The table MEDPAR is part of the dataset Medicare 20% [2019-2020] MedPAR, available at https://stanford.redivis.com/datasets/0n7e-e4ebjt3mm. It contains 6987323 rows across 426 variables.

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Documentation

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Section 2

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The Medicare Provider Analysis and Review (MEDPAR) File contains data from claims for services provided to beneficiaries admitted to Medicare certified inpatient hospitals and skilled nursing facilities (SNF). The accumulation of claims from a beneficiarys date of admission to an inpatient hospital, where the beneficiary has been discharged, or to a skilled nursing facility, where the beneficiary may still be a patient, represents one stay. A stay record may represent one claim or multiple claims.

This dataset was taken from the United States Food and Drugs Association (US FDA).The datset is a list of Hospitals with Fewer than 1,600 Medicare Discharges Based on the December 2017 Update of the FY 2016 MedPAR File and Potentially Eligible Hospitals’ FY 2018 Low-Volume Hospital Payment Adjustment. Eligibility for the low-volume hospital payment adjustment is also dependent upon meeting the mileage criteria specified at 412.101(b)(2)(ii) of the regulations.

This brief presentation outlines the educational objectives for the Introduction to Medicare workshop. Objectives of the workshop which are found in the various video segments include -understanding the basic structure and content of the Medicare program -learning which Medicare data files are available for research purposes -knowing the source of the Medicare administrative data sets -reviewing the Master Beneficiary Summary File (a.k.a. Denominator), MedPAR file, and the Carrier file for use by researchers

Here, you will find resources to use the Bynum-Standard 1-Year Algorithm including a README file that accompanies SAS and Stata scripts for the 1-Year Standard Method for identifying Alzheimer’s Disease and Related Dementias (ADRD) in Medicare Claims data. There are seven script files (plus a parameters file for SAS [parm.sas]) for both SAS and Stata. The files are numbered in the order in which they should be run; the five “1” files may be run in any order.The full algorithm requires access to a single year of Medicare Claims data for (1) MedPAR, (2) Home Health Agency (HHA) Claims File, (3) Hospice Claims File, (4) Carrier Claims and Line Files, and (5) Hospital Outpatient File (HOF) Claims and Revenue Files. All Medicare Claims files are expected to be in SAS format (.sas7bdat).For each data source, the script will output three files*:Diagnosis-level file: Lists individual ADRD diagnoses for each beneficiary for a given visit. This file allows researchers to identify which ICD-9-CM or ICD-10-CM codes are used in the claims data.Service Date-level file: Aggregated from the Diagnosis-level file, this file includes all beneficiaries with an ADRD diagnosis by Service Date (date of a claim with at least one ADRD diagnosis).Beneficiary-level file: Aggregated from the Service Date-level file, this file includes all beneficiaries with at least one* ADRD diagnosis at any point in the year within a specific file* The algorithm combines the Carrier and HOF files at the Service Date-level. The final combined Carrier and HOF Beneficiary-level file includes those with at least two (2) claims that are seven (7) or more days apart.​A final combined file is created by merging all Beneficiary-level files. This file is used to identify beneficiaries with ADRD and can be merged onto other files by the Beneficiary ID (BENE_ID).With appreciation & acknowledgement to colleagues from a grant funded by the NIA for their involvement in development & validation of the Bynum-Standard 1-Year Algorithm

