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Medicare Physician & Other Practitioners APIs

Source: vignettes/articles/mcr-phys-other-pract.Rmd
mcr-phys-other-pract.Rmd



Information on services and procedures provided to Original Medicare (fee-for-service) Part B (Medical Insurance) beneficiaries by physicians and other healthcare professionals.


The Centers for Medicare & Medicaid Services (CMS) has prepared a public data set, the Provider Utilization and Payment Data Physician and Other Practitioners Dataset, with information on services and procedures provided to Medicare beneficiaries by physicians and other healthcare professionals. The Physician and Other Practitioners Dataset 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. The data in the Physician and Other Practitioners dataset contains 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. Claims processed by Durable Medical Equipment, Prosthetic, Orthotics and Supplies (DMEPOS) Medicare Administrative Contractor (MAC) are not included in the Physician and Other Practitioners Dataset.


Physician & Other Practitioners: by Provider


The Provider data subset provides information on use, payments, submitted charges and beneficiary demographic and health characteristics organized by National Provider Identifier (NPI). This dataset is based on information gathered from CMS administrative claims data for Original Medicare Part B beneficiaries available from the CMS Chronic Conditions Data Warehouse.

  • Data update frequency: Annually
  • Data source: Centers for Medicare & Medicaid Services

Examples 

2013:2021 |> 
  purrr::map(\(year) physician_by_provider(year, npi = 1003000423)) |> 
  purrr::list_rbind()
#> # A tibble: 9 × 70
#>    year npi     first_name middle_name last_name credential gender entype street
#>   <int> <chr>   <chr>      <chr>       <chr>     <chr>      <chr>  <chr>  <chr> 
#> 1  2013 100300… Jennifer   A           Velotta   MD         F      Indiv… 11100…
#> 2  2014 100300… Jennifer   A           Velotta   MD         F      Indiv… 11100…
#> 3  2015 100300… Jennifer   A           Velotta   MD         F      Indiv… 11100…
#> 4  2016 100300… Jennifer   A           Velotta   MD         F      Indiv… 11100…
#> 5  2017 100300… Jennifer   A           Velotta   MD         F      Indiv… 11100…
#> 6  2018 100300… Jennifer   A           Velotta   MD         F      Indiv… 11100…
#> 7  2019 100300… Jennifer   A           Velotta   MD         F      Indiv… 11100…
#> 8  2020 100300… Jennifer   A           Velotta   MD         F      Indiv… 11100…
#> 9  2021 100300… Jennifer   A           Velotta   MD         F      Indiv… 11100…
#> # ℹ 61 more variables: city <chr>, state <chr>, fips <chr>, zipcode <chr>,
#> #   ruca <chr>, country <chr>, specialty <chr>, par <lgl>, tot_hcpcs <int>,
#> #   tot_benes <int>, tot_srvcs <int>, tot_charges <dbl>, tot_allowed <dbl>,
#> #   tot_payment <dbl>, tot_std_pymt <dbl>, drug_hcpcs <int>, drug_benes <int>,
#> #   drug_srvcs <int>, drug_charges <dbl>, drug_allowed <dbl>,
#> #   drug_payment <dbl>, drug_std_pymt <dbl>, med_hcpcs <int>, med_benes <int>,
#> #   med_srvcs <int>, med_charges <dbl>, med_allowed <dbl>, med_payment <dbl>, …


physician_by_provider(year = 2021, 
                      entype = "I", 
                      city = "Hershey", 
                      state = "PA", 
                      fips = 42, 
                      ruca = 1, 
                      gender = "F", 
                      credential = "MD", 
                      specialty = "Anesthesiology")
#> # A tibble: 17 × 70
#>     year npi    first_name middle_name last_name credential gender entype street
#>    <int> <chr>  <chr>      <chr>       <chr>     <chr>      <chr>  <chr>  <chr> 
#>  1  2021 10232… Melissa    L           Coleman   MD         F      Indiv… 500 U…
#>  2  2021 10634… Padmani    NA          Dhar      MD         F      Indiv… 500 U…
#>  3  2021 11240… To-Nhu     NA          Vu        MD         F      Indiv… 500 U…
#>  4  2021 12159… Cathy      D           Paige     MD         F      Indiv… 500 U…
#>  5  2021 13062… Eileen     M           Micaroni  MD         F      Indiv… 500 U…
#>  6  2021 14473… Anita      NA          Malhotra  MD         F      Indiv… 500 U…
#>  7  2021 15482… Sonia      J           Vaida     MD         F      Indiv… 500 U…
#>  8  2021 15583… Priti      G           Dalal     MD         F      Indiv… 500 U…
#>  9  2021 16090… Zoulfira   NA          Nisnevit… MD         F      Indiv… 500 U…
#> 10  2021 17503… Niraja     NA          Rajan     MD         F      Indiv… 500 U…
#> 11  2021 18010… Sharon     NA          Lee       MD         F      Indiv… 500 U…
#> 12  2021 18018… Jansie     NA          Prozesky  MD         F      Indiv… 500 U…
#> 13  2021 18514… Kelly      S           Gidusko   MD         F      Indiv… 500 U…
#> 14  2021 18717… Rochelle   NA          Sims      MD         F      Indiv… 500 U…
#> 15  2021 18917… Elizabeth  H           Sinz      MD         F      Indiv… 500 U…
#> 16  2021 19222… Kristin    B           Brennan   MD         F      Indiv… 500 U…
#> 17  2021 19628… Sadie      E           Smith     MD         F      Indiv… 500 U…
#> # ℹ 61 more variables: city <chr>, state <chr>, fips <chr>, zipcode <chr>,
#> #   ruca <chr>, country <chr>, specialty <chr>, par <lgl>, tot_hcpcs <int>,
#> #   tot_benes <int>, tot_srvcs <int>, tot_charges <dbl>, tot_allowed <dbl>,
#> #   tot_payment <dbl>, tot_std_pymt <dbl>, drug_hcpcs <int>, drug_benes <int>,
#> #   drug_srvcs <int>, drug_charges <dbl>, drug_allowed <dbl>,
#> #   drug_payment <dbl>, drug_std_pymt <dbl>, med_hcpcs <int>, med_benes <int>,
#> #   med_srvcs <int>, med_charges <dbl>, med_allowed <dbl>, med_payment <dbl>, …

