1Data Collection
All salary data on SalaryDr is submitted voluntarily and anonymously by practicing physicians through our multi-step salary submission form. The process is designed to be quick, anonymous, and comprehensive.
Physicians self-report their compensation details without providing their name or employer name. The form captures a complete picture of physician compensation including base salary, total compensation, bonuses, wRVUs, practice setting, employment type, and more.
The data architecture is fully de-identified from the ground up. We never ask for personally identifiable information that could link a salary submission back to the submitter.
2Verification Process
SalaryDr takes data integrity seriously. Every submission goes through a multi-layer verification pipeline to ensure only real physicians contribute to our dataset.
NPI Verification
Submitters provide their National Provider Identifier (NPI), which is validated against the NPPES registry in real time. This confirms the submitter is a licensed healthcare provider with an active NPI number.
AI-Powered Moderation
Advanced algorithms automatically screen every submission for outliers, data-entry errors, and implausible values. Submissions that fall outside expected ranges for a given specialty are flagged for further review.
Human Review
Submissions flagged by automated checks are routed to a manual review queue. A human reviewer evaluates the data for plausibility before it is approved and published to the platform.
Professional Role Verification
We verify that the submitter holds a qualifying professional role (Attending Physician, Fellow, Resident, or Dental Professional). This ensures our physician salary data reflects only MD/DO compensation.
3Data Points Collected
Our submission form captures a comprehensive set of compensation and career data points:
- Base salary (guaranteed annual compensation)
- Total compensation (base + bonuses + incentives)
- wRVU volume (Work Relative Value Units)
- Signing bonus
- Medical specialty & subspecialty
- Practice setting (private, hospital, academic, VA, locum)
- Employment type (W-2, 1099, partner/owner)
- Years of experience as an attending
- Work-life metrics (hours/week, call frequency, vacation)
- Satisfaction scores (overall, work-life balance, would choose again)
4Statistical Methodology
SalaryDr calculates and presents compensation data using standard statistical methods to ensure accuracy and transparency.
Key Statistical Measures
- Median (50th Percentile)
- The middle value when all salaries are sorted. This is our primary measure because it is less sensitive to outliers than the mean.
- Mean (Average)
- The arithmetic average of all salaries in a cohort. Useful but can be skewed by very high or very low values.
- Percentiles (25th, 75th, 90th)
- Show the distribution of salaries. The 25th percentile means 25% of physicians earn less; the 90th means only 10% earn more.
- Total Compensation
- Defined as base salary + bonus/incentive pay + any other cash compensation. This is the primary metric displayed throughout SalaryDr.
Minimum Sample Thresholds
We only display aggregated statistics (medians, percentiles, averages) for cohorts that meet a minimum sample size. This prevents misleading conclusions drawn from too few data points and ensures statistical relevance.
Outlier Handling
Submissions with extremely high or low total compensation values are flagged automatically. For broad display purposes, we filter physician salaries to plausible ranges to remove data-entry errors. The full dataset is available for specialty-specific breakdowns where wider ranges are expected.
All percentile calculations use linear interpolation on the sorted dataset. Statistics are recalculated in real time as new approved submissions enter the database.
5Update Frequency
SalaryDr data is updated daily as new submissions are received, verified, and approved. This is a fundamental differentiator from traditional compensation surveys, which are typically published annually and can be 12 to 18 months behind real-world conditions by the time they reach physicians.
All calculations are rolling — as new verified submissions are approved, medians, percentiles, and averages are recalculated automatically. Page-level caching ensures fast load times while still reflecting the latest data within a short revalidation window (typically 30 minutes to 1 hour).
6Comparison to Traditional Surveys
SalaryDr was built to address specific shortcomings in existing physician compensation data sources like MGMA, Medscape, and Doximity.
| Feature | SalaryDr | MGMA | Medscape | Doximity |
|---|---|---|---|---|
| Physician-Only | Yes (NPI verified) | Yes | Mostly | Yes |
| Update Frequency | Daily | Annual | Annual | Annual |
| Data Lag | Real-time | 12-18 months | 12-18 months | 12-18 months |
| Cost | Free | $3,000+/yr | Free (limited) | Free (limited) |
| Verification | NPI + AI + Human | Employer-reported | Self-reported | Self-reported |
| Community-Driven | Yes | No | Partially | No |
| Granularity | Specialty + State + City | Specialty + Region | Specialty | Specialty + Metro |
7Privacy & De-identification
Physician trust is paramount. Our data architecture ensures that salary submissions are fully anonymous and cannot be traced back to individual physicians.
- No PII stored with salary data: Salary submissions are stored separately from any identifying account information. There is no technical way to link a specific salary to a specific person.
- Anonymous by design: We never collect employer names, practice names, or any information that could identify the submitter through their workplace.
- No data sold to employers: SalaryDr never sells individual submission data to employers, recruiters, or any third party.
- Aggregated reporting only: All public-facing data is presented in aggregate form (medians, percentiles, ranges) to prevent re-identification.
- Minimum cohort sizes: We enforce minimum sample sizes before displaying data for any specialty-location combination, preventing identification through small group analysis.
For full details, see our Privacy Policy and Data Retention Policy.
8Data Limitations
We believe in full transparency about the strengths and limitations of our data.
- Self-reported data: All compensation figures are self-reported. While NPI verification confirms provider identity, we cannot independently audit each salary figure.
- Sample size variation: Some specialties and geographic regions have significantly more data than others. Coverage depth varies.
- Selection bias: Physicians who voluntarily submit may not be perfectly representative of all physicians in a given specialty or location.
- Benefits not included: Total compensation primarily reflects cash compensation. Non-cash benefits (health insurance, retirement contributions, CME allowances) are not included unless specifically noted.
Help Improve Our Dataset
SalaryDr gets better with every submission. Your anonymous contribution helps thousands of colleagues benchmark their compensation and negotiate better contracts.