The CMS Program Statistics - Medicare Part A & Part B - All Types of Service tables provide use and payment data by type of coverage and type of service. For additional information on enrollment, providers, and Medicare use and payment, visit the CMS Program Statistics page. These data do not exist in a machine-readable format, so the view data and API options are not available. Please use the download function to access the data. Below is the list of tables: MDCR SUMMARY AB 1. Medicare Part A and Part B Summary: Utilization, Program Payments, and Cost Sharing for All Original Medicare Beneficiaries, by Type of Coverage and Type of Service, Yearly Trend MDCR SUMMARY AB 2. Medicare Part A and Part B Summary: Utilization, Program Payments, and Cost Sharing for Aged Original Medicare Beneficiaries, by Type of Coverage and Type of Service, Yearly Trend MDCR SUMMARY AB 3. Medicare Part A and Part B Summary: Utilization, Program Payments, and Cost Sharing for Disabled Original Medicare Beneficiaries by Type of Coverage and Type of Service, Yearly Trend MDCR SUMMARY AB 4. Medicare Part A and Part B Summary: Utilization, Program Payments, and Cost Sharing for Original Medicare Beneficiaries, by Type of Coverage, Demographic Characteristics, and Medicare-Medicaid Enrollment Status MDCR SUMMARY AB 5. Medicare Part A and Part B Summary: Utilization, Program Payments, and Cost Sharing for Original Medicare Beneficiaries, by Type of Coverage and by Area of Residence MDCR SUMMARY AB 6. Medicare Part A and Part B Summary: Utilization and Program Payments for Original Medicare Beneficiaries, by Type of Entitlement, Amount of Program Payments, Type of Coverage, and Type of Service

The All CMS Data Feeds dataset is an expansive resource offering access to 118 unique report feeds, providing in-depth insights into various aspects of the U.S. healthcare system. With over 25.8 billion rows of data meticulously collected since 2007, this dataset is invaluable for healthcare professionals, analysts, researchers, and businesses seeking to understand and analyze healthcare trends, performance metrics, and demographic shifts over time. The dataset is updated monthly, ensuring that users always have access to the most current and relevant data available.

Dataset Overview:

118 Report Feeds: - The dataset includes a wide array of report feeds, each providing unique insights into different dimensions of healthcare. These topics range from Medicare and Medicaid service metrics, patient demographics, provider information, financial data, and much more. The breadth of information ensures that users can find relevant data for nearly any healthcare-related analysis. - As CMS releases new report feeds, they are automatically added to this dataset, keeping it current and expanding its utility for users.

25.8 Billion Rows of Data:

• With over 25.8 billion rows of data, this dataset provides a comprehensive view of the U.S. healthcare system. This extensive volume of data allows for granular analysis, enabling users to uncover insights that might be missed in smaller datasets. The data is also meticulously cleaned and aligned, ensuring accuracy and ease of use.

Historical Data Since 2007: - The dataset spans from 2007 to the present, offering a rich historical perspective that is essential for tracking long-term trends and changes in healthcare delivery, policy impacts, and patient outcomes. This historical data is particularly valuable for conducting longitudinal studies and evaluating the effects of various healthcare interventions over time.

Monthly Updates:

• To ensure that users have access to the most current information, the dataset is updated monthly. These updates include new reports as well as revisions to existing data, making the dataset a continuously evolving resource that stays relevant and accurate.

Data Sourced from CMS:

• The data in this dataset is sourced directly from the Centers for Medicare & Medicaid Services (CMS). After collection, the data is meticulously cleaned and its attributes are aligned, ensuring consistency, accuracy, and ease of use for any application. Furthermore, any new updates or releases from CMS are automatically integrated into the dataset, keeping it comprehensive and current.

Use Cases:

Market Analysis:

• The dataset is ideal for market analysts who need to understand the dynamics of the healthcare industry. The extensive historical data allows for detailed segmentation and analysis, helping users identify trends, market shifts, and growth opportunities. The comprehensive nature of the data enables users to perform in-depth analyses of specific market segments, making it a valuable tool for strategic decision-making.

Healthcare Research:

• Researchers will find the All CMS Data Feeds dataset to be a robust foundation for academic and commercial research. The historical data, combined with the breadth of coverage across various healthcare metrics, supports rigorous, in-depth analysis. Researchers can explore the effects of healthcare policies, study patient outcomes, analyze provider performance, and more, all within a single, comprehensive dataset.