Physician & Other Practitioners: by Geography and Service


Examples 

physician_by_geography(hcpcs_code = "0002A", year = 2020)
#> # A tibble: 9 × 16
#>    year level    sublevel   fips  hcpcs_code hcpcs_desc hcpcs_drug place_of_srvc
#>   <int> <chr>    <chr>      <chr> <chr>      <chr>      <lgl>      <chr>        
#> 1  2020 National National   NA    0002A      Adm sarsc… FALSE      O            
#> 2  2020 State    California 06    0002A      Adm sarsc… FALSE      O            
#> 3  2020 State    Florida    12    0002A      Adm sarsc… FALSE      O            
#> 4  2020 State    Illinois   17    0002A      Adm sarsc… FALSE      O            
#> 5  2020 State    Maine      23    0002A      Adm sarsc… FALSE      O            
#> 6  2020 State    Maryland   24    0002A      Adm sarsc… FALSE      O            
#> 7  2020 State    Massachus… 25    0002A      Adm sarsc… FALSE      O            
#> 8  2020 State    New Jersey 34    0002A      Adm sarsc… FALSE      O            
#> 9  2020 State    Pennsylva… 42    0002A      Adm sarsc… FALSE      O            
#> # ℹ 8 more variables: tot_provs <int>, tot_benes <int>, tot_srvcs <int>,
#> #   tot_day <int>, avg_charges <dbl>, avg_allowed <dbl>, avg_payment <dbl>,
#> #   avg_std_pymt <dbl>



service <- purrr::map_dfr(as.character(2013:2020), ~physician_by_service(npi = 1003000126, year = .x))



Physician & Other Practitioners: by Provider and Service


The spending and utilization data in the Physician and Other Practitioners by Provider and Service Dataset are aggregated to the following:


  1. the NPI for the performing provider,
  2. the Healthcare Common Procedure Coding System (HCPCS) code, and
  3. the place of service (either facility or non-facility).


There can be multiple records for a given NPI based on the number of distinct HCPCS codes that were billed and where the services were provided. Data have been aggregated based on the place of service because separate fee schedules apply depending on whether the place of service submitted on the claim is facility or non-facility.


Examples 

# Search by NPI
physician_by_service(npi = 1003000126)
#> Error in `physician_by_service()`:
#> ! `year` is absent but must be supplied.
# Search by Last Name for 2019
physician_by_service(npi = 1720392988, year = 2019)
#> # A tibble: 20 × 28
#>     year npi        entype    first_name middle_name last_name credential gender
#>    <int> <chr>      <chr>     <chr>      <chr>       <chr>     <chr>      <chr> 
#>  1  2019 1720392988 Individu… Mustafa    NA          Abas      MD,        M     
#>  2  2019 1720392988 Individu… Mustafa    NA          Abas      MD,        M     
#>  3  2019 1720392988 Individu… Mustafa    NA          Abas      MD,        M     
#>  4  2019 1720392988 Individu… Mustafa    NA          Abas      MD,        M     
#>  5  2019 1720392988 Individu… Mustafa    NA          Abas      MD,        M     
#>  6  2019 1720392988 Individu… Mustafa    NA          Abas      MD,        M     
#>  7  2019 1720392988 Individu… Mustafa    NA          Abas      MD,        M     
#>  8  2019 1720392988 Individu… Mustafa    NA          Abas      MD,        M     
#>  9  2019 1720392988 Individu… Mustafa    NA          Abas      MD,        M     
#> 10  2019 1720392988 Individu… Mustafa    NA          Abas      MD,        M     
#> 11  2019 1720392988 Individu… Mustafa    NA          Abas      MD,        M     
#> 12  2019 1720392988 Individu… Mustafa    NA          Abas      MD,        M     
#> 13  2019 1720392988 Individu… Mustafa    NA          Abas      MD,        M     
#> 14  2019 1720392988 Individu… Mustafa    NA          Abas      MD,        M     
#> 15  2019 1720392988 Individu… Mustafa    NA          Abas      MD,        M     
#> 16  2019 1720392988 Individu… Mustafa    NA          Abas      MD,        M     
#> 17  2019 1720392988 Individu… Mustafa    NA          Abas      MD,        M     
#> 18  2019 1720392988 Individu… Mustafa    NA          Abas      MD,        M     
#> 19  2019 1720392988 Individu… Mustafa    NA          Abas      MD,        M     
#> 20  2019 1720392988 Individu… Mustafa    NA          Abas      MD,        M     
#> # ℹ 20 more variables: specialty <chr>, street <chr>, city <chr>, state <chr>,
#> #   fips <chr>, zipcode <chr>, ruca <chr>, country <chr>, par <lgl>,
#> #   hcpcs_code <chr>, hcpcs_desc <chr>, hcpcs_drug <chr>, place_of_srvc <chr>,
#> #   tot_benes <int>, tot_srvcs <int>, tot_day <int>, avg_charges <dbl>,
#> #   avg_allowed <dbl>, avg_payment <dbl>, avg_std_pymt <dbl>
# Multiple NPIs
c(1003026055,
          1720392988,
          1518184605,
          1922056829,
          1083879860)
#> [1] 1003026055 1720392988 1518184605 1922056829 1083879860

#npis |> purrr::map_dfr(physician_by_service)
# Retrieve All Provider Data, 2013-2020
purrr::map_dfr(as.character(2013:2020),
~physician_by_service(npi = 1003000126, year = .x))
#> # A tibble: 78 × 28
#>     year npi        entype    first_name middle_name last_name credential gender
#>    <int> <chr>      <chr>     <chr>      <chr>       <chr>     <chr>      <chr> 
#>  1  2013 1003000126 Individu… Ardalan    NA          Enkeshafi MD         M     
#>  2  2013 1003000126 Individu… Ardalan    NA          Enkeshafi MD         M     
#>  3  2013 1003000126 Individu… Ardalan    NA          Enkeshafi MD         M     
#>  4  2013 1003000126 Individu… Ardalan    NA          Enkeshafi MD         M     
#>  5  2013 1003000126 Individu… Ardalan    NA          Enkeshafi MD         M     
#>  6  2013 1003000126 Individu… Ardalan    NA          Enkeshafi MD         M     
#>  7  2013 1003000126 Individu… Ardalan    NA          Enkeshafi MD         M     
#>  8  2014 1003000126 Individu… Ardalan    NA          Enkeshafi MD         M     
#>  9  2014 1003000126 Individu… Ardalan    NA          Enkeshafi MD         M     
#> 10  2014 1003000126 Individu… Ardalan    NA          Enkeshafi MD         M     
#> # ℹ 68 more rows
#> # ℹ 20 more variables: specialty <chr>, street <chr>, city <chr>, state <chr>,
#> #   fips <chr>, zipcode <chr>, ruca <chr>, country <chr>, par <lgl>,
#> #   hcpcs_code <chr>, hcpcs_desc <chr>, hcpcs_drug <chr>, place_of_srvc <chr>,
#> #   tot_benes <int>, tot_srvcs <int>, tot_day <int>, avg_charges <dbl>,
#> #   avg_allowed <dbl>, avg_payment <dbl>, avg_std_pymt <dbl>

Provider Data Dictionary

Variable Description

rndrng_npi
National Provider Identifier
National Provider Identifier (NPI) for the rendering provider on the claim. The provider NPI is the numeric identifier registered in NPPES.

rndrng_prvdr_last_org_name
Last Name/Organization Name of the Provider
When the provider is registered in NPPES as an individual (entity type code=’I’), this is the provider’s last name. When the provider is registered as an organization (entity type code = ‘O’), this is the organization name.

rndrng_prvdr_first_name
First Name of the Provider
When the provider is registered in NPPES as an individual (entity type code=’I’), this is the provider’s first name. When the provider is registered as an organization (entity type code = ‘O’), this will be blank.

rndrng_prvdr_mi
Middle Initial of the Provider
When the provider is registered in NPPES as an individual (entity type code=’I’), this is the provider’s middle initial. When the provider is registered as an organization (entity type code = ‘O’), this will be blank.

rndrng_prvdr_crdntls
Credentials of the Provider
When the provider is registered in NPPES as an individual (entity type code=’I’), these are the provider’s credentials. When the provider is registered as an organization (entity type code = ‘O’), this will be blank.

rndrng_prvdr_gndr
Gender of the Provider
When the provider is registered in NPPES as an individual (entity type code=’I’), this is the provider’s gender. When the provider is registered as an organization (entity type code = ‘O’), this will be blank.

rndrng_prvdr_ent_cd
Entity Type of the Provider
Type of entity reported in NPPES. An entity code of ‘I’ identifies providers registered as individuals and an entity type code of ‘O’ identifies providers registered as organizations.

rndrng_prvdr_st1
Street Address 1 of the Provider
The first line of the provider’s street address, as reported in NPPES.

rndrng_prvdr_st2
Street Address 2 of the Provider
The second line of the provider’s street address, as reported in NPPES.

rndrng_prvdr_city
City of the Provider
The city where the provider is located, as reported in NPPES.

rndrng_prvdr_state_abrvtn
State Abbreviation of the Provider
The state where the provider is located, as reported in NPPES. The fifty U.S. states and the District of Columbia are reported by the state postal abbreviation. The following values are used for all other areas:

rndrng_prvdr_state_fips
State FIPS Code of the Provider
FIPS code for rendering provider's state.

rndrng_prvdr_zip5
Zip Code of the Provider
The provider’s zip code, as reported in NPPES.

rndrng_prvdr_ruca
RUCA Code of the Provider
Rural-Urban Commuting Area Codes (RUCAs), are a Census tract-based classification scheme that utilizes the standard Bureau of Census Urbanized Area and Urban Cluster definitions in combination with work commuting information to characterize all of the nation's Census tracts regarding their rural and urban status and relationships. The Referring Provider ZIP code was cross walked to the United States Department of Agriculture (USDA) 2010 Rural-Urban Commuting Area Codes.

rndrng_prvdr_ruca_desc
RUCA Description
Description of Rural-Urban Commuting Area (RUCA) Code

rndrng_prvdr_cntry
Country Code of the Provider
The country where the provider is located, as reported in NPPES. The country code will be ‘US’ for any state or U.S. possession. For foreign countries (i.e., state values of ‘ZZ’), the provider country values include the following:

rndrng_prvdr_type
Provider Type of the Provider
Derived from the provider specialty code reported on the claim. For providers that reported more than one specialty code on their claims, this is the specialty code associated with the largest number of services.

rndrng_prvdr_mdcr_prtcptg_ind
Medicare Participation Indicator
Identifies whether the provider participates in Medicare and/or accepts assignment of Medicare allowed amounts. The value will be ‘Y’ for any provider that had at least one claim identifying the provider as participating in Medicare or accepting assignment of Medicare allowed amounts within HCPCS code and place of service. A non-participating provider may elect to accept Medicare allowed amounts for some services and not accept Medicare allowed amounts for other services.

tot_hcpcs_cds
Number of HCPCS
Total number of unique HCPCS codes.

tot_benes
Number of Medicare Beneficiaries
Total Medicare beneficiaries receiving services from the provider. The beneficiary counts reported in the demographic sub-groups (i.e., age, sex, race and entitlement) may not aggregate to the ‘Number of Unique Beneficiaries’ due to the suppression of beneficiaries fewer than 11 within the demographic sub-groups. In addition, a small percentage of beneficiaries are reflected in the “Number of Unique Beneficiaries” but are not reflected in the beneficiary demographic information due to the lack of demographic information available at the time of reporting.

tot_srvcs
Number of Services
Total provider services.

tot_sbmtd_chrg
Total Submitted Charge Amount
The total charges that the provider submitted for all services.

tot_mdcr_alowd_amt
Total Medicare Allowed Amount
The Medicare allowed amount for all provider services. This figure is the sum of the amount Medicare pays, the deductible and coinsurance amounts that the beneficiary is responsible for paying, and any amounts that a third party is responsible for paying.

tot_mdcr_pymt_amt
Total Medicare Payment Amount
Total amount that Medicare paid after deductible and coinsurance amounts have been deducted for all the provider's line item services.

tot_mdcr_stdzd_amt
Total Medicare Standardized Payment Amount
Total amount that Medicare paid after deductible and coinsurance amounts have been deducted for the line item service and after standardization of the Medicare payment has been applied. Standardization removes geographic differences in payment rates for individual services, such as those that account for local wages or input prices and makes Medicare payments across geographic areas comparable, so that differences reflect variation in factors such as physicians’ practice patterns and beneficiaries’ ability and willingness to obtain care.

drug_sprsn_ind
Drug Suppress Indicator
Identifies whether the utilization, cost and payment information associated with HCPCS codes for drug services as listed on the Medicare Part B Drug Average Sales Price (ASP) list have been suppressed. An '*' identifies that the suppressed information is based on fewer than 11 beneficiaries and a '#' identifies that the information has been counter suppressed to prevent the re-calculation of information suppressed due to fewer than 11 beneficiaries. For example, if the information associated with Drug services has been suppressed because fewer than 11 beneficiaries received these services from a provider, then the information associated with Medical services must also be suppressed so that the information associated with Drug services cannot be recalculated by subtracting the Medical values from the provider's overall values.

drug_tot_hcpcs_cds
Number of HCPCS Associated With Drug Services
Total number of HCPCS codes for drug services, as defined from the Medicare Part B Drug ASP File.

drug_tot_benes
Number of Medicare Beneficiaries With Drug Services
Total Medicare beneficiaries receiving drug services, as defined from the Medicare Part B Drug ASP File.

drug_tot_srvcs
Number of Drug Services
Total drug services, as defined from the Medicare Part B Drug ASP File.

drug_sbmtd_chrg
Total Drug Submitted Charge Amount
The total charges that the provider submitted for drug services, as defined from the Medicare Part B Drug ASP File.

drug_mdcr_alowd_amt
Total Drug Medicare Allowed Amount
The Medicare allowed amount for drug services, as defined from the Medicare Part B Drug ASP File. This figure is the sum of the amount Medicare pays, the deductible and coinsurance amounts that the beneficiary is responsible for paying, and any amounts that a third party is responsible for paying.