2019 - 2021, county-level U.S. heart disease hospitalization rates. Dataset developed by the Centers for Disease Control and Prevention, Division for Heart Disease and Stroke Prevention.Create maps of U.S. heart disease hospitalization rates among Medicare fee-for-service beneficiaries aged 65 and older, by county. Data can be stratified by race/ethnicity and sex.Visit the CDC Atlas of Heart Disease and Stroke for additional data and maps. Atlas of Heart Disease and StrokeData SourceHospitalization data were obtained from the Centers for Medicare and Medicaid Services Medicare Provider Analysis and Review (MEDPAR) file, Part A and the Master Beneficiary Summary File (MBSF). International Classification of Diseases, 10th Revision, Clinical Modification (ICD-10-CM) codes: I00-I09, I11, I13, I20-I51; principle (i.e., first-listed) diagnosis. Medicare fee-for-service beneficiaries 65 and older were included. Visit the Atlas of Heart Disease and Stroke Statistical Methods pages for more detailed Medicare data inclusion criteriaData DictionaryData for counties with small populations are not displayed when a reliable rate could not be generated. These counties are represented in the data with values of '-1.' CDC excludes these values when classifying the data on a map, indicating those counties as 'Insufficient Data.'Data field names and descriptionsstcty_fips: state FIPS code + county FIPS codeOther fields use the following format: RRR_S_aaaa (e.g., API_M_35UP)  RRR: 3 digits represent race/ethnicity    All - Overall   BLK - Black, non-Hispanic    HIS - Hispanic    WHT - White, non-Hispanic  S: 1 digit represents sex    A - All    F - Female    M - Male  aaaa: 4 digits represent age. The first 2 digits are the lower bound for age and the last 2 digits are the upper bound for age. 'UP' indicates the data includes the maximum age available and 'LT' indicates ages less than the upper bound. Example: The column 'BLK_M_65UP' displays rates per 1,000 black Medicare beneficiaries aged 65 years and older.MethodologyRates are calculated using a 3-year average and are age-standardized in 10-year age groups using the 2000 U.S. Standard Population. Rates are calculated and displayed per 1,000 Medicare beneficiaries. Rates were spatially smoothed using a Local Empirical Bayes algorithm to stabilize risk by borrowing information from neighboring geographic areas, making estimates more statistically robust and stable for counties with small populations. Data for counties with small populations are coded as '-1' when a reliable rate could not be generated. County-level rates were generated when the following criteria were met over a 3-year time period within each of the filters (e.g., age, race, and sex).At least one of the following 3 criteria:At least 20 events occurred within the county and its adjacent neighbors.ORAt least 16 events occurred within the county.ORAt least 5,000 population years within the county.AND all 3 of the following criteria:At least 6 population years for each age group used for age adjustment if that age group had 1 or more event.The number of population years in an age group was greater than the number of events.At least 100 population years within the county.More Questions?Interactive Atlas of Heart Disease and StrokeData SourcesStatistical Methods

Create maps of U.S. stroke hospitalization rates among Medicare fee-for-service beneficiaries aged 65 and older, by county. Data can be stratified by race/ethnicity and gender. Visit the CDC/DHDSP Atlas of Heart Disease and Stroke for additional data and maps. Atlas of Heart Disease and StrokeData SourceHospitalization data were obtained from the Centers for Medicare and Medicaid Services Medicare Provider Analysis and Review (MEDPAR) file, Part A and the Master Beneficiary Summary File (MBSF). International Classification of Diseases, 9th Revision, Clinical Modification (ICD-9-CM) codes: 430-434, 436-438; principle (i.e., first-listed) diagnosis. Medicare fee-for-service beneficiaries 65 and older were included. Visit the Atlas of Heart Disease and Stroke Statistical Methods pages for more detailed Medicare data inclusion criteria.Data DictionaryData for counties with small populations are not displayed when a reliable rate could not be generated. These counties are represented in the data with values of '-1.' CDC/DHDSP excludes these values when classifying the data on a map, indicating those counties as 'Insufficient Data.' Data field names and descriptionsstcty_fips: state FIPS code + county FIPS codeOther fields use the following format: RRR_S_aaaa (e.g., BLK_M_65UP) RRR: 3 digits represent race/ethnicity All - Overall BLK - Black, non-Hispanic HIS - Hispanic WHT - White, non-Hispanic S: 1 digit represents sex/gender A - All F - Female M - Male������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������aaaa: 4 digits represent age. The first 2 digits are the lower bound for age and the last 2 digits are the upper bound for age. 'UP' indicates the data includes the maximum age available and 'LT' indicates ages less than the upper bound. Example: The column 'BLK_M_65UP' displays rates per 1,000 black Medicare beneficiaries aged 65 years and older.MethodologyRates are calculated using a 3-year average and are age-standardized in 10-year age groups using the 2000 U.S. Standard Population. Rates are calculated and displayed per 1,000 Medicare beneficiaries. Rates were spatially smoothed using a Local Empirical Bayes algorithm to stabilize risk by borrowing information from neighboring geographic areas, making estimates more statistically robust and stable for counties with small populations. Data for counties with small populations are coded as '-1' when a reliable rate could not be generated. County-level rates were generated when the following criteria were met over a 3-year time period within each of the filters (e.g., age, race, and gender).At least one of the following 3 criteria: At least 20 events occurred within the county and its adjacent neighbors.ORAt least 16 events occurred within the county.ORAt least 5,000 population years within the county.AND all 3 of the following criteria:At least 6 population years for each age group used for age adjustment if that age group had 1 or more event.The number of population years in an age group was greater than the number of events.At least 100 population years within the county.More Questions?Interactive Atlas of Heart Disease and StrokeData SourcesStatistical Methods

Create maps of U.S. heart disease hospitalization rates among Medicare fee-for-service beneficiaries aged 65 and older, by county. Data can be stratified by race/ethnicity and sex. Visit the CDC/DHDSP Atlas of Heart Disease and Stroke for additional data and maps. Atlas of Heart Disease and StrokeData SourceHospitalization data were obtained from the Centers for Medicare and Medicaid Services Medicare Provider Analysis and Review (MEDPAR) file, Part A and the Master Beneficiary Summary File (MBSF). International Classification of Diseases, 9th Revision, Clinical Modification (ICD-9-CM) codes: 390-398, 402, 404, 410-429; principle (i.e., first-listed) diagnosis. Medicare fee-for-service beneficiaries 65 and older were included. Visit the Atlas of Heart Disease and Stroke Statistical Methods pages for more detailed Medicare data inclusion criteria.Data DictionaryData for counties with small populations are not displayed when a reliable rate could not be generated. These counties are represented in the data with values of '-1.' CDC/DHDSP excludes these values when classifying the data on a map, indicating those counties as 'Insufficient Data.' Data field names and descriptionsstcty_fips: state FIPS code + county FIPS codeOther fields use the following format: RRR_S_aaaa (e.g., API_M_35UP)   RRR: 3 digits represent race/ethnicity     All - Overall   BLK - Black, non-Hispanic     HIS - Hispanic     WHT - White, non-Hispanic   S: 1 digit represents sex     A - All    F - Female     M - Male  aaaa: 4 digits represent age. The first 2 digits are the lower bound for age and the last 2 digits are the upper bound for age. 'UP' indicates the data includes the maximum age available and 'LT' indicates ages less than the upper bound.  Example: The column 'BLK_M_65UP' displays rates per 1,000 black Medicare beneficiaries aged 65 years and older.MethodologyRates are calculated using a 3-year average and are age-standardized in 10-year age groups using the 2000 U.S. Standard Population. Rates are calculated and displayed per 1,000 Medicare beneficiaries. Rates were spatially smoothed using a Local Empirical Bayes algorithm to stabilize risk by borrowing information from neighboring geographic areas, making estimates more statistically robust and stable for counties with small populations. Data for counties with small populations are coded as '-1' when a reliable rate could not be generated. County-level rates were generated when the following criteria were met over a 3-year time period within each of the filters (e.g., age, race, and sex).At least one of the following 3 criteria: At least 20 events occurred within the county and its adjacent neighbors.ORAt least 16 events occurred within the county.ORAt least 5,000 population years within the county.AND all 3 of the following criteria:At least 6 population years for each age group used for age adjustment if that age group had 1 or more event.The number of population years in an age group was greater than the number of events.At least 100 population years within the county.More Questions?Interactive Atlas of Heart Disease and StrokeData SourcesStatistical Methods

