Multi-source benchmarking of how long it takes to fill Director of Nursing and RN/Nurse Manager roles — combining Xelerate's own placement data, national industry reports, and market-specific indicators.
Four key TTF data points from the most authoritative sources.
How Xelerate's actual performance stacks up against every available benchmark, by role type.
Granular breakdown from Xelerate's 82 completed nursing placements.
| Market / Segment | Placements | Avg TTF (Hire) | Avg TTF (VOA) | Salary Range | Top Source |
|---|---|---|---|---|---|
| Director of Nursing | |||||
| California (all regions) | 15 | ~95 days | ~52 days | $145K–$210K | Indeed, Internal |
| Minnesota | 3 | ~86 days | ~73 days | $105K–$142K | Indeed, ZipRecruiter |
| Pacific Northwest (WA) | 5 | ~121 days | ~72 days | $157K–$200K | Indeed, LinkedIn, Referral |
| Regional / Multi-Site | 3 | ~77 days | ~30 days | $182K–$210K | Internal Transfer |
| DON Overall Average | 26 | ~95 days | ~60 days | $105K–$210K | — |
| Nurse Manager / RN Leadership | |||||
| Minnesota (high volume) | 31 | ~115 days | ~96 days | $45/hr–$115K | Indeed, LifeSpark ATS |
| California (all regions) | 19 | ~128 days | ~113 days | $51/hr–$167.5K | Indeed, Telecare ATS |
| Twin Cities (Tru Healthcare) | 2 | ~48 days | ~29 days | $82K–$88K | Indeed |
| Mgr Role Overall Average | 56 | ~101 days | ~101 days | $45/hr–$167.5K | — |
| NNSVH Forecast (Sparks, NV) | |||||
| DON — $104K–$151.8K | — | 85–105 days | — | $104K–$151.8K | Indeed (projected) |
| RN Nurse Mgr — $89K–$101K | — | 90–115 days | — | $89K–$101K | Indeed (projected) |
The NNSVH Director of Nursing salary band ($104K–$151.8K) aligns with the faster-filling end of Xelerate's DON history. The closest comps are Minnesota DON placements ($105K–$142K) which averaged ~86 days, and mid-range California DONs ($145K–$160K). This suggests an 85–105 day forecast is realistic.
The Nurse Manager role ($89K–$101K) maps to LifeSpark manager placements in the $88K–$98K band, where TTF showed more variability. The 90–115 day forecast assumes a moderately difficult fill, consistent with Sparks' thin talent pool.
Key variable: interview speed and comp alignment at the facility level will determine whether this lands at 85 days or 115.
Every published TTF data point we could find for nursing roles, organized by source and confidence level.
| Source | Metric | Value | Year | Sample | Confidence |
|---|---|---|---|---|---|
| Tier 1 Sources — Large-Scale Industry Benchmarks | |||||
| NSI Nursing Solutions | RN Recruitment Difficulty Index | 83 days | 2025 | 450 hospitals / 37 states | High |
| NSI Nursing Solutions | Med-Surg RN TTF | 94 days | 2024 | 450 hospitals / 37 states | High |
| NSI Nursing Solutions | Progressive Care / Step-Down RN | 88 days | 2024 | 450 hospitals / 37 states | High |
| RogueHire | Patient Care / Revenue Roles | 131+ days | 2025 | 10,000+ data pts / 200+ systems | High |
| RogueHire | % Nursing Roles >150 days | 46% | 2025 | 10,000+ data pts / 200+ systems | High |
| RogueHire | % Nursing Roles >120 days | 33% | 2025 | 10,000+ data pts / 200+ systems | High |
| Tier 2 Sources — Industry Reports & Aggregators | |||||
| iCIMS Workforce Report | General Healthcare TTF | 41 days | 2024 | iCIMS platform data | Medium |
| iCIMS | Nursing Applicants per Opening | 9 | 2024 | Platform data | Medium |
| AAG Health / Industry Surveys | Med-Surg RN (contract labor cycle) | 152 days | 2025 | Industry aggregate | Medium |
| SHRM | Healthcare Overall TTF | 42 days | 2024 | SHRM member surveys | Medium |
| NC Healthcare Association | % RN Vacancies >60 days | 70% | 2024 | NC hospitals | Medium |
| Tier 3 Sources — Derived / Estimated | |||||
| Industry Rule of Thumb | DON / CNO TTF | 90–120 days | Ongoing | Practitioner consensus | Estimated |
| Industry Rule of Thumb | Nurse Manager TTF | 60–90 days | Ongoing | Practitioner consensus | Estimated |
| Rural / SNF Estimate | Nursing roles in rural/SNF settings | 109–200+ days | Ongoing | Multiple sources | Estimated |
Metro-level TTF data isn't publicly available, but we can infer relative difficulty from shortage severity, vacancy rates, and workforce pipeline metrics.
| Market | Shortage Severity | RN Vacancy Signal | Pipeline Adequacy | RN Wage vs National | Est. TTF Difficulty |
|---|---|---|---|---|---|
| Reno-Sparks, NV | Acute (3,000+ gap) | 9.6% (state avg) | Weak — 192 grads/yr | +7% above | High |
| Colorado Springs, CO | Critical (7,319 deficit) | Severe statewide | Weak — expanding | −2% below | Very High |
| Tucson, AZ | Critical (28,100 state gap) | 23.9% first-yr turnover | Moderate — UA ranked #23 | −6% below | Very High |
| Boise, ID | Acute (750–1K/mo) | High vacancy rate | Moderate — BSU expanding | −1% below | High |
| Spokane, WA | Serious ("worst ever") | 8th in travel RN demand | Weak | Below avg | High |
| Asheville, NC | Critical (worsening) | 70% >60 days (state) | Weak — faculty crisis | −4% below | Very High |
| Salem, OR | Critical (2,500/yr needed) | Contingency staffing | Weak | +21% above | High |
| Huntsville, AL | Emerging | Growing demand | Present but unquantified | −14% below | Moderate–High |
| Knoxville, TN | Severe (8,500 by 2035) | Statewide concern | Adequate — strong schools | −11% below | Moderate |
| Pensacola, FL | Emerging | State decline projected | Moderate | −9% below | Moderate |
An honest assessment of data confidence and where to invest for better intelligence.
Xelerate's own data (82 placements, exact dates, salary, source channel, market) is the strongest benchmark.
NSI national benchmarks (83 days RN avg, specialty breakdowns) are well-sampled and widely cited.
RogueHire real-world distribution (46% > 150 days) gives the fullest picture of what employers actually experience.
DON-specific TTF — no published benchmark exists. Leadership roles are too low-volume for standard surveys.
Metro-level TTF — no public source breaks nursing TTF by MSA.
SNF-specific TTF — skilled nursing facilities are underrepresented. Most benchmarks come from acute care hospitals. SNFs likely run 20–40% longer.
The most valuable TTF data won't come from a report you buy — it comes from tagging your own placements with market archetype data. As you expand into Sparks and the Tier 1 comparable markets, every placement adds a data point to your proprietary benchmark.
At 20–30 placements per market type, you'll have statistically meaningful TTF benchmarks segmented by archetype, salary band, role type, and source channel — data that doesn't exist anywhere else in the industry. That becomes a competitive moat.