drug_mdcr_pymt_amt
Total Drug Medicare Payment Amount
Total amount that Medicare paid after deductible and coinsurance amounts have been deducted for all the provider's line item drug services, as defined from the Medicare Part B Drug ASP File.

drug_mdcr_stdzd_amt
Total Drug Medicare Standardized Payment Amount
Total amount that Medicare paid after deductible and coinsurance amounts have been deducted for the line item drug service, as defined from the Medicare Part B Drug ASP File and after standardization of the Medicare payment has been applied. Standardization removes geographic differences in payment rates for individual services, such as those that account for local wages or input prices and makes Medicare payments across geographic areas comparable, so that differences reflect variation in factors such as physicians’ practice patterns and beneficiaries’ ability and willingness to obtain care.

med_sprsn_ind
Medical Suppress Indicator
Identifies whether the utilization, cost and payment information associated with HCPCS codes for Medical (non-ASP) services have been suppressed. An '*' identifies that the suppressed information is based on fewer than 11 beneficiaries and a '#' identifies that the information has been counter suppressed to prevent the re-calculation of information suppressed due to fewer than 11 beneficiaries. For example, if the information associated with Medical (non-ASP) services has been suppressed because fewer than 11 beneficiaries received these services from a provider, then the information associated with Drug services must also be suppressed so that the information associated with Medical services cannot be recalculated by subtracting the Drug values from the provider's overall values.

med_tot_hcpcs_cds
Number of HCPCS Associated With Medical Services
Total number of HCPCS codes associated with medical (non-ASP) services.

med_tot_benes
Number of Medicare Beneficiaries With Medical Services
Total Medicare beneficiaries receiving medical (non-ASP) services.

med_tot_srvcs
Number of Medical Services
Total medical (non-ASP) services.

med_sbmtd_chrg
Total Medical Submitted Charge Amount
The total charges that the provider submitted for medical (non-ASP) services.

med_mdcr_alowd_amt
Total Medical Medicare Allowed Amount
The Medicare allowed amount for medical (non-ASP) services. This figure is the sum of the amount Medicare pays, the deductible and coinsurance amounts that the beneficiary is responsible for paying, and any amounts that a third party is responsible for paying.

med_mdcr_pymt_amt
Total Medical Medicare Payment Amount
Total amount that Medicare paid after deductible and coinsurance amounts have been deducted for all of the provider's line item medical (non-ASP) services.

med_mdcr_stdzd_amt
Total Medical Medicare Standardized Payment Amount
Total amount that Medicare paid after deductible and coinsurance amounts have been deducted for the line item medical (non-ASP) service, as defined from the Medicare Part B Drug ASP File and after standardization of the Medicare payment has been applied. Standardization removes geographic differences in payment rates for individual services, such as those that account for local wages or input prices and makes Medicare payments across geographic areas comparable, so that differences reflect variation in factors such as physicians’ practice patterns and beneficiaries’ ability and willingness to obtain care.

bene_avg_age
Average Age of Beneficiaries
Average age of beneficiaries. Beneficiary age is calculated at the end of the calendar year or at the time of death.

bene_age_lt_65_cnt
Number of Beneficiaries Age Less 65
Number of beneficiaries under the age of 65. Beneficiary age is calculated at the end of the calendar year or at the time of death.

bene_age_65_74_cnt
Number of Beneficiaries Age 65 to 74
Number of beneficiaries between the ages of 65 and 74. Beneficiary age is calculated at the end of the calendar year or at the time of death.

bene_age_75_84_cnt
Number of Beneficiaries Age 75 to 84
Number of beneficiaries between the ages of 75 and 84. Beneficiary age is calculated at the end of the calendar year or at the time of death.

bene_age_gt_84_cnt
Number of Beneficiaries Age Greater 84
Number of beneficiaries over the age of 84. Beneficiary age is calculated at the end of the calendar year or at the time of death.

bene_feml_cnt
Number of Female Beneficiaries
Number of female beneficiaries.

bene_male_cnt
Number of Male Beneficiaries
Number of male beneficiaries.

bene_race_wht_cnt
Number of Non-Hispanic White Beneficiaries
Number of non-Hispanic white beneficiaries. Race/ethnicity information is based on the variable RTI_RACE_CD from the CMS CCW enrollment database. The RTI_RACE_CD variable is based upon a validated algorithm that uses Census surname lists and geography to improve the accuracy of race/ethnicity classification, particularly for those who are Hispanic or Asian/Pacific Islanders.

bene_race_black_cnt
Number of Black or African American Beneficiaries
Number of non-Hispanic black or African American beneficiaries. Race/ethnicity information is based on the variable RTI_RACE_CD from the CMS CCW enrollment database. The RTI_RACE_CD variable is based upon a validated algorithm that uses Census surname lists and geography to improve the accuracy of race/ethnicity classification, particularly for those who are Hispanic or Asian/Pacific Islanders.

bene_race_api_cnt
Number of Asian Pacific Islander Beneficiaries
Number of Asian Pacific Islander beneficiaries. Race/ethnicity information is based on the variable RTI_RACE_CD from the CMS CCW enrollment database. The RTI_RACE_CD variable is based upon a validated algorithm that uses Census surname lists and geography to improve the accuracy of race/ethnicity classification, particularly for those who are Hispanic or Asian/Pacific Islanders.

bene_race_hspnc_cnt
Number of Hispanic Beneficiaries
Number of Hispanic beneficiaries. Race/ethnicity information is based on the variable RTI_RACE_CD from the CMS CCW enrollment database. The RTI_RACE_CD variable is based upon a validated algorithm that uses Census surname lists and geography to improve the accuracy of race/ethnicity classification, particularly for those who are Hispanic or Asian/Pacific Islanders.

bene_race_natind_cnt
Number of American Indian/Alaska Native Beneficiaries
Number of American Indian or Alaska Native beneficiaries. Race/ethnicity information is based on the variable RTI_RACE_CD from the CMS CCW enrollment database. The RTI_RACE_CD variable is based upon a validated algorithm that uses Census surname lists and geography to improve the accuracy of race/ethnicity classification, particularly for those who are Hispanic or Asian/Pacific Islanders.

bene_race_othr_cnt
Number of Beneficiaries With Race Not Elsewhere Classified
Number of beneficiaries with race not elsewhere classified.

bene_dual_cnt
Number of Beneficiaries With Medicare & Medicaid Entitlement
Number of Medicare beneficiaries qualified to receive Medicare and Medicaid benefits. Beneficiaries are classified as Medicare and Medicaid entitlement if in any month in the given calendar year they were receiving full or partial Medicaid benefits.

bene_ndual_cnt
Number of Beneficiaries With Medicare Only Entitlement
Number of Medicare beneficiaries qualified to receive Medicare only benefits. Beneficiaries are classified as Medicare only entitlement if they received zero months of any Medicaid benefits (full or partial) in the given calendar year.

