Look up Medicare Geographic Practice Cost Index values for any locality. Understand how location affects physician reimbursement.
Adjusts for regional wage differences in physician compensation.
Range: 1.000 – 1.100
Adjusts for rent, staff wages, equipment, and supplies costs.
Range: 0.850 – 1.440
Adjusts for malpractice insurance costs by state and locality.
Range: 0.300 – 2.500
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| Locality ▲ | State ▲ | Work GPCI ▲ | PE GPCI ▲ | MP GPCI ▲ | Avg GPCI ▲ |
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Based on 2025 Medicare conversion factor of $33.29. For illustration purposes only.
The Geographic Practice Cost Index (GPCI) is a set of adjustment factors created by the Centers for Medicare & Medicaid Services (CMS) to reflect the relative cost of practicing medicine in different parts of the United States. Because the cost of living, wages, rent, and insurance premiums vary dramatically by region, CMS uses GPCIs to ensure that Medicare payments to physicians are fair and reflect local economic conditions.
GPCI values are updated annually as part of the Medicare Physician Fee Schedule (MPFS) Final Rule, typically published each November for the following calendar year. The values are derived from economic data sources including the Bureau of Labor Statistics, the American Community Survey, and state insurance commissioner reports.
There are three separate GPCI components, each adjusting a different part of the physician payment formula: Work GPCI, Practice Expense GPCI, and Malpractice GPCI. Together, these three factors ensure that the total Medicare reimbursement for any given procedure accounts for where it was performed.
The Work GPCI adjusts for geographic differences in the cost of physician labor. It reflects wage differences for the time, effort, skill, and stress involved in providing medical services. Congress has set a statutory floor of 1.000 for the Work GPCI, meaning no locality pays less than the national average on the work component. In practice, Work GPCI values range from 1.000 (the floor for most areas) to about 1.100 for high-cost metropolitan areas, with Alaska being the notable exception at 1.500.
The PE GPCI adjusts for geographic differences in the cost of maintaining a medical practice, including office rent, staff wages, medical equipment, and supplies. This is typically the most variable component, ranging from about 0.85 in lower-cost rural areas to over 1.40 in expensive metropolitan markets like San Francisco and San Jose. The PE GPCI has the largest impact on total payment for most procedure types.
The MP GPCI adjusts for geographic differences in professional liability insurance premiums. This component shows the widest range of all three GPCIs, from as low as 0.30 in states with tort reform (like South Carolina) to over 2.40 in areas with high malpractice costs (like Miami, FL). Malpractice insurance costs are driven by state legal environments, jury award patterns, and specialty risk profiles.
The Medicare physician payment formula incorporates GPCI values by multiplying each RVU component by its corresponding GPCI before applying the conversion factor:
// Medicare Payment Formula
Payment = [(Work RVU × Work GPCI)
+ (PE RVU × PE GPCI)
+ (MP RVU × MP GPCI)]
× Conversion Factor ($33.29)
Example: Consider a 99214 office visit in Manhattan, NY vs. rural Alabama:
Work: 1.92 × 1.094 = 2.100
PE: 1.07 × 1.316 = 1.408
MP: 0.10 × 1.657 = 0.166
Total: 3.674 RVUs × $33.29 = $122.31
Work: 1.92 × 1.000 = 1.920
PE: 1.07 × 0.878 = 0.939
MP: 0.10 × 0.590 = 0.059
Total: 2.918 RVUs × $33.29 = $97.14
The same procedure in Manhattan pays $25.17 more (26% higher) than in Alabama, entirely due to geographic cost differences reflected in the GPCI.
High PE GPCI areas correlate with expensive real estate markets and higher staff wages, concentrated in coastal metropolitan areas.
Low PE GPCI areas reflect lower costs of doing business in rural and Southern states, where rent, wages, and supplies are less expensive.
RVU Tracker automatically applies GPCI adjustments to your productivity data. See how your compensation changes by location and make informed career decisions.
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