data.cms.gov
Medicare Post-Acute Care Utilization - Skilled Nursing Facility by Geography and Provider
The Medicare Post-Acute Care (PAC) Utilization - Skilled Nursing Facility (SNF) by Geography and Provider dataset contains data summarized at the provider, state, and national levels.
Freshness
- Last posted
- Period covered
- Jan 1, 2024 to Dec 31, 2024
- Update frequency
- Annually
Dates as CMS lists them in its catalog.
Columns 69
| Column | What it means | Type |
|---|---|---|
YearYEAR | The year of data. | string |
Year TypeYEAR_TYPE | Identifies if the data is for calendar year (CY) or fiscal year (FY). | string |
Summary CategorySMRY_CTGRY | Identifies if the data is at the national, state, or provider level. | string |
Service CategorySRVC_CTGRY | Identifies the PAC setting: HH, hospice, SNFs, IRFs, or LTCHs. | string |
Provider IDPRVDR_ID | The 6-digit CCN for the provider. | string |
Provider NamePRVDR_NAME | The provider name, as reported in the Provider of Services file. | string |
Provider CityPRVDR_CITY | The city where the provider is located, as reported in the Provider of Services file. | string |
Provider StateSTATE | The state where the provider is located, as reported in the Provider of Services file. The fifty U.S. states, the District of Columbia, and Puerto Rico are reported by their postal abbreviation. Note for national level, no state is reported. | string |
Provider ZIPPRVDR_ZIP | The provider’s ZIP code, as reported in the Provider of Services file. Note, for state and national levels, ZIP code is not reported. | string |
Distinct BeneficiariesBENE_DSTNCT_CNT | Number of unique Medicare beneficiaries with at least one paid claim in the calendar or fiscal year. | number |
Episode or Stay CountTOT_EPSD_STAY_CNT | For home health, this is the total count of 30-day episodes in the CY. For hospice, SNF, IRF, and LTCH this is the total count of stays provided in the fiscal year. | number |
Days of ServiceTOT_SRVC_DAYS | Total count of covered days delivered by a provider in the calendar or fiscal year. | number |
Total Charge AmountTOT_CHRG_AMT | Total charges submitted by the provider. | number |
Total Allowed AmountTOT_ALOWD_AMT | Total of the Medicare allowed amount; 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. This applies only to the SNF, IRF, and LTCH settings. | number |
Total Medicare Payment AmountTOT_MDCR_PYMT_AMT | Total amount that Medicare paid after deductible and coinsurance amounts have been deducted. | number |
Total Medicare Standard Payment AmountTOT_MDCR_STDZD_PYMT_AMT | Total amount that Medicare paid adjusted for geographic differences in payment rates. | number |
Percent (%) Dual BeneficiariesBENE_DUAL_PCT | Percent of Medicare beneficiaries qualified to receive Medicare and Medicaid benefits, can also be referred to as dual eligibility. Beneficiaries are classified as a dual if in any month in the given calendar year they were receiving full or partial Medicaid benefits | number |
Percent Medicare Beneficiaries in a Rural ZIPBENE_RRL_PCT | Percent of Medicare beneficiaries who receive their Medicare correspondence in a rural area based on having a Core-based Statistical Area (CBSA) designation equal to Non-CBSA. | number |
Beneficiary Average AgeBENE_AVG_AGE | The arithmetic mean age of beneficiaries. Beneficiary age is calculated at the end of the calendar year or at the time of validated death. | number |
Percent (%) of Beneficiaries who are MaleBENE_MALE_PCT | Percent of beneficiaries who are male. | number |
Percent (%) of Beneficiaries who are FemaleBENE_FEML_PCT | Percent of beneficiaries who are female. | number |
Percent (%) of Beneficiaries who are WhiteBENE_RACE_WHT_PCT | Percent of beneficiaries who are non-Hispanic white. | number |
Percent (%) of Beneficiaries who are BlackBENE_RACE_BLACK_PCT | Percent of beneficiaries who are a non-Hispanic black or African American. | number |
Percent (%) of Beneficiaries who are Asian Pacific IslanderBENE_RACE_API_PCT | Percent of beneficiaries are Asian Pacific Islander. | number |
Percent (%) of Beneficiaries who are HispanicBENE_RACE_HSPNC_PCT | Percent of beneficiaries who are Hispanic. | number |
Percent (%) of Beneficiaries who are American Indian or Alaska NativeBENE_RACE_NATIND_PCT | Percent of beneficiaries who are American Indian or Alaska Native. | number |
Percent (%) of Beneficiaries who are Race UnknownBENE_RACE_UNK_PCT | Percent of beneficiaries with an unknown race. | number |
Percent (%) of Beneficiaries who are OtherBENE_RACE_OTHR_PCT | Percent of beneficiaries with are an other race. | number |
Average Risk ScoreBENE_AVG_RISK_SCRE | The arithmetic mean Hierarchical Condition Category (HCC) risk score of beneficiaries. | number |
BENE_CC_BH_ADHD_OTHCD_V1_PCTBENE_CC_BH_ADHD_OTHCD_V1_PCT | number | |
Percent (%) Of Beneficiaries Identified With Alcohol and Drug Use DisordersBENE_CC_BH_ALCOHOL_DRUG_V1_PCT | Percent of beneficiaries meeting the CCW chronic condition algorithms for both alcohol use disorder and/or drug use disorder. Please note that this condition was not updated as part of the 2020 technical expert panel (TEP) to refine and enhance chronic conditions algorithms, hence the V1 component of the variable name. Chronic condition metrics are only available for file years 2017 forward. For more details on this condition, see https://www2.ccwdata.org/web/guest/condition-categories-other. | number |
Percent (%) Of Beneficiaries Identified With Alzheimer's Disease And Non-Alzheimer's DementiaBENE_CC_BH_ALZ_NONALZDEM_V2_PCT | Percent of beneficiaries meeting the CCW chronic condition algorithms for both Alzheimer's disease and/or non-Alzheimer's dementia. In 2020, CMS contracted an technical expert panel (TEP) to refine and enhance the chronic condition algorithms, including the algorithms for Alzheimer's disease and non-Alzheimer's dementia. The V2 portion of the variable name indicates that this variable was updated as part of the TEP. Chronic condition metrics are only available for file years 2017 forward. For more details on this condition, see https://www2.ccwdata.org/web/guest/condition-categories-chronic. | number |
Percent (%) Of Beneficiaries Identified With Anxiety DisordersBENE_CC_BH_ANXIETY_V1_PCT | Percent of beneficiaries meeting the CCW chronic condition algorithm for anxiety disorders. Please note that this condition was not updated as part of the 2020 technical expert panel (TEP) to refine and enhance chronic conditions algorithms, hence the V1 component of the variable name. Chronic condition metrics are only available for file years 2017 forward. For more details on this condition, see https://www2.ccwdata.org/web/guest/condition-categories-other. | number |
BENE_CC_BH_BIPOLAR_V1_PCTBENE_CC_BH_BIPOLAR_V1_PCT | number | |
Percent (%) Of Beneficiaries Identified With Major Depressive Affective DisorderBENE_CC_BH_DEPRESS_V1_PCT | Percent of beneficiaries meeting the CCW chronic condition algorithm for bipolar disorders. Please note that this condition was not updated as part of the 2020 technical expert panel (TEP) to refine and enhance chronic conditions algorithms, hence the V1 component of the variable name. Chronic condition metrics are only available for file years 2017 forward. For more details on this condition, see https://www2.ccwdata.org/web/guest/condition-categories-other. | number |
Percent (%) Of Beneficiaries Identified With Depression, Bipolar Or Other Depressive Mood DisordersBENE_CC_BH_MOOD_V2_PCT | Percent of beneficiaries meeting the CCW chronic condition algorithm for depression and other depressive mood disorders. In 2020, CMS contracted an technical expert panel (TEP) to refine and enhance the chronic condition algorithms, including the algorithm for depressive and other depressive mood disorders. The V2 portion of the variable name indicates that this variable was updated as part of the TEP. Chronic condition metrics are only available for file years 2017 forward. For more details on this condition, see https://www2.ccwdata.org/web/guest/condition-categories-chronic. | number |
Percent (%) Of Beneficiaries Identified With Personality DisordersBENE_CC_BH_PD_V1_PCT | Percent of beneficiaries meeting the CCW chronic condition algorithm for personality disorders. Please note that this condition was not updated as part of the 2020 technical expert panel (TEP) to refine and enhance chronic conditions algorithms, hence the V1 component of the variable name. Chronic condition metrics are only available for file years 2017 forward. For more details on this condition, see https://www2.ccwdata.org/web/guest/condition-categories-other. | number |
BENE_CC_BH_PTSD_V1_PCTBENE_CC_BH_PTSD_V1_PCT | number | |
BENE_CC_BH_SCHIZO_OTHPSY_V1_PCTBENE_CC_BH_SCHIZO_OTHPSY_V1_PCT | number | |
Percent (%) Of Beneficiaries Identified With Tobacco Use DisordersBENE_CC_BH_TOBACCO_V1_PCT | Percent of beneficiaries meeting the CCW chronic condition algorithm for tobacco use disorders. Please note that this condition was not updated as part of the 2020 technical expert panel (TEP) to refine and enhance chronic conditions algorithms, hence the V1 component of the variable name. Chronic condition metrics are only available for file years 2017 forward. For more details on this condition, see https://www2.ccwdata.org/web/guest/condition-categories-other. | number |
Percent (%) Of Beneficiaries Identified With Atrial Fibrillation And FlutterBENE_CC_PH_AFIB_V2_PCT | Percent of beneficiaries meeting the CCW chronic condition algorithm for atrial fibrillation/flutter. In 2020, CMS contracted an technical expert panel (TEP) to refine and enhance the chronic condition algorithms, including the algorithm for atrial fibrillation/flutter. The V2 portion of the variable name indicates that this variable was updated as part of the TEP. For more details on this condition, see https://www2.ccwdata.org/web/guest/condition-categories-chronic. | number |
Percent (%) Of Beneficiaries Identified With Rheumatoid Arthritis / OsteoarthritisBENE_CC_PH_ARTHRITIS_V2_PCT | Percent of beneficiaries meeting the CCW chronic condition algorithm for rheumatoid arthritis/osteoarthritis. In 2020, CMS contracted an technical expert panel (TEP) to refine and enhance the chronic condition algorithms, including the algorithm for rheumatoid arthritis/osteoarthritis. The V2 portion of the variable name indicates that this variable was updated as part of the TEP. Chronic condition metrics are only available for file years 2017 forward. For more details on this condition, see https://www2.ccwdata.org/web/guest/condition-categories-chronic. | number |
BENE_CC_PH_ASTHMA_V2_PCTBENE_CC_PH_ASTHMA_V2_PCT | number | |
Percent (%) Of Beneficiaries Identified With Combined Cancer Flag For 6 Cancer IndicatorsBENE_CC_PH_CANCER6_V2_PCT | Percent of beneficiaries meeting the CCW chronic condition algorithms for six cancer types; includes breast cancer, colorectal cancer, endometrial cancer, lung cancer, prostate cancer and urological cancer. In 2020, CMS contracted an technical expert panel (TEP) to refine and enhance the chronic condition algorithms. The V2 portion of the variable name indicates that this variable was updated as part of the TEP. Chronic condition metrics are only available for file years 2017 forward. For more details on this condition, see https://www2.ccwdata.org/web/guest/condition-categories-chronic. | number |
Percent (%) Of Beneficiaries Identified With Chronic Kidney DiseaseBENE_CC_PH_CKD_V2_PCT | Percent of beneficiaries meeting the CCW chronic condition algorithms for chronic kidney disease. In 2020, CMS contracted an technical expert panel (TEP) to refine and enhance the chronic condition algorithms, including the algorithm for chronic kidney disease. The V2 portion of the variable name indicates that this variable was updated as part of the TEP. Chronic condition metrics are only available for file years 2017 forward. For more details on this condition, see https://www2.ccwdata.org/web/guest/condition-categories-chronic. | number |
Percent (%) Of Beneficiaries Identified With Chronic Obstructive Pulmonary DiseaseBENE_CC_PH_COPD_V2_PCT | Percent of beneficiaries meeting the CCW chronic condition algorithm for COPD. In 2020, CMS contracted an technical expert panel (TEP) to refine and enhance the chronic condition algorithms, including the algorithm for COPD. The V2 portion of the variable name indicates that this variable was updated as part of the TEP. Chronic condition metrics are only available for file years 2017 forward. For more details on this condition, see https://www2.ccwdata.org/web/guest/condition-categories-chronic. | number |
