198,000 patients across 43 units found understaffed units carried roughly 6% higher mortality risk (AACN Fact Sheet, citing peer-reviewed staffing outcomes research). This reframes time-to-fill from an HR metric into a patient-safety metric: a faster, but poorly matched, hire that leads to early turnover doesn't actually solve the underlying vacancy problem — it just defers it a few months.
Where specifically does the 83 days go?
Largely into sourcing and credentialing, both of which are compressible with the right tooling. Complex credentialing, licensing verification, and fragmented data are cited by healthcare staffing firms as the primary reasons the sector lags the broader staffing industry in AI adoption — only 7% of healthcare staffing firms have AI embedded throughout their entire workflow, versus 10% industry-wide, and 26% report barely using AI at all, versus 20% industry-wide (Bullhorn GRID 2026 Industry Trends Report: Healthcare Spotlight).
Does the 83-day benchmark vary meaningfully by facility type or region?
Meaningfully, though a single national breakdown by facility type wasn't available in this research pass. What is clear from the broader benchmarking data is that the 83-day national average sits well above the general 36-44 day U.S. market average across all industries, and that specialized clinical roles push well past even that elevated baseline — the 250-day tail cited in cross-industry benchmarking (Staftr, The 2025 Staffing Speed Report). Facilities in rural or underserved markets, where the pool of credentialed candidates is inherently smaller, would reasonably be expected to sit toward the longer end of the national range, though the available research does not isolate a precise regional breakdown.
The financial stakes of moving faster are well quantified even without a regional breakdown: replacing 20 travel nurses with permanent or contract-agency staff was modeled to save one institution $1,582,000, illustrating how directly fill-speed improvements translate into hospital-level savings regardless of the specific facility or region involved (2025 NSI Report).
UPPER's POV: The 83-day RN Recruitment Difficulty Index is a sourcing problem before it's a credentialing problem — and it's the part of the timeline most amenable to automation. UPPER runs always-on sourcing against passive, credentialed clinical talent pools, attacking the single biggest lever in the NSI benchmark before a candidate ever reaches the manual verification stage.
Key data points
- The RN Recruitment Difficulty Index stands at 83 days nationally (2025 NSI Report).
- Specialized clinical positions can take up to 250 days to fill even through an agency (Staftr 2025 Staffing Speed Report).
- Each successful RN hire versus a vacancy saves an institution an estimated $79,100 (2025 NSI Report).
- Each departing bedside RN costs a hospital $61,110 on average (2025 NSI Report).
- Only 7% of healthcare staffing firms have AI embedded throughout their workflow, versus 10% industry-wide (Bullhorn GRID 2026 Healthcare Spotlight).