CMS Provider Utilization & Payment Data - Physician and Other Supplier

General description

1. Database primary purpose - Provide information on services and procedures provided to Medicare beneficiaries by physicians and other healthcare professionals
2. Overall data type - Physicians and other supplier aggregates
3. Dataset type - Longitudinal
4. Data source - Claims
5. Data level - Provider level
6. Geographic location of the data collection sites - United States (although providers can be located in foreign countries)
7. Sponsor, manager, or home institution - Centers for Medicare & Medicaid Services (CMS)
8. Date range - 2012 - 2016
9. Geolocation data - Provider's street address, city, state, zip code, country
10. Hospital identifiers - National Provider Identifier (NPI) and organization name when the provider is registered in the National Plan & Provider Enumeration System (NPPES) as an organization
11. Physician identifiers - National Provider Identifier (NPI); first and last name when the provider is registered in NPPES as an individual; NPPES credential
12. Longitudinal tracking - Track providers through the above-mentioned identifiers
13. Financial variables - Total and average of the charges that the provider submitted for the service; Medicare payment amount
14. Clinical areas of interest - all
15. Variables that are uniquely present in this dataset - The Physician and Other Supplier contains information on utilization, payment (allowed amount and Medicare payment), and submitted charges organized by National Provider Identifier (NPI), Healthcare Common Procedure Coding System (HCPCS) code, and place of service. Also, contain 100% final-action (i.e., all claim adjustments have been resolved) physician/supplier Part B non-institutional line items for the Medicare fee-for-service (FFS) population
16. Database caveats and limitations - (1) Claims processed by Durable Medical Equipment, Prosthetic, Orthotics, and Supplies (DMEPOS) Medicare Administrative Contractor (MAC) are not included. (2) The data may not represent a physician’s entire practice since it only has information for Medicare beneficiaries with Part B FFS coverage. (3) The information presented does not indicate the quality of care provided by individual physicians. (4) The data are not risk adjusted and thus do not account for differences in the underlying severity of disease of patient populations treated by providers. (5) The file does not include data for services performed on 10 or fewer beneficiaries, so users should be aware that summing the data in the file may underestimate the true Part B FFS totals.

Applicable methods

1. Associations analysis, such as multivariable logistic regression model (1, 2), linear regression (3, 4), binomial regression (5)
2. Cost analysis (6)

High-impact designs

• Characterize changes in treatment and payment (7)

• Evaluate differences by sex in productivity, breadth of practice, and payments (8, 9)

• Examine the trends in scope and volume of procedures billed by advanced practice professionals (10)

• Assess characteristics of care by nonphysician clinicians (11)

• Evaluate the association between reported industry payments and physician-prescribing habits (12)

• Enrichment of the Physician and Other Supplier dataset through linkage to other datasets, such as CMS Physician Compare (13), MSSP Accountable Care Organizations (ACO) Provider-Level Research Identifiable File (14)

Data dictionary

Link to the dictionary

Variable categories

1. Provider characteristics (e.g., gender, specialty, Medicare participation, place of service, specific medical service, number of services provided, drug services)
2. Entity type (i.e., provider is an individual or organization)
3. Beneficiary characteristics (e.g., average age; number by sex, age group, race/ethnicity; number of beneficiaries qualified to receive Medicare and Medicaid benefits; number of beneficiaries with a determined condition)

Linkage to other datasets

• Linkages can be established for any dataset that might have provider identifiers (NPI or NPPES credentials) or geolocation data (zip code)