Percent (%) Of Beneficiaries Identified With DiabetesBENE_CC_PH_DIABETES_V2_PCT | Percent of beneficiaries meeting the CCW chronic condition algorithm for diabetes. In 2020, CMS contracted an technical expert panel (TEP) to refine and enhance the chronic condition algorithms, including the algorithm for diabetes. The V2 portion of the variable name indicates that this variable was updated as part of the TEP. Chronic condition metrics are only available for file years 2017 forward. For more details on this condition, see https://www2.ccwdata.org/web/guest/condition-categories-chronic. | number |
Percent (%) Of Beneficiaries Identified With Heart Failure And Non-Ischemic Heart DiseaseBENE_CC_PH_HF_NONIHD_V2_PCT | Percent of beneficiaries meeting the CCW chronic condition algorithm for heart failure/non-ischemic heart disease. In 2020, CMS contracted an technical expert panel (TEP) to refine and enhance the chronic condition algorithms, including the algorithm for heart failure/non-ischemic heart disease. The V2 portion of the variable name indicates that this variable was updated as part of the TEP. Chronic condition metrics are only available for file years 2017 forward. For more details on this condition, see https://www2.ccwdata.org/web/guest/condition-categories-chronic. | number |
Percent (%) Of Beneficiaries Identified With HyperlipidemiaBENE_CC_PH_HYPERLIPIDEMIA_V2_PCT | Percent of beneficiaries meeting the CCW chronic condition algorithm for hyperlipidemia. In 2020, CMS contracted an technical expert panel (TEP) to refine and enhance the chronic condition algorithms, including the algorithm for hyperlipidemia. The V2 portion of the variable name indicates that this variable was updated as part of the TEP. Chronic condition metrics are only available for file years 2017 forward. For more details on this condition, see https://www2.ccwdata.org/web/guest/condition-categories-chronic. | number |
Percent (%) Of Beneficiaries Identified With HypertensionBENE_CC_PH_HYPERTENSION_V2_PCT | Percent of beneficiaries meeting the CCW chronic condition algorithm for hypertension. In 2020, CMS contracted an technical expert panel (TEP) to refine and enhance the chronic condition algorithms, including the algorithm for hypertension. The V2 portion of the variable name indicates that this variable was updated as part of the TEP. Chronic condition metrics are only available for file years 2017 forward. For more details on this condition, see https://www2.ccwdata.org/web/guest/condition-categories-chronic. | number |
Percent (%) Of Beneficiaries Identified With Ischemic Heart DiseaseBENE_CC_PH_ISCHEMICHEART_V2_PCT | Percent of beneficiaries meeting the CCW chronic condition algorithm for ischemic heart disease. In 2020, CMS contracted an technical expert panel (TEP) to refine and enhance the chronic condition algorithms, including the algorithm for ischemic heart disease. The V2 portion of the variable name indicates that this variable was updated as part of the TEP. Chronic condition metrics are only available for file years 2017 forward. For more details on this condition, see https://www2.ccwdata.org/web/guest/condition-categories-chronic. | number |
Percent (%) Of Beneficiaries Identified With Osteoporosis With Or Without Pathological FractureBENE_CC_PH_OSTEOPOROSIS_V2_PCT | Percent of beneficiaries meeting the CCW chronic condition algorithm for osteoporosis. In 2020, CMS contracted an technical expert panel (TEP) to refine and enhance the chronic condition algorithms, including the algorithm for osteoporosis. The V2 portion of the variable name indicates that this variable was updated as part of the TEP. Chronic condition metrics are only available for file years 2017 forward. For more details on this condition, see https://www2.ccwdata.org/web/guest/condition-categories-chronic. | number |
Percent (%) Of Beneficiaries Identified With Parkinson's Disease And Secondary Parkinsonism ToBENE_CC_PH_PARKINSON_V2_PCT | Percent of beneficiaries meeting the CCW chronic condition algorithm for Parkinson's disease/secondary parkinsonism. In 2020, CMS contracted an technical expert panel (TEP) to refine and enhance the chronic condition algorithms, including the algorithm for Parkinson's disease/secondary parkinsonism. The V2 portion of the variable name indicates that this variable was updated as part of the TEP. Chronic condition metrics are only available for file years 2017 forward. For more details on this condition, see https://www2.ccwdata.org/web/guest/condition-categories-chronic. | number |
Percent (%) Of Beneficiaries Identified With Stroke / Transient Ischemic AttackBENE_CC_PH_STROKE_TIA_V2_PCT | Percent of beneficiaries meeting the CCW chronic condition algorithm for stroke/transient ischemic attack. In 2020, CMS contracted an technical expert panel (TEP) to refine and enhance the chronic condition algorithms, including the algorithm for stroke/transient ischemic attack. The V2 portion of the variable name indicates that this variable was updated as part of the TEP. Chronic condition metrics are only available for file years 2017 forward. For more details on this condition, see https://www2.ccwdata.org/web/guest/condition-categories-chronic. | number |
Percent (%) of Episodes with a Primary Diagnosis of Infectious and Parasitic DiseasesPRMRY_DX_INFCTN_PCT | Percent of episodes with a primary diagnosis of Infections or Parasitic Disease. This includes diagnoses within an ICD-10 code range of A00-B99 or an ICD-9 code range of 001-039. | number |
Percent (%) of Episodes with a Primary Diagnosis of Neoplasms & Diseases of the Blood and Blood forming organsPRMRY_DX_NEOBLD_PCT | Percent of Episodes with a primary diagnosis of Neoplasms & Diseases of the Blood and Blood forming organs or certain disorders involving the immune mechanism. This includes diagnoses within an ICD-10 code range of C00-D89 (ICD-10) or an ICD-9 code range of 140-239, 280-289. | number |
Percent (%) of Episodes with a Primary Diagnosis of Endocrine, Nutritional and Metabolic DiseasesPRMRY_DX_ENDONUTRMET_PCT | Percent of episodes with a primary diagnosis of Endocrine, Nutritional or Metabolic diseases. This includes diagnoses within an ICD-10 code range of E00-E89 (ICD-10) or an ICD-9 code range of 240-279. | number |
Percent (%) of Episodes with a Primary Diagnosis of Mental, Behavioral and Neurodevelopmental disordersPRMRY_DX_MNTBEHNEUDIS_PCT | Percent of episodes with a primary diagnosis of Mental, Behavioral, or Neurodevelopmental Disorders. This includes diagnoses within an ICD-10 code range of F01-F99 or ICD-9 code range of 290-319. | number |
Percent (%) of Episodes with a Primary Diagnosis of Diseases of the Nervous SystemPRMRY_DX_NERVSYSTM_PCT | Percent of episodes with a primary diagnosis of Diseases of the Nervous System. This includes diagnoses within an ICD-10 code range of G00-G99 or ICD-9 code range of 320-389. | number |
Percent (%) of Episodes with a Primary Diagnosis of Diseases of the Eye and Adnexa & Disease of the Ear and Mastoid processPRMRY_DX_ENTSYS_PCT | Percent of Episodes with a primary diagnosis of Diseases of the Eye and Adnexa & Disease of the Ear and Mastoid process. This includes diagnoses within an ICD-10 code range of H00-H95 or an ICD-9 range of 360-379. | number |
Percent (%) of Episodes with a Primary Diagnosis of Diseases of the Circulatory SystemPRMRY_DX_CIRCSYSTM_PCT | Percent of Episodes with a primary diagnosis of Diseases of the Circulatory System. This includes diagnoses within an ICD-10 code range of I00-I99 or an ICD-9 code range of 390-459. | number |
Percent (%) of Episodes with a Primary Diagnosis of Diseases of the Respiratory SystemPRMRY_DX_RSPSYSTM_PCT | Percent of episodes with a primary diagnosis of Diseases of the Respiratory System. This includes diagnoses within an ICD-10 code range of J00-J99 or an ICD-9 code range of 460-519. | number |
Percent (%) of Episodes with a Primary Diagnosis of Diseases of the Digestive SystemPRMRY_DX_DIGSYSTM_PCT | Percent of episodes with a primary diagnosis of Diseases of the Digestive System. This includes diagnoses within an ICD-10 code range of K00-K95 or an ICD-9 code range of 520-579. | number |
Percent (%) of Episodes with a Primary Diagnosis of Diseases of the Skin and Subcutaneous Tissue & Diseases of the Musculoskeletal System and Connective TissuePRMRY_DX_SKNMUSSYSTM_PCT | Percent of Episodes with a primary diagnosis of Diseases of the Skin and Subcutaneous Tissue & Diseases of the Musculoskeletal System and Connective Tissue This includes diagnoses within an ICD-10 code range of L00-M99 or an ICD-9 code range of 680-709, 710-739. | number |
Percent (%) of Episodes with a Primary Diagnosis of Diseases of the Genitourinary SystemPRMRY_DX_GUSYSTM_PCT | Percent of episodes with a primary diagnosis of Diseases of the Genitourinary System. This includes diagnoses within an ICD-10 code range of N00-N99 or an ICD-9 code range of 580-629. | number |
Percent (%) of Episodes with a Primary Diagnosis of Pregnancy, Childbirth and the Puerperium, certain conditions originating in the perinatal Period, & Congenital Malformations, Deformations and Chromosomal AbnormalitiesPRMRY_DX_PRGPERICONG_PCT | Percent of Episodes with a primary diagnosis of Pregnancy, Childbirth and the Puerperium, certain conditions originating in the perinatal Period, & Congenital Malformations, Deformations and Chromosomal Abnormalities This includes diagnoses within an ICD-10 code range of O00-Q99 or an ICD-9 code range of 630-679, 740-759, or 760-779. | number |
Percent (%) of Episodes with a Primary Diagnosis of Symptoms, Signs, and Ill-defined ConditionsPRMRY_DX_SXILLDEF_PCT | Percent of episodes with a primary diagnosis of Symptoms, Signs and Abnormal Clinical and Laboratory findings, not elsewhere classified. This includes diagnoses within an ICD-10 code range of R00-R99 or an ICD-9 code range of 780-799. | number |
Percent (%) of Episodes with a Primary Diagnosis of Injury, Poisoning and certain other consequences of external causes & external causes of MorbidityPRMRY_DX_INJPOIS_PCT | Percent of episodes with a primary diagnosis of Injury, Poisoning and certain other consequences of external causes & external causes of Morbidity. This includes diagnoses within an ICD-10 code range of S00-T88 or V00-Y99 or an ICD-9 code range of 800-999. | number |
Percent (%) of Episodes with a Primary Diagnosis of Factors influencing health status and contact with health services & codes for special purposesPRMRY_DX_HLTHSRV_PCT | Percent of episodes with a primary diagnosis of Factors influencing health status and contact with health services & codes for special purposes. This includes diagnoses within an ICD-10 code range of Z00-Z99 or U00-U85 or an ICD-9 code range of E000-E999. | number |
No column matches that filter.
At a glance
- Catalog
- data.cms.gov
- Publisher
- Office of Enterprise Data and Analytics (OEDA)
- Rows
- 13,837
- Columns
- 69
- State column
STATE
API
Free, no key needed. This request returns the first 10 rows as JSON:
https://data.cms.gov/data-api/v1/dataset/eaed338b-847e-41b1-a4d3-a206f40dc72b/data?size=10
To keep only one state, filter on the STATE column.
Versions 11
The newest version is the one linked above. Older releases stay on the official site.
- 2024-01-01posted Aug 11, 2026
- 2023-01-02posted Jul 10, 2026
- 2022-01-01posted Jul 10, 2026
- 2021-01-01posted Jul 10, 2026
- 2020-01-01posted Jul 10, 2026
- 2019-01-01posted Jul 10, 2026
- 2018-01-01posted Jul 10, 2026
- 2017-01-01posted Jul 10, 2026
Show 3 older versions
- 2016-01-01posted Jul 10, 2026
- 2015-01-01posted Jul 10, 2026
- 2014-01-01posted Jul 10, 2026
CMS's description
The Medicare Post-Acute Care (PAC) Utilization - Skilled Nursing Facility (SNF) by Geography and Provider dataset contains data summarized at the provider, state, and national levels. Payment information includes provider charges, Medicare allowed amount (if applicable), Medicare payment, and the standardized payment for care provided in the SNF setting.
Methodology and other documents from CMS:
The summary at the top is the first sentence of this description. Record id cms:eaed338b-847e-41b1-a4d3-a206f40dc72b. This record as JSON.