bene_cc_af_pct
Percent (%) of Beneficiaries Identified With Atrial Fibrillation
Percent of beneficiaries meeting the CCW chronic condition algorithm for atrial fibrillation. To protect the privacy of Medicare beneficiaries, the number of beneficiaries fewer than 11 have been suppressed and the percent of beneficiaries between 75% and 100% have been top-coded at 75%. Information on source data is available from the CMS Chronic Conditions Warehouse (CCW).

bene_cc_alzhmr_pct
Percent (%) of Beneficiaries Identified With Alzheimer’s Disease or Dementia
Percent of beneficiaries meeting the CCW chronic condition algorithm for Alzheimer’s, related disorders, or dementia. To protect the privacy of Medicare beneficiaries, the number of beneficiaries fewer than 11 have been suppressed and the percent of beneficiaries between 75% and 100% have been top-coded at 75%. Information on source data is available from the CMS Chronic Conditions Warehouse (CCW).

bene_cc_asthma_pct
Percent (%) of Beneficiaries Identified With Asthma
Percent of beneficiaries meeting the CCW chronic condition algorithm for Asthma. To protect the privacy of Medicare beneficiaries, the number of beneficiaries fewer than 11 have been suppressed and the percent of beneficiaries between 75% and 100% have been top-coded at 75%. Information on source data is available from the CMS Chronic Conditions Warehouse (CCW).

bene_cc_cncr_pct
Percent (%) of Beneficiaries Identified With Cancer
Percent of beneficiaries meeting the CCW chronic condition algorithms for cancer. Includes breast cancer, colorectal cancer, lung cancer and prostate cancer. To protect the privacy of Medicare beneficiaries, the number of beneficiaries fewer than 11 have been suppressed and the percent of beneficiaries between 75% and 100% have been top-coded at 75%. Information on source data is available from the CMS Chronic Conditions Warehouse (CCW).

bene_cc_chf_pct
Percent (%) of Beneficiaries Identified With Heart Failure
Percent of beneficiaries meeting the CCW chronic condition algorithm for heart failure. To protect the privacy of Medicare beneficiaries, the number of beneficiaries fewer than 11 have been suppressed and the percent of beneficiaries between 75% and 100% have been top-coded at 75%. Information on source data is available from the CMS Chronic Conditions Warehouse (CCW).

bene_cc_ckd_pct
Percent (%) of Beneficiaries Identified With Chronic Kidney Disease
Percent of beneficiaries meeting the CCW chronic condition algorithm for chronic kidney disease.To protect the privacy of Medicare beneficiaries, the number of beneficiaries fewer than 11 have been suppressed and the percent of beneficiaries between 75% and 100% have been top-coded at 75%. Information on source data is available from the CMS Chronic Conditions Warehouse (CCW).

bene_cc_copd_pct
Percent (%) of Beneficiaries Identified With Chronic Obstructive Pulmonary Disease
Percent of beneficiaries meeting the CCW chronic condition algorithm for chronic obstructive pulmonary disease. To protect the privacy of Medicare beneficiaries, the number of beneficiaries fewer than 11 have been suppressed and the percent of beneficiaries between 75% and 100% have been top-coded at 75%. Information on source data is available from the CMS Chronic Conditions Warehouse (CCW).

bene_cc_dprssn_pct
Percent (%) of Beneficiaries Identified With Depression
Percent of beneficiaries meeting the CCW chronic condition algorithm for depression. To protect the privacy of Medicare beneficiaries, the number of beneficiaries fewer than 11 have been suppressed and the percent of beneficiaries between 75% and 100% have been top-coded at 75%. Information on source data is available from the CMS Chronic Conditions Warehouse (CCW).

bene_cc_dbts_pct
Percent (%) of Beneficiaries Identified With Diabetes
Percent of beneficiaries meeting the CCW chronic condition algorithm for diabetes. To protect the privacy of Medicare beneficiaries, the number of beneficiaries fewer than 11 have been suppressed and the percent of beneficiaries between 75% and 100% have been top-coded at 75%. Information on source data is available from the CMS Chronic Conditions Warehouse (CCW).

bene_cc_hyplpdma_pct
Percent (%) of Beneficiaries Identified With Hyperlipidemia
Percent of beneficiaries meeting the CCW chronic condition algorithm for hyperlipidemia. To protect the privacy of Medicare beneficiaries, the number of beneficiaries fewer than 11 have been suppressed and the percent of beneficiaries between 75% and 100% have been top-coded at 75%. Information on source data is available from the CMS Chronic Conditions Warehouse (CCW).

bene_cc_hyprtnsn_pct
Percent (%) of Beneficiaries Identified With Hypertension
Percent of beneficiaries meeting the CCW chronic condition algorithm for hypertension. To protect the privacy of Medicare beneficiaries, the number of beneficiaries fewer than 11 have been suppressed and the percent of beneficiaries between 75% and 100% have been top-coded at 75%. Information on source data is available from the CMS Chronic Conditions Warehouse (CCW).

bene_cc_ihd_pct
Percent (%) of Beneficiaries Identified With Ischemic Heart Disease
Percent of beneficiaries meeting the CCW chronic condition algorithm for ischemic heart disease. To protect the privacy of Medicare beneficiaries, the number of beneficiaries fewer than 11 have been suppressed and the percent of beneficiaries between 75% and 100% have been top-coded at 75%. Information on source data is available from the CMS Chronic Conditions Warehouse (CCW).

bene_cc_opo_pct
Percent (%) of Beneficiaries Identified With Osteoporosis
Percent of beneficiaries meeting the CCW chronic condition algorithm for osteoporosis. To protect the privacy of Medicare beneficiaries, the number of beneficiaries fewer than 11 have been suppressed and the percent of beneficiaries between 75% and 100% have been top-coded at 75%. Information on source data is available from the CMS Chronic Conditions Warehouse (CCW).

bene_cc_raoa_pct
Percent (%) of Beneficiaries Identified With Rheumatoid Arthritis / Osteoarthritis
Percent of beneficiaries meeting the CCW chronic condition algorithm for rheumatoid arthritis/osteoarthritis. To protect the privacy of Medicare beneficiaries, the number of beneficiaries fewer than 11 have been suppressed and the percent of beneficiaries between 75% and 100% have been top-coded at 75%. Information on source data is available from the CMS Chronic Conditions Warehouse (CCW).

bene_cc_sz_pct
Percent (%) of Beneficiaries Identified With Schizophrenia / Other Psychotic Disorders
Percent of beneficiaries meeting the CCW chronic condition algorithm for schizophrenia and other psychotic disorders. To protect the privacy of Medicare beneficiaries, the number of beneficiaries fewer than 11 have been suppressed and the percent of beneficiaries between 75% and 100% have been top-coded at 75%. Information on source data is available from the CMS Chronic Conditions Warehouse (CCW).

bene_cc_strok_pct
Percent (%) of Beneficiaries Identified With Stroke
Percent of beneficiaries meeting the CCW chronic condition algorithm for stroke. To protect the privacy of Medicare beneficiaries, the number of beneficiaries fewer than 11 have been suppressed and the percent of beneficiaries between 75% and 100% have been top-coded at 75%. Information on source data is available from the CMS Chronic Conditions Warehouse (CCW).

bene_avg_risk_scre
Average HCC Risk Score of Beneficiaries
Average Hierarchical Condition Category (HCC) risk score of beneficiaries.

Geography Data Dictionary

Variable Description

rndrng_prvdr_geo_lvl
Geography Level
Identifies the level of geography that the data in the row has been aggregated. A value of 'State' indicates the data in the row is aggregated to a single state identified in the Rendering Provider State column for a given HCPCS Code Level. A value of 'National' indicates the data in the row is aggregated across all states for a given HCPCS Code Level.

rndrng_prvdr_geo_cd
Rendering Provider Geography Code
FIPS code of the referring provider state. This variable is blank when reported at the national level.

rndrng_prvdr_geo_desc
Rendering Provider Geography Description
The state name where the provider is located, as reported in NPPES. The values include the 50 United States, District of Columbia, U.S. territories, Armed Forces areas, Unknown and Foreign Country. Data aggregated at the National level are identified by the word 'National'.

hcpcs_cd
HCPCS Code
HCPCS code used to identify the specific medical service furnished by the provider. HCPCS codes include two levels. Level I codes are the Current Procedural Terminology (CPT) codes that are maintained by the American Medical Association and Level II codes are created by CMS to identify products, supplies and services not covered by the CPT codes (such as ambulance services). CPT codes, descriptions and other data only are copyright 2016 American Medical Association. All rights reserved. CPT is a registered trademark of the American Medical Association (AMA). Please review the complete CMS AMA CPT License agreement which is presented to users when accessing the data. For additional information on HCPCS codes, visit the HCPCS general information page.

hcpcs_desc
HCPCS Description
Description of the HCPCS code for the specific medical service furnished by the provider. HCPCS descriptions associated with CPT codes are consumer friendly descriptions provided by the AMA. CPT Consumer Friendly Descriptors are lay synonyms for CPT descriptors that are intended to help healthcare consumers who are not medical professionals understand clinical procedures on bills and patient portals. CPT Consumer Friendly Descriptors should not be used for clinical coding or documentation. All other descriptions are CMS Level II descriptions provided in long form. Due to variable length restrictions, the CMS Level II descriptions have been truncated to 256 bytes. As a result, the same HCPCS description can be associated with more than one HCPCS code. For complete CMS Level II descriptions, please visit the HCPCS Release Code Sets page.

hcpcs_drug_ind
HCPCS Drug Indicator
Identifies whether the HCPCS code for the specific service furnished by the provider is a HCPCS listed on the Medicare Part B Drug Average Sales Price (ASP) File. Please visit the ASP drug pricing page for additional information.

place_of_srvc
Place of Service
Identifies whether the place of service submitted on the claims is a facility (value of ‘F’) or non-facility (value of ‘O’). Non-facility is generally an office setting; however other entities are included in non-facility. The following values are entities included in facility and non-facility:

tot_rndrng_prvdrs
Number of Providers
Number of providers within HCPCS code and place of service.

tot_srvcs
Number of Services
Number of services provided; note that the metrics used to count the number provided can vary from service to service.

tot_benes
Number of Medicare Beneficiaries
Number of distinct Medicare beneficiaries receiving the service for each Rndrng_Prvdr_Geo_Desc and HCPCS_Cd, Place_Of_Srvc.

tot_bene_day_srvcs
Number of Distinct Medicare Beneficiary/Per Day Services
Number of distinct Medicare beneficiary/per day services. Since a given beneficiary may receive multiple services of the same type (e.g., single vs. multiple cardiac stents) on a single day, this metric removes double-counting from the line service count to identify whether a unique service occurred.

avg_sbmtd_chrg
Average Submitted Charge Amount
Average of the charges that providers submit for the service.

avg_mdcr_alowd_amt
Average Medicare Allowed Amount
Average of the Medicare allowed amount for the service. Medicare allowed amounts includes the amount Medicare pays, the deductible and coinsurance amounts that the beneficiary is responsible for paying, and any amounts that a third party is responsible for paying.

avg_mdcr_pymt_amt
Average Medicare Payment Amount
Average amount that Medicare paid after deductible and coinsurance amounts have been deducted for the line item service.

avg_mdcr_stdzd_amt
Average Medicare Standardized Payment Amount
Average amount that Medicare paid after beneficiary deductible and coinsurance amounts have been deducted for the line item service and after standardization of the Medicare payment has been applied. Standardization removes geographic differences in payment rates for individual services, such as those that account for local wages or input prices and makes Medicare payments across geographic areas comparable, so that differences reflect variation in factors such as physicians’ practice patterns and beneficiaries’ ability and willingness to obtain care. Additional information on the standardization of Medicare payments can be found in the “Geographic Variation Public Use File: Technical Supplement on Standardization.”

Service Data Dictionary

Variable Description

rndrng_npi
National Provider Identifier
National Provider Identifier (NPI) for the rendering provider on the claim. The provider NPI is the numeric identifier registered in NPPES.

rndrng_prvdr_last_org_name
Last Name/Organization Name of the Provider
When the provider is registered in NPPES as an individual (entity type code=’I’), this is the provider’s last name. When the provider is registered as an organization (entity type code = ‘O’), this is the organization name.

rndrng_prvdr_first_name
First Name of the Provider
When the provider is registered in NPPES as an individual (entity type code=’I’), this is the provider’s first name. When the provider is registered as an organization (entity type code = ‘O’), this will be blank.

rndrng_prvdr_mi
Middle Initial of the Provider
When the provider is registered in NPPES as an individual (entity type code=’I’), this is the provider’s middle initial. When the provider is registered as an organization (entity type code = ‘O’), this will be blank.

rndrng_prvdr_crdntls
Credentials of the Provider
When the provider is registered in NPPES as an individual (entity type code=’I’), these are the provider’s credentials. When the provider is registered as an organization (entity type code = ‘O’), this will be blank.

rndrng_prvdr_gndr
Gender of the Provider
When the provider is registered in NPPES as an individual (entity type code=’I’), this is the provider’s gender. When the provider is registered as an organization (entity type code = ‘O’), this will be blank.

rndrng_prvdr_ent_cd
Entity Type of the Provider
Type of entity reported in NPPES. An entity code of ‘I’ identifies providers registered as individuals and an entity type code of ‘O’ identifies providers registered as organizations.

rndrng_prvdr_st1
Street Address 1 of the Provider
The first line of the provider’s street address, as reported in NPPES.

rndrng_prvdr_st2
Street Address 2 of the Provider
The second line of the provider’s street address, as reported in NPPES.

rndrng_prvdr_city
City of the Provider
The city where the provider is located, as reported in NPPES.

rndrng_prvdr_state_abrvtn
State Abbreviation of the Provider
The state where the provider is located, as reported in NPPES. The fifty U.S. states and the District of Columbia are reported by the state postal abbreviation. The following values are used for all other areas:

rndrng_prvdr_state_fips
State FIPS Code of the Provider
FIPS code for rendering provider's state.

rndrng_prvdr_zip5
Zip Code of the Provider
The provider’s zip code, as reported in NPPES.

rndrng_prvdr_ruca
RUCA Code of the Provider
Rural-Urban Commuting Area Codes (RUCAs), are a Census tract-based classification scheme that utilizes the standard Bureau of Census Urbanized Area and Urban Cluster definitions in combination with work commuting information to characterize all of the nation's Census tracts regarding their rural and urban status and relationships. The Referring Provider ZIP code was cross walked to the United States Department of Agriculture (USDA) 2010 Rural-Urban Commuting Area Codes.

rndrng_prvdr_ruca_desc
RUCA Description
Description of Rural-Urban Commuting Area (RUCA) Code

rndrng_prvdr_cntry
Country Code of the Provider
The country where the provider is located, as reported in NPPES. The country code will be ‘US’ for any state or U.S. possession. For foreign countries (i.e., state values of ‘ZZ’), the provider country values include the following:

rndrng_prvdr_type
Provider Type of the Provider
Derived from the provider specialty code reported on the claim. For providers that reported more than one specialty code on their claims, this is the specialty code associated with the largest number of services.

rndrng_prvdr_mdcr_prtcptg_ind
Medicare Participation Indicator
Identifies whether the provider participates in Medicare and/or accepts assignment of Medicare allowed amounts. The value will be ‘Y’ for any provider that had at least one claim identifying the provider as participating in Medicare or accepting assignment of Medicare allowed amounts within HCPCS code and place of service. A non-participating provider may elect to accept Medicare allowed amounts for some services and not accept Medicare allowed amounts for other services.

hcpcs_cd
HCPCS Code
HCPCS code used to identify the specific medical service furnished by the provider. HCPCS codes include two levels. Level I codes are the Current Procedural Terminology (CPT) codes that are maintained by the American Medical Association and Level II codes are created by CMS to identify products, supplies and services not covered by the CPT codes (such as ambulance services). CPT codes, descriptions and other data only are copyright 2016 American Medical Association. All rights reserved. CPT is a registered trademark of the American Medical Association (AMA). Please review the complete CMS AMA CPT License agreement which is presented to users when accessing the data. For additional information on HCPCS codes, visit the HCPCS general information page.

hcpcs_desc
HCPCS Description
Description of the HCPCS code for the specific medical service furnished by the provider. HCPCS descriptions associated with CPT codes are consumer friendly descriptions provided by the AMA. CPT Consumer Friendly Descriptors are lay synonyms for CPT descriptors that are intended to help healthcare consumers who are not medical professionals understand clinical procedures on bills and patient portals. CPT Consumer Friendly Descriptors should not be used for clinical coding or documentation. All other descriptions are CMS Level II descriptions provided in long form. Due to variable length restrictions, the CMS Level II descriptions have been truncated to 256 bytes. As a result, the same HCPCS description can be associated with more than one HCPCS code. For complete CMS Level II descriptions, please visit the HCPCS Release Code Sets page.

hcpcs_drug_ind
HCPCS Drug Indicator
Identifies whether the HCPCS code for the specific service furnished by the provider is a HCPCS listed on the Medicare Part B Drug Average Sales Price (ASP) File. Please visit the ASP drug pricing page for additional information.

place_of_srvc
Place of Service
Identifies whether the place of service submitted on the claims is a facility (value of ‘F’) or non-facility (value of ‘O’). Non-facility is generally an office setting; however other entities are included in non-facility. The following values are entities included in facility and non-facility:

tot_benes
Number of Medicare Beneficiaries
Number of distinct Medicare beneficiaries receiving the service for each Rndrng_NPI, HCPCS_Cd, and Place_Of_Srvc.

tot_srvcs
Number of Services
Number of services provided; note that the metrics used to count the number provided can vary from service to service.

tot_bene_day_srvcs
Number of Distinct Medicare Beneficiary/Per Day Services
Number of distinct Medicare beneficiary/per day services. Since a given beneficiary may receive multiple services of the same type (e.g., single vs. multiple cardiac stents) on a single day, this metric removes double-counting from the line service count to identify whether a unique service occurred.

avg_sbmtd_chrg
Average Submitted Charge Amount
Average of the charges that the provider submitted for the service.

avg_mdcr_alowd_amt
Average Medicare Allowed Amount
Average of the Medicare allowed amount for the service; this figure is the sum of the amount Medicare pays, the deductible and coinsurance amounts that the beneficiary is responsible for paying, and any amounts that a third party is responsible for paying.

avg_mdcr_pymt_amt
Average Medicare Payment Amount
Average amount that Medicare paid after deductible and coinsurance amounts have been deducted for the line item service. Note: In general, Medicare FFS claims with dates-of-service or dates-of-discharge on or after April 1, 2013, incurred a 2 percent reduction in Medicare payment. This is in response to mandatory across-the-board reductions in Federal spending, also known as sequestration.

avg_mdcr_stdzd_amt
Average Medicare Standardized Payment Amount
Average amount that Medicare paid after beneficiary deductible and coinsurance amounts have been deducted for the line item service and after standardization of the Medicare payment has been applied. Standardization removes geographic differences in payment rates for individual services, such as those that account for local wages or input prices and makes Medicare payments across geographic areas comparable, so that differences reflect variation in factors such as physicians’ practice patterns and beneficiaries’ ability and willingness to obtain care. Note: This variable is available starting with the calendar year 2014 data. Please refer to the “Additional Information” section of this document for more details on the standardization of Medicare payments.



Key Data Sources


The data for the Physician and Other Practitioners Dataset are based upon CMS administrative claims data for Medicare beneficiaries enrolled in the fee-for-service program. The data are available from the CMS Chronic Condition Data Warehouse (CCW), a database with 100% of Medicare enrollment and fee-for-service claims data. Service counts, beneficiary counts, provider charges, Medicare allowed amounts and payments and the place of service indicator are summarized from Part B non-institutional claims processed through Medicare Administrative Contractor (MAC) Jurisdictions (NCH Claim Type Codes ‘71’, ‘72’). Please see the CCW website for additional information.


For all Physician and Other Practitioners Dataset data years, provider demographics (name, credentials, gender, complete address and entity type) are included from the National Plan & Provider Enumeration System (NPPES). CMS developed the NPPES to assign unique identifiers, known as National Provider Identifiers (NPIs), to health care providers. The health care provider’s demographic information is collected at the time of enrollment and updated periodically. The demographics information provided in the Physician and Other Practitioners Dataset was extracted from NPPES at the end of calendar year following the reporting year (e.g. for CY2017 reporting year, the NPPES data was extracted at the end of calendar year 2018). Please visit the NPPES website for additional information.


Population


The Physician and Other Practitioners Dataset includes data for providers that had a valid NPI and submitted Medicare Part B non-institutional claims (excluding DMEPOS) during the reporting period. To protect the privacy of Medicare beneficiaries, any aggregated records which are derived from 10 or fewer beneficiaries are excluded from the Physician and Other Practitioners Dataset.


Data Limitations


Although the Physician and Other Practitioners Dataset has a wealth of payment and utilization information about many Medicare Part B services, the dataset also has a number of limitations that are worth noting.


First, the data in the Physician and Other Practitioners Dataset may not be representative of a physician’s entire practice. The data in the file only have information for Medicare beneficiaries with Part B FFS coverage, but physicians typically treat many other patients who do not have that form of coverage. The Physician and Other Practitioners Dataset does not have any information on patients who are not covered by Medicare, such as those with coverage from other federal programs (like the Federal Employees Health Benefits Program or Tricare), those with private health insurance (such as an individual policy or employer-sponsored coverage), or those who are uninsured. Even within Medicare, the Physician and Other Practitioners Dataset does not include information for patients who are enrolled in any form of Medicare Advantage plan.


The information presented in this file also does not indicate the quality of care provided by individual physicians. The file only contains cost and utilization information, and for the reasons described in the preceding paragraph, the volume of procedures presented may not be fully inclusive of all procedures performed by the provider. Medicare allowed amounts and Medicare payments for a given HCPCS code/place of service can vary based on a number of factors, including modifiers, geography, and other services performed during the same day/visit. For example, modifiers (two-character designators that signal a change in how the HCPCS code for the procedure or service should be applied) may be included on the claim line when the service intensity was increased or decreased, when an additional physician administered services, or when the service provided differs from the procedure definition. In some cases, modifiers impact allowed amounts and payments. In addition, allowed amounts and payments vary geographically because Medicare makes adjustments for most services based on an area’s cost of living. Allowed amounts and payments can also be adjusted when a physician renders multiple services to a beneficiary on the same day, which is referred to as a multiple procedure payment reduction. For standard payment and allowed amount rates by CPT/HCPCS code, please visit the Physician fee schedule.


In general, when a provider administers drugs to a patient, the provider purchases the drug and Medicare pays the provider 106% of the average sales price (ASP) for the drug. Although the ASP list was used in these datasets to define drug services, the drugs listed on the ASP fee schedule are not a complete listing of drugs paid under part B, but the ASP fee schedule represents the majority of drugs that are used in the office. For more information on payments for drugs covered under Part B, please visit ASP Drug Pricing.


Additionally, the data are not risk adjusted and thus do not account for difference in the underlying severity of disease of patient populations treated by providers. However, we have provided average beneficiary risk scores in the “Medicare Physician and Other Practitioners by Provider Dataset” (i.e., one record per NPI) to provide information on the health status of the beneficiaries the providers serve. Also, since the data presented are summarized from actual claims received from providers and no attempts were made to modify any data (i.e., no statistical outliers were removed or truncated), in rare instances the average submitted charge amount may reflect errors included on claims submitted by providers.


As noted earlier, the file does not include data for services that were 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. In addition, some providers bill under both an individual NPI and an organizational NPI. In this case, users cannot determine a provider’s actual total because there is no way to identify the individual’s portion when billed under their organization.


Medicare pays differently when services are provided in a facility setting versus a freestanding physicians’ office (or other non-facility setting). When services are delivered in a facility setting, Medicare makes two payments, one for the physician’s professional fee and one for the facility. For services delivered in a facility (Place_Of_Srvc = ”F”), the data in the Physician and Other Practitioners Dataset generally represents the physician’s professional fee and does not include the facility payment. The exception is services delivered in Ambulatory Surgical Centers (ASCs). In these cases, both the physician’s professional fee and the ASC’s fee are represented in the Physician and Other Practitioners Dataset. ASCs can be identified using the provider type. For services delivered in a non-facility setting, such as a physician’s office (Place_Of_Srvc = ”O”), the Physician and Other Practitioners Dataset represents the complete payment for the service.


If users try to link data from this file to other public datasets, please be aware of the particular Medicare populations included and timeframes used in each file that will be merged. For example, efforts to link the Physician and Other Practitioners Dataset data to Part D prescription drug data would need to account for the fact that some beneficiaries who have FFS Part B coverage (and are thus included in the Physician and Other Practitioners Dataset) do not have Part D drug coverage (and thus not represented in Part D data files). At the same time, some beneficiaries that have Part D coverage (and are thus included in the Part D data) do not have FFS Part B coverage (and thus not included in the Physician and Other Practitioners Dataset). Another example would be linking to data constructed from different or non-aligning time periods, such as publically available data on physician referral patterns, which is based on an 18-month period.


Finally, users should be aware that payments from some CMS demonstration programs are included in the Physician and Other Practitioners Dataset. Since some CMS demonstration programs utilize the Medicare claims submission process, payments for services under these demonstrations are included in the data file and may be grouped under specific demonstration HCPCS codes or aggregated under non-demonstration specific HCPCS codes. Demonstration programs that are paid outside of the Medicare claims submission process are not included in the Physician and Other Practitioners Dataset.


Additional Information

Other Data Sources

CMS also releases the “Medicare Fee-For-Service Public Provider Enrollment Data” that include provider name and address information from the Provider Enrollment and Chain Ownership System (PECOS). These data are updated on a quarterly basis and are available at data.cms.gov.


Medicare Standardized Spending

Users can find more information on Medicare payment standardization by referring to the Geographic Variation Methodology available within the “Risk adjustment and standardization” section of the following web page: Geographic Variation Methodology.


HCCs (Hierarchical Condition Categories)

CMS developed a risk-adjustment model that uses HCCs (hierarchical condition categories) to assign risk scores. Those scores estimate how beneficiaries’ FFS spending will compare to the overall average for the entire Medicare population. The summary on average risk scores of beneficiaries represented in each calendar year of the Medicare Physician & Other Practitioners - by Provider dataset are located in the “Resources’” section of the following web page: Medicare Physician & Other Practitioners - by Provider. Beneficiaries with scores greater than the average risk score are expected to have above-average spending, and vice versa. Risk scores are based on a beneficiary’s age and sex; whether the beneficiary is eligible for Medicaid, first qualified for Medicare on the basis of disability, or lives in an institution (usually a nursing home); and the beneficiary’s diagnoses from the previous year.


The HCC model was designed for risk adjustment on larger populations, such as the enrollees in an MA plan, and generates more accurate results when used to compare groups of beneficiaries rather than individuals. Please visit HCC risk score for more information.