Performance Tracking:

• Healthcare providers and organizations can use the dataset to track performance metrics over time. By comparing data across different periods, organizations can identify areas for improvement, monitor the effectiveness of initiatives, and ensure compliance with regulatory standards. The dataset provides the detailed, reliable data needed to track and analyze key performance indicators.

Compliance and Regulatory Reporting:

• The dataset is also an essential tool for compliance officers and those involved in regulatory reporting. With detailed data on provider performance, patient outcomes, and healthcare utilization, the dataset helps organizations meet regulatory requirements, prepare for audits, and ensure adherence to best practices. The accuracy and comprehensiveness of the data make it a trusted resource for regulatory compliance.

Data Quality and Reliability:

The All CMS Data Feeds dataset is designed with a strong emphasis on data quality and reliability. Each row of data is meticulously cleaned and aligned, ensuring that it is both accurate and consistent. This attention to detail makes the dataset a trusted resource for high-stakes applications, where data quality is critical.

Integration and Usability:

Ease of Integration:

• The dataset is provided in a CSV format, which is widely compatible with most data analysis tools and platforms. This ensures that users can easily integrate the data into their existing wo...

Context

The CMS National Plan and Provider Enumeration System (NPPES) was developed as part of the Administrative Simplification provisions in the original HIPAA act. The primary purpose of NPPES was to develop a unique identifier for each physician that billed medicare and medicaid. This identifier is now known as the National Provider Identifier Standard (NPI) which is a required 10 digit number that is unique to an individual provider at the national level.

Once an NPI record is assigned to a healthcare provider, parts of the NPI record that have public relevance, including the provider’s name, speciality, and practice address are published in a searchable website as well as downloadable file of zipped data containing all of the FOIA disclosable health care provider data in NPPES and a separate PDF file of code values which documents and lists the descriptions for all of the codes found in the data file.

Content

The dataset contains the latest NPI downloadable file in an easy to query BigQuery table, npi_raw. In addition, there is a second table, npi_optimized which harnesses the power of Big Query’s next-generation columnar storage format to provide an analytical view of the NPI data containing description fields for the codes based on the mappings in Data Dissemination Public File - Code Values documentation as well as external lookups to the healthcare provider taxonomy codes . While this generates hundreds of columns, BigQuery makes it possible to process all this data effectively and have a convenient single lookup table for all provider information.

Fork this kernel to get started.

Acknowledgements

https://bigquery.cloud.google.com/dataset/bigquery-public-data:nppes?_ga=2.117120578.-577194880.1523455401

https://console.cloud.google.com/marketplace/details/hhs/nppes?filter=category:science-research

Dataset Source: Center for Medicare and Medicaid Services. This dataset is publicly available for anyone to use under the following terms provided by the Dataset Source - http://www.data.gov/privacy-policy#data_policy — and is provided "AS IS" without any warranty, express or implied, from Google. Google disclaims all liability for any damages, direct or indirect, resulting from the use of the dataset.

Banner Photo by @rawpixel from Unplash.

Inspiration

What are the top ten most common types of physicians in Mountain View?

What are the names and phone numbers of dentists in California who studied public health?

The CMS Program Statistics - Medicare Total Enrollment tables provide data on characteristics of the Medicare-covered populations. For additional information on enrollment, providers, and Medicare use and payment, visit the CMS Program Statistics page. These data do not exist in a machine-readable format, so the view data and API options are not available. Please use the download function to access the data. Below is the list of tables: MDCR ENROLL AB 1. Total Medicare Enrollment: Total, Original Medicare, and Medicare Advantage and Other Health Plan Enrollment, Yearly Trend MDCR ENROLL AB 2. Total Medicare Enrollment: Total, Original Medicare, Medicare Advantage and Other Health Plan Enrollment, and Resident Population, by Area of Residence MDCR ENROLL AB 3. Total Medicare Enrollment: Part A and/or Part B Total, Aged, and Disabled Enrollees, Yearly Trend MDCR ENROLL AB 4. Total Medicare Enrollment: Part A and/or Part B Enrollees, by Age Group, Yearly Trend MDCR ENROLL AB 5. Total Medicare Enrollment: Part A and/or Part B Enrollees, by Demographic Characteristics MDCR ENROLL AB 6. Total Medicare Enrollment: Part A and/or Part B Enrollees, by Type of Entitlement and Demographic Characteristics MDCR ENROLL AB 7. Total Medicare Enrollment: Part A and/or Part B Total, Aged, and Disabled Enrollees, by Area of Residence MDCR ENROLL AB 8. Total Medicare Enrollment: Part A and/or Part B Enrollees, by Type of Entitlement and Area of Residence

Content

This crosswalk links the types of providers and suppliers who are eligible to apply for enrollment in the Medicare program with the appropriate Healthcare Provider Taxonomy Codes. This crosswalk includes the Medicare Specialty Codes for those provider/supplier types who have Medicare Specialty Codes. The Healthcare Provider Taxonomy Code Set is available from the Washington Publishing Company (www.wpc-edi.com) and is maintained by the National Uniform Claim Committee (www.nucc.org). The code set is updated twice a year, with the updates being effective April 1 and October 1 of each year. This document reflects Healthcare Provider Taxonomy Codes effective for use on April 2, 2018.

When changes are made to Medicare provider enrollment requirements, the Medicare Specialty Codes, or the Healthcare Provider Taxonomy Code Set, this document may need to be revised.

NOTE: This document does not alter existing Medicare claims preparation, processing, or payment instructions, nor does it alter existing Medicare provider enrollment requirements or policies.

Context

This is a dataset hosted by the Centers for Medicare & Medicaid Services (CMS). The organization has an open data platform found here and they update their information according the amount of data that is brought in. Explore CMS's Data using Kaggle and all of the data sources available through the CMS organization page!

• Update Frequency: This dataset is updated daily.

Acknowledgements

This dataset is maintained using Socrata's API and Kaggle's API. Socrata has assisted countless organizations with hosting their open data and has been an integral part of the process of bringing more data to the public.

Cover photo by Markus Spiske on Unsplash
Unsplash Images are distributed under a unique Unsplash License.

This dataset is distributed under NA

Context

In the United States, Medicare is a single-payer, national social insurance program administered by the U.S. federal government since 1966. It provides health insurance for Americans aged 65 and older who have worked and paid into the system through the payroll tax. Source: https://en.wikipedia.org/wiki/Medicare_(United_States)

Content

This public dataset was created by the Centers for Medicare & Medicaid Services. The data summarizes the utilization and payments for procedures, services, and prescription drugs provided to Medicare beneficiaries by specific inpatient and outpatient hospitals, physicians, and other suppliers. The dataset includes the following data.

Common inpatient and outpatient services All physician and other supplier procedures and services All Part D prescriptions. Providers determine what they will charge for items, services, and procedures provided to patients and these charges are the amount that providers bill for an item, service, or procedure.

Fork this kernel to get started.

Acknowledgements

https://bigquery.cloud.google.com/dataset/bigquery-public-data:medicare

https://cloud.google.com/bigquery/public-data/medicare

Dataset Source: Center for Medicare and Medicaid Services. This dataset is publicly available for anyone to use under the following terms provided by the Dataset Source - http://www.data.gov/privacy-policy#data_policy — and is provided "AS IS" without any warranty, express or implied, from Google. Google disclaims all liability for any damages, direct or indirect, resulting from the use of the dataset.

Banner Photo by @rawpixel from Unplash.

Inspiration

What is the total number of medications prescribed in each state?

What is the most prescribed medication in each state?

What is the average cost for inpatient and outpatient treatment in each city and state?

Which are the most common inpatient diagnostic conditions in the United States?

Which cities have the most number of cases for each diagnostic condition?

What are the average payments for these conditions in these cities and how do they compare to the national average?

Centers for Medicare & Medicaid Services - Nursing HomesThis feature layer, utilizing data from the Centers for Medicare & Medicaid Services (CMS), displays the locations of nursing homes in the U.S. Nursing homes provide a type of residential care. They are a place of residence for people who require constant nursing care and have significant deficiencies with activities of daily living. Per CMS, "Nursing homes, which include Skilled Nursing Facilities (SNFs) and Nursing Facilities (NFs), are required to be in compliance with Federal requirements to receive payment under the Medicare or Medicaid programs. The Secretary of the United States Department of Health & Human Services has delegated to the CMS and the State Medicaid Agency the authority to impose enforcement remedies against a nursing home that does not meet Federal requirements." This layer includes currently active nursing homes, including number of certified beds, address, and other information.Bridgepoint Sub-Acute and Rehab Capitol HillData downloaded: August 1, 2024Data source: Provider InformationData modification: This dataset includes only those facilities with addresses that were appropriately geocoded.For more information: Nursing homes including rehab servicesFor feedback, please contact: ArcGIScomNationalMaps@esri.comCenters for Medicare & Medicaid ServicesPer USA.gov, "The Centers for Medicare and Medicaid Services (CMS) provides health coverage to more than 100 million people through Medicare, Medicaid, the Children’s Health Insurance Program, and the Health Insurance Marketplace. The CMS seeks to strengthen and modernize the Nation’s health care system, to provide access to high quality care and improved health at lower costs."

This dataset contains estimates of tree canopy cover presence at high resolution (0.5m) across the state of Vermont for 2016 in Cloud-Optimized GeoTIFF (*.tif) format. Tree canopy was derived from 2016 high-resolution remotely sensed data as part of the Vermont High-Resolution Land Cover mapping project. Object-based image analysis techniques (OBIA) were employed to extract potential tree canopy and trees using the best available remotely sensed and vector GIS datasets. OBIA systems work by grouping pixels into meaningful objects based on their spectral and spatial properties, while taking into account boundaries imposed by existing vector datasets. Within the OBIA environment a rule-based expert system was designed to effectively mimic the process of manual image analysis by incorporating the elements of image interpretation (color/tone, texture, pattern, location, size, and shape) into the classification process. A series of morphological procedures were employed to ensure that the end product is both accurate and cartographically pleasing. Following the automated OBIA mapping a detailed manual review of the dataset was carried out at a scale of 1:3000 and all observable errors were corrected. Tree canopy assessments have been conducted for numerous communities throughout the U.S. where the results have been instrumental in helping to establish tree canopy goals.

The All CMS Data Feeds dataset is an expansive resource offering access to 118 unique report feeds, providing in-depth insights into various aspects of the U.S. healthcare system. With over 25.8 billion rows of data meticulously collected since 2007, this dataset is invaluable for healthcare professionals, analysts, researchers, and businesses seeking to understand and analyze healthcare trends, performance metrics, and demographic shifts over time. The dataset is updated monthly, ensuring that users always have access to the most current and relevant data available.

Dataset Overview:

118 Report Feeds: - The dataset includes a wide array of report feeds, each providing unique insights into different dimensions of healthcare. These topics range from Medicare and Medicaid service metrics, patient demographics, provider information, financial data, and much more. The breadth of information ensures that users can find relevant data for nearly any healthcare-related analysis. - As CMS releases new report feeds, they are automatically added to this dataset, keeping it current and expanding its utility for users.

25.8 Billion Rows of Data:

• With over 25.8 billion rows of data, this dataset provides a comprehensive view of the U.S. healthcare system. This extensive volume of data allows for granular analysis, enabling users to uncover insights that might be missed in smaller datasets. The data is also meticulously cleaned and aligned, ensuring accuracy and ease of use.

Historical Data Since 2007: - The dataset spans from 2007 to the present, offering a rich historical perspective that is essential for tracking long-term trends and changes in healthcare delivery, policy impacts, and patient outcomes. This historical data is particularly valuable for conducting longitudinal studies and evaluating the effects of various healthcare interventions over time.

Monthly Updates:

• To ensure that users have access to the most current information, the dataset is updated monthly. These updates include new reports as well as revisions to existing data, making the dataset a continuously evolving resource that stays relevant and accurate.

Data Sourced from CMS:

• The data in this dataset is sourced directly from the Centers for Medicare & Medicaid Services (CMS). After collection, the data is meticulously cleaned and its attributes are aligned, ensuring consistency, accuracy, and ease of use for any application. Furthermore, any new updates or releases from CMS are automatically integrated into the dataset, keeping it comprehensive and current.

Use Cases:

Market Analysis:

• The dataset is ideal for market analysts who need to understand the dynamics of the healthcare industry. The extensive historical data allows for detailed segmentation and analysis, helping users identify trends, market shifts, and growth opportunities. The comprehensive nature of the data enables users to perform in-depth analyses of specific market segments, making it a valuable tool for strategic decision-making.

Healthcare Research:

• Researchers will find the All CMS Data Feeds dataset to be a robust foundation for academic and commercial research. The historical data, combined with the breadth of coverage across various healthcare metrics, supports rigorous, in-depth analysis. Researchers can explore the effects of healthcare policies, study patient outcomes, analyze provider performance, and more, all within a single, comprehensive dataset.

Performance Tracking:

• Healthcare providers and organizations can use the dataset to track performance metrics over time. By comparing data across different periods, organizations can identify areas for improvement, monitor the effectiveness of initiatives, and ensure compliance with regulatory standards. The dataset provides the detailed, reliable data needed to track and analyze key performance indicators.

Compliance and Regulatory Reporting:

• The dataset is also an essential tool for compliance officers and those involved in regulatory reporting. With detailed data on provider performance, patient outcomes, and healthcare utilization, the dataset helps organizations meet regulatory requirements, prepare for audits, and ensure adherence to best practices. The accuracy and comprehensiveness of the data make it a trusted resource for regulatory compliance.

Data Quality and Reliability:

The All CMS Data Feeds dataset is designed with a strong emphasis on data quality and reliability. Each row of data is meticulously cleaned and aligned, ensuring that it is both accurate and consistent. This attention to detail makes the dataset a trusted resource for high-stakes applications, where data quality is critical.

Integration and Usability:

Ease of Integration:

• The dataset is provided in a CSV format, which is widely compatible with most data analysis tools and platforms. This ensures that users can easily integrate the data into their existing wo...

This series of files links two large population-based sources providing detailed data about Medicare beneficiaries with cancer. The SEER (Surveillance, Epidemiology, and End Results) program consists of clinical, demographic, and cause of death information collected from tumor registries beginning in January 1, 1973. The Medicare contribution includes all claims for covered health care services from beneficiaries’ time of eligibility until death. Linkage is processed biennially by SEER and Centers for Medicare and Medicaid Services (CMS) staff. 95% of individuals age 65 and older are included in the SEER files. Due to privacy concerns, access to this database requires an application, SEER-Medicare Data Use Agreement (DUA), and documentation of institutional review board approval. Additionally, the National Cancer Institute’s information technology contractor assesses a processing fee the amount of which is dependent upon the type and number of files requested.

This dataset includes the total number of individuals enrolled in Medi-Cal by eligibility group: Modified Adjusted Gross Income (MAGI), non-MAGI, and Children’s Health Insurance Program (CHIP). The groups are defined by the Centers for Medicare and Medicaid Services (CMS) Performance Indicators (CMSPI) reporting requirements. The Department of Health Care Services (DHCS) submits eligibility and enrollment data regarding Medicaid and CHIP monthly to CMS. The enrollment data represents enrollment totals as of 60 days after the eligibility month (indicated as “Reporting Period” in the dataset). CMS publishes the state total enrollments on the CMSPI website. The total enrollment comprises of individuals who are eligible for full scope Medi-Cal by MAGI – Child, MAGI – Adult, Non-MAGI Child, Non-MAGI Adult, and CHIP eligibility groups. DHCS does not report to CMS the total enrollment in limited scope Medi-Cal or state-only funded programs (indicated as the “Non-CMSPI” in the dataset).

The Medicare Home Health Agency tables provide use and payment data for home health agencies. The tables include use and expenditure data from home health Part A (Hospital Insurance) and Part B (Medical Insurance) claims. For additional information on enrollment, providers, and Medicare use and payment, visit the CMS Program Statistics page. These data do not exist in a machine-readable format, so the view data and API options are not available. Please use the download function to access the data. Below is the list of tables: MDCR HHA 1. Medicare Home Health Agencies: Utilization and Program Payments for Original Medicare Beneficiaries, by Type of Entitlement, Yearly Trend MDCR HHA 2. Medicare Home Health Agencies: Utilization and Program Payments for Original Medicare Beneficiaries, by Demographic Characteristics and Medicare-Medicaid Enrollment Status MDCR HHA 3. Medicare Home Health Agencies: Utilization and Program Payments for Original Medicare Beneficiaries, by Area of Residence MDCR HHA 4. Medicare Home Health Agencies: Persons with Utilization and Total Service Visits for Original Medicare Beneficiaries, Type of Agency and Type of Service Visit MDCR HHA 5. Medicare Home Health Agencies: Persons with Utilization and Total Service Visits for Original Medicare Beneficiaries, by Type of Control and Type of Service Visit MDCR HHA 6. Medicare Home Health Agencies: Persons with Utilization, Total Service Visits, and Program Payments for Original Medicare Beneficiaries, by Number of Service Visits and Number of Episodes

The Case Mix Index (CMI) is the average relative DRG weight of a hospital’s inpatient discharges, calculated by summing the Medicare Severity-Diagnosis Related Group (MS-DRG) weight for each discharge and dividing the total by the number of discharges. The CMI reflects the diversity, clinical complexity, and resource needs of all the patients in the hospital. A higher CMI indicates a more complex and resource-intensive case load. Although the MS-DRG weights, provided by the Centers for Medicare & Medicaid Services (CMS), were designed for the Medicare population, they are applