Nurse Wage Benchmarking: The Complete Resource Hub

How to Use This Hub

The question arrives in different forms. Sometimes it is a nurse manager asking why two ICU nurses with similar tenure are paid differently. Sometimes it is a CNO preparing for a board conversation about retention spend. Sometimes it is an HR director looking at a travel-nurse invoice and wondering what a permanently employed RN in the same metro actually earns at the 75th percentile.

The underlying task is the same each time: compare what your facility pays against what the external labor market offers. That comparison — nurse wage benchmarking — sounds straightforward, but it involves a specific methodology: the right data source (BLS Occupational Employment and Wage Statistics), the right geographic level (state versus metro), the right occupational codes (SOC 29-1141 for RNs, SOC 29-2061 for LPN/LVNs), and a clear framework for turning raw percentile figures into actionable pay bands and wage-gap alerts.

This hub collects every resource on this site that addresses nurse pay benchmarking. Whether you are starting from scratch with BLS tables or refining a multi-facility compensation model, the guides below are sequenced to move you from first principles to applied practice. Bookmark this page; it updates as new resources are added.

Start Here: The Foundations of Nurse Wage Benchmarking

What BLS OES data is — and what it is not

The Bureau of Labor Statistics Occupational Employment and Wage Statistics (OES) program is the authoritative public source for nurse wage data in the United States. It publishes annual estimates of employment and wages by occupation, industry, state, and metropolitan statistical area (MSA). For nursing, the two primary occupational codes are RN (SOC 29-1141) and LPN/LVN (SOC 29-2061).

The May 2024 BLS release — the most recent as of this writing — shows a national median annual RN wage of $93,600, with the 10th percentile below $66,030 and the 90th percentile above $135,320 (BLS Occupational Outlook Handbook, May 2024). For LPN/LVNs, the May 2024 median is $62,340 ($29.97/hr), with the 10th percentile below $47,960 and the 90th percentile above $80,510 (BLS OOH, May 2024).

These figures are national. Your facility competes in a local labor market, which is why the geographic granularity of the data matters — and why state-level and metro-level figures can diverge substantially. California's mean annual RN wage, for instance, stands at approximately $148,330, well above the national median (BLS OEWS May 2024, via Sunbelt Staffing analysis, May 2024). Reading a national figure against a California facility's pay band would produce a misleading baseline.

→ Read: BLS Nurse Wage Benchmarking Guide — a step-by-step walkthrough of the OES dataset, from finding the right occupational table to interpreting the percentile columns.

→ Read: How to Read BLS OES Wage Data — a plain-English guide to the table structure: what the 10th, 25th, 50th, 75th, and 90th percentile columns mean and how to use them in a compensation review.

Choosing the Right Geographic Level

State-level versus metro-level benchmarking

BLS OES publishes wage data at multiple geographic levels: national, state, and metropolitan/nonmetropolitan area. Choosing the wrong level is one of the most common benchmarking errors in nursing compensation work.

State-level data is appropriate when a facility draws nurses from across a broad catchment area — rural critical-access hospitals and smaller SNFs often fit here. Metro-level data is more precise for facilities in or near a defined metropolitan statistical area, where the competitive labor market is local: nurses are comparing your offer against neighboring health systems, not against averages from the other side of the state.

The difference is not trivial. Within a single state, wage variation between MSAs can span tens of thousands of dollars annually for RNs. Using a state figure when a metro figure is available risks benchmarking against a diluted average that understates local competition.

→ Read: State vs. Metro Wage Benchmarking for Nurses — when to use each geographic level, how to locate metro wage tables in the OES dataset, and a worked example showing the gap between a state median and the same role's metro median in a high-cost market.

Understanding the Occupational Profiles: RN vs. LPN/LVN

Why the two occupations benchmark differently

RNs and LPN/LVNs are distinct occupational classifications with different scope of practice, education requirements, and — consequently — different wage distributions. Treating them as a single "nursing" category in a compensation model produces misleading averages.

The May 2024 BLS data illustrates the spread clearly: the national median RN wage ($93,600) exceeds the national median LPN/LVN wage ($62,340) by more than $31,000 annually (BLS OOH, May 2024). The percentile distributions also differ in shape: the RN 90th-percentile wage ($135,320+) reflects the premium for highly specialized or geographically concentrated RN roles; the LPN/LVN distribution is narrower. Benchmarking each role against its own OES occupational category is essential to accurate pay-band construction.

Occupational profiles from O*NET — which describe the skills, tasks, knowledge, abilities, and work context associated with each role — are joinable to BLS OES wages by SOC code, enabling richer workforce analytics that pair compensation data with occupational demands.

Occupational data sourced from O*NET, licensed under CC BY 4.0. O*NET® is a trademark of the U.S. Department of Labor, Employment and Training Administration. onetcenter.org

→ Read: RN vs. LPN/LVN Wage Differences Explained — a side-by-side comparison of the two wage distributions, how scope-of-practice differences drive the gap, and what this means for facilities that employ both roles.

→ Read: O*NET Nursing Occupations Explained — how O*NET occupational profiles for RNs (29-1141.00) and LPN/LVNs (29-2061.00) are structured, what the skills and work-context data describe, and how to use them alongside BLS wage data in workforce planning.

From Benchmarks to Pay Bands

Translating percentile data into a workable compensation structure

A BLS percentile table is a diagnostic tool, not a pay structure. The practical step after benchmarking is building pay bands: defined minimum, midpoint, and maximum pay levels for each role, informed by the external market and calibrated to the facility's competitive positioning.