ARIC = Atherosclerosis Risk in Communities.CMS = Centers for Medicare and Medicaid Services.*All CMS includes MedPAR and outpatient claims.Inpatient CMS includes MedPAR claims.Outpatient CMS includes outpatient and carrier claims.% agreement calculated as the number of participants with consistent classification of diagnosed AF from active ARIC cohort follow-up and surveillance of CMS divided by the total number of observations and converted to a percent.% positive agreement calculated as the number of participants classified as having AF based on both active ARIC cohort follow-up and surveillance of CMS, conditional on being classified as having AF from at least one source, and converted to a percent.% negative agreement calculated as the number of participants classified as not having AF based on both active ARIC cohort follow-up and surveillance of CMS, conditional on being classified as not having AF from at least one source, and converted to a percent.Data are limited to participants enrolled in Medicare fee-for-service.

Values are median [interquartile range], frequency (percent) or mean ± standard deviation.MedPAR = Medicare Provider Analysis and Review File.*The total number of 2005 admissions in MedPAR independent of eligibility for this study.Long-term acute care hospital characteristics by type.

The final dataset combines cardiopulmonary hospitalization data for those 65 and over using the Medicare Provider Analysis and Review (MEDPAR) files from the Center for Medicare and Medicaid Services (CMS), modeled fine particulate matter (PM2.5) concentrations from the Community Multiscale Air Quality (CMAQ) model, and monitoring site concentrations of PM2.5 from the Air Quality System (AQS). All data are aggregated to the county level and restricted to counties with wildfires recorded between 2008-2010. This dataset is not publicly accessible because: EPA cannot release personally identifiable information regarding living individuals, according to the Privacy Act and the Freedom of Information Act (FOIA). This dataset contains information about human research subjects. Because there is potential to identify individual participants and disclose personal information, either alone or in combination with other datasets, individual level data are not appropriate to post for public access. Restricted access may be granted to authorized persons by contacting the party listed. It can be accessed through the following means: Due to the presence of PII, limited data are available on request. Format: The data are stored as an R dataset (.RData) on a restricted drive. This dataset is associated with the following publication: Deflorio-Barker, S., J. Crooks, J. Reyes, and A.G. Rappold. Cardiopulmonary effects of fine particulate matter exposure among older adults, during wildfire and non-wildfire periods, in U.S. 2008-2010. ENVIRONMENTAL HEALTH PERSPECTIVES. National Institute of Environmental Health Sciences (NIEHS), Research Triangle Park, NC, USA, 127(3): 37006, (2019).

Create maps of U.S. heart disease hospitalization rates among Medicare fee-for-service beneficiaries aged 65 and older, by county. Data can be stratified by race/ethnicity and sex. Visit the CDC/DHDSP Atlas of Heart Disease and Stroke for additional data and maps. Atlas of Heart Disease and StrokeData SourceHospitalization data were obtained from the Centers for Medicare and Medicaid Services Medicare Provider Analysis and Review (MEDPAR) file, Part A and the Master Beneficiary Summary File (MBSF). International Classification of Diseases, 9th Revision, Clinical Modification (ICD-9-CM) codes: 390-398, 402, 404, 410-429; principle (i.e., first-listed) diagnosis. Medicare fee-for-service beneficiaries 65 and older were included. Visit the Atlas of Heart Disease and Stroke Statistical Methods pages for more detailed Medicare data inclusion criteria.Data DictionaryData for counties with small populations are not displayed when a reliable rate could not be generated. These counties are represented in the data with values of '-1.' CDC/DHDSP excludes these values when classifying the data on a map, indicating those counties as 'Insufficient Data.' Data field names and descriptionsstcty_fips: state FIPS code + county FIPS codeOther fields use the following format: RRR_S_aaaa (e.g., API_M_35UP)   RRR: 3 digits represent race/ethnicity     All - Overall   BLK - Black, non-Hispanic     HIS - Hispanic     WHT - White, non-Hispanic   S: 1 digit represents sex     A - All    F - Female     M - Male  aaaa: 4 digits represent age. The first 2 digits are the lower bound for age and the last 2 digits are the upper bound for age. 'UP' indicates the data includes the maximum age available and 'LT' indicates ages less than the upper bound.  Example: The column 'BLK_M_65UP' displays rates per 1,000 black Medicare beneficiaries aged 65 years and older.MethodologyRates are calculated using a 3-year average and are age-standardized in 10-year age groups using the 2000 U.S. Standard Population. Rates are calculated and displayed per 1,000 Medicare beneficiaries. Rates were spatially smoothed using a Local Empirical Bayes algorithm to stabilize risk by borrowing information from neighboring geographic areas, making estimates more statistically robust and stable for counties with small populations. Data for counties with small populations are coded as '-1' when a reliable rate could not be generated. County-level rates were generated when the following criteria were met over a 3-year time period within each of the filters (e.g., age, race, and sex).At least one of the following 3 criteria: At least 20 events occurred within the county and its adjacent neighbors.ORAt least 16 events occurred within the county.ORAt least 5,000 population years within the county.AND all 3 of the following criteria:At least 6 population years for each age group used for age adjustment if that age group had 1 or more event.The number of population years in an age group was greater than the number of events.At least 100 population years within the county.More Questions?Interactive Atlas of Heart Disease and StrokeData SourcesStatistical Methods

ARIC = Atherosclerosis Risk in Communities.CMS = Centers for Medicare and Medicaid Services.*Rates per 1,000 person-years (95% confidence intervals).†Includes inpatient (MedPAR) and outpatient diagnosis of atrial fibrillation.P-values from testing the null hypothesis that the incidence rate ratio (whites compared to blacks) equals one.

Description2019 - 2022, county-level U.S. stroke hospitalization rates. Dataset developed by the Centers for Disease Control and Prevention, Division for Heart Disease and Stroke Prevention.Create maps of U.S. stroke hospitalization rates among Medicare fee-for-service beneficiaries aged 65 and older, by county. Data can be stratified by race/ethnicity and sex.Visit the CDC Atlas of Heart Disease and Stroke for additional data and maps. Atlas of Heart Disease and StrokeData SourceHospitalization data were obtained from the Centers for Medicare and Medicaid Services Medicare Provider Analysis and Review (MEDPAR) file, Part A and the Master Beneficiary Summary File (MBSF). International Classification of Diseases, 10th Revision, Clinical Modification (ICD-10-CM) codes: I60-I69; principle (i.e., first-listed) diagnosis. Medicare fee-for-service beneficiaries 65 and older were included. Visit the Atlas of Heart Disease and Stroke Statistical Methods pages for more detailed Medicare data inclusion criteria.Data DictionaryData for counties with small populations are not displayed when a reliable rate could not be generated. These counties are represented in the data with values of '-1.' CDC excludes these values when classifying the data on a map, indicating those counties as 'Insufficient Data.'Data field names and descriptionsstcty_fips: state FIPS code + county FIPS codeOther fields use the following format: RRR_S_aaaa (e.g., API_M_35UP)  RRR: 3 digits represent race/ethnicity    All - Overall   BLK - Black, non-Hispanic    HIS - Hispanic    WHT - White, non-Hispanic  S: 1 digit represents sex    A - All    F - Female    M - Male  aaaa: 4 digits represent age. The first 2 digits are the lower bound for age and the last 2 digits are the upper bound for age. 'UP' indicates the data includes the maximum age available and 'LT' indicates ages less than the upper bound. Example: The column 'BLK_M_65UP' displays rates per 1,000 black Medicare beneficiaries aged 65 years and older.MethodologyRates are calculated using a 3-year average and are age-standardized in 10-year age groups using the 2000 U.S. Standard Population. Rates are calculated and displayed per 1,000 Medicare beneficiaries. Rates were spatially smoothed using a Local Empirical Bayes algorithm to stabilize risk by borrowing information from neighboring geographic areas, making estimates more statistically robust and stable for counties with small populations. Data for counties with small populations are coded as '-1' when a reliable rate could not be generated. County-level rates were generated when the following criteria were met over a 3-year time period within each of the filters (e.g., age, race, and sex).At least one of the following 3 criteria:At least 20 events occurred within the county and its adjacent neighbors.ORAt least 16 events occurred within the county.ORAt least 5,000 population years within the county.AND all 3 of the following criteria:At least 6 population years for each age group used for age adjustment if that age group had 1 or more event.The number of population years in an age group was greater than the number of events.At least 100 population years within the county.More Questions?Interactive Atlas of Heart Disease and StrokeData SourcesStatistical Methods

2018 - 2020, county-level U.S. stroke hospitalization rates. Dataset developed by the Centers for Disease Control and Prevention, Division for Heart Disease and Stroke Prevention.Create maps of U.S. stroke hospitalization rates among Medicare fee-for-service beneficiaries aged 65 and older, by county. Data can be stratified by race/ethnicity and sex.Visit the CDC/DHDSP Atlas of Heart Disease and Stroke for additional data and maps. Atlas of Heart Disease and StrokeData SourceHospitalization data were obtained from the Centers for Medicare and Medicaid Services Medicare Provider Analysis and Review (MEDPAR) file, Part A and the Master Beneficiary Summary File (MBSF). International Classification of Diseases, 10th Revision, Clinical Modification (ICD-10-CM) codes: I60-I69; principle (i.e., first-listed) diagnosis. Medicare fee-for-service beneficiaries 65 and older were included. Visit the Atlas of Heart Disease and Stroke Statistical Methods pages for more detailed Medicare data inclusion criteria.Data DictionaryData for counties with small populations are not displayed when a reliable rate could not be generated. These counties are represented in the data with values of '-1.' CDC/DHDSP excludes these values when classifying the data on a map, indicating those counties as 'Insufficient Data.'Data field names and descriptionsstcty_fips: state FIPS code + county FIPS codeOther fields use the following format: RRR_S_aaaa (e.g., API_M_35UP)  RRR: 3 digits represent race/ethnicity    All - Overall   BLK - Black, non-Hispanic    HIS - Hispanic    WHT - White, non-Hispanic  S: 1 digit represents sex    A - All    F - Female    M - Male  aaaa: 4 digits represent age. The first 2 digits are the lower bound for age and the last 2 digits are the upper bound for age. 'UP' indicates the data includes the maximum age available and 'LT' indicates ages less than the upper bound. Example: The column 'BLK_M_65UP' displays rates per 1,000 black Medicare beneficiaries aged 65 years and older.MethodologyRates are calculated using a 3-year average and are age-standardized in 10-year age groups using the 2000 U.S. Standard Population. Rates are calculated and displayed per 1,000 Medicare beneficiaries. Rates were spatially smoothed using a Local Empirical Bayes algorithm to stabilize risk by borrowing information from neighboring geographic areas, making estimates more statistically robust and stable for counties with small populations. Data for counties with small populations are coded as '-1' when a reliable rate could not be generated. County-level rates were generated when the following criteria were met over a 3-year time period within each of the filters (e.g., age, race, and sex).At least one of the following 3 criteria:At least 20 events occurred within the county and its adjacent neighbors.ORAt least 16 events occurred within the county.ORAt least 5,000 population years within the county.AND all 3 of the following criteria:At least 6 population years for each age group used for age adjustment if that age group had 1 or more event.The number of population years in an age group was greater than the number of events.At least 100 population years within the county.More Questions?Interactive Atlas of Heart Disease and StrokeData SourcesStatistical Methods