About

# About LocumRates You deserve to know what the market actually pays — not what an agency tells you it pays. Physicians spend a decade in training before earning an independent paycheck. By the time you're negotiating a locum assignment, you've already given years of nights, weekends, and personal sacrifice to become competent at something genuinely difficult. LocumRates was built by a General Surgery physician who went looking for reliable locum rate data and found industry surveys buried behind agency registration forms and outdated forum posts. This site is the resource that should have existed. LocumRates is an independent data publication. There is no course to sell you, no upsell funnel, and your data is not for sale. This site exists for one reason: pay transparency for physicians who have earned it. If you're anything like me, you graduated residency chronically sleep deprived and a little burnt out. You don't have the time or energy to search for hours and negotiate back and forth with an agency that does this every day. Hopefully this helps. *Sincerely, one of the nicer general surgeons.* --- ## What We Publish Rate benchmarks for 20 physician specialties across four US Census regions (Northeast, Midwest, South, West) and two practice settings (urban hospital, rural critical access). Data is presented as 25th percentile, median, and 75th percentile hourly rates. ## Data Sources Our rate estimates are built from a model that synthesizes several publicly available sources: **Bureau of Labor Statistics (BLS) Occupational Employment and Wage Statistics (OEWS)** Annual national and state-level employed physician wage data, used as the baseline for regional and specialty wage variation. Available at bls.gov/oes. **CMS Medicare Physician Fee Schedule — Geographic Practice Cost Indices (GPCI)** CMS locality-level cost indices used to calibrate sub-regional rate variation within Census regions. **AMN Healthcare Annual Locum Tenens Survey** Industry survey data from AMN Healthcare, one of the largest physician staffing firms nationally. Published annually; includes specialty-level rate ranges and demand indices. **CHG Healthcare "State of Locum Tenens" Report** Annual industry report from CHG Healthcare (parent of CompHealth, Weatherby Healthcare). Includes specialty demand rankings and regional rate variation. **Weatherby Healthcare Compensation Data** Specialty-level rate ranges and setting-specific benchmarks published by Weatherby Healthcare. ## How We Model Rates BLS OEWS data reflects employed physician wages — not locum rates. We apply a structured adjustment: 1. **Benefits replacement markup (×1.28):** Employed physicians receive approximately 28% of total compensation as benefits (health insurance, retirement, malpractice, paid time off). Locum physicians bear these costs independently. 2. **Market premium by setting:** - Urban hospital: ×1.08–1.15 (competitive market, moderate premium for flexibility) - Rural critical access: ×1.20–1.30 (shortage market, significant premium) 3. **Regional index:** BLS state-level wage data calibrated against national averages. 4. **Cross-reference:** All modeled medians are compared against AMN, CHG, and Weatherby published ranges. Estimates deviating more than 20% from survey data are reviewed before publication. ## Data Vintage All rate data includes a vintage field indicating the year of the underlying source data. We update annually as new BLS OEWS, CMS GPCI, and industry survey data is released. | Source | Current Vintage | |--------|----------------| | BLS OEWS | 2024 | | CMS MPFS GPCI | 2025 | | AMN Healthcare Survey | 2025 | | CHG Healthcare Report | 2024 | ## Limitations - These are estimates, not guarantees. Actual locum rates vary based on individual negotiation, agency markup, credentialing timeline, and facility budget constraints. - BLS data does not distinguish locum from employed physician wages at the source level. - Regional averages mask significant intra-regional variation (e.g., NYC rates vs. upstate NY rates). - Rates change faster than annual updates — use this data as a baseline, not a ceiling.