Most facilities choose a market position — paying at the 50th percentile, at the 60th, or somewhere in a defined range — and then construct bands around that anchor. The midpoint of a pay band typically corresponds to the target market position. The minimum and maximum define the spread, which affects both budget exposure and the range of experience the band can accommodate.

Pay bands that are not revisited against updated BLS data drift. The BLS OES is updated annually; a pay band built on 2021 wage data and not refreshed is benchmarking against a labor market that no longer exists. For RNs, this matters acutely: the May 2024 national median of $93,600 reflects a labor market shaped by post-pandemic demand, wage growth, and geographic redistribution of nursing supply (BLS OOH, May 2024).

→ Read: How to Build Nurse Pay Bands Using BLS Data — a practical framework for constructing pay bands from OES percentile data, including how to set a market position, define band spreads, and schedule annual refreshes.

Wage Gaps and Flight Risk

When internal pay falls behind the external market

A pay band built on current data is only useful if it reflects what nurses at your facility are actually being paid. The gap between where a nurse's current wage sits and the external benchmark is where retention risk accumulates quietly — until it does not.

The pattern is familiar: a nurse hired three years ago at the 50th percentile has received modest annual increases while the local market has moved. Their current wage now sits below the 25th percentile for the role in their MSA. They have not said anything. The manager has not flagged anything. The resignation letter arrives anyway.

Wage-gap analysis involves two steps: anchoring each role to the appropriate external benchmark (the correct SOC code, the correct geography, the current BLS release), and then calculating where each nurse's actual wage falls relative to that benchmark. Nurses whose pay falls meaningfully below the market median represent a measurable and monitorable retention risk — one that is far less expensive to address proactively than to absorb as a departure.

The NSI 2026 report puts the average cost of a single staff RN departure at $60,090 (NSI National Health Care Retention & RN Staffing Report, 2026, via Becker's Hospital Review, 2026). Preventing one departure through a targeted wage correction is a materially different financial equation than replacing a nurse after they leave.

→ Read: Nurse Wage Gap and Flight Risk: What BLS Data Tells You — how to calculate wage gaps by role and unit, how to interpret the signal, and what proactive wage-band corrections look like in practice.

Applying Benchmarks Across Multiple Facilities

A guide for HR directors and regional operators

For HR directors managing nursing compensation across more than one facility, the benchmarking challenge compounds. Each facility may sit in a different metropolitan statistical area, compete in a different local labor market, and carry a different mix of RN and LPN/LVN roles. Applying a single wage structure across a multi-facility portfolio produces winners and losers by geography — and the losers quietly become flight risks.

A multi-facility benchmarking approach requires geo-specific anchoring: each facility's pay bands are benchmarked against the BLS OES data for its own state or metro, not against a blended average. It also requires a consistent methodology for flagging cross-facility anomalies — situations where the same role is compensated at materially different market positions across facilities in the same portfolio.

→ Read: Nurse Compensation Benchmarking for HR Directors — a framework for managing nurse pay benchmarking at the portfolio level, including geo-specific anchoring, cross-facility wage-gap alerts, and the reporting structures that support board-level compensation conversations.

Workforce Analytics Context

Wage benchmarking inside a broader workforce picture

Wage benchmarking does not exist in isolation. Pay is one retention lever among several — alongside scheduling, unit culture, advancement pathways, and workload. But it is the most directly measurable one, and it is the lever that BLS OES data speaks to with precision.

Situating wage benchmarking inside a fuller workforce-analytics framework means connecting pay-band data to turnover rates, vacancy trends, and retention risk scoring by unit. A unit with a 30% rolling 12-month RN turnover rate and a median wage sitting at the 30th percentile for its MSA is telling a coherent story. A unit with a low turnover rate despite pay at the 25th percentile may have other retention factors offsetting the wage gap — or may simply not have reached the point where nurses start comparing offers.

The national staff RN turnover rate in 2025 was 17.6%, up 1.2 percentage points from the prior year, reversing the prior year's decline (NSI 2026, via Becker's, 2026). Each percentage point of RN turnover costs the average hospital approximately $295,000 per year (NSI 2026). Wage benchmarking is one of the more direct tools available for managing that exposure before it registers in turnover.

→ Read: Nursing Workforce Analytics: A Complete Guide — how turnover, vacancy, wage benchmarking, and retention risk scoring fit together in a coherent workforce-analytics practice.

All Wage Benchmarking Resources at a Glance

For quick navigation, every resource in this cluster:

• BLS Nurse Wage Benchmarking Guide — Start here if you are new to OES data.
• How to Read BLS OES Wage Data — Decoding the percentile table structure.
• State vs. Metro Wage Benchmarking — Choosing the right geographic level.
• RN vs. LPN/LVN Wage Differences Explained — Why the two occupations benchmark separately.
• O*NET Nursing Occupations Explained — Occupational profiles alongside wage data.
• How to Build Nurse Pay Bands Using BLS Data — From benchmarks to a workable pay structure.
• Nurse Wage Gap and Flight Risk — Turning wage-gap analysis into retention action.
• Nurse Compensation Benchmarking for HR Directors — Multi-facility and portfolio-level frameworks.
• Nursing Workforce Analytics: A Complete Guide — Situating wage work inside a full analytics practice.

Stay Current: New Resources as They Publish

BLS OES data updates annually. When new wage releases publish, benchmarks shift — and pay bands built on prior-year data need review. We publish updates to this hub and new benchmarking guides as the data moves.

Subscribe to the Nursing Workforce Planner newsletter to receive new wage benchmarking resources, BLS release notes, and practical guides when they publish. No scheduling content, no vendor announcements — only workforce data and the frameworks to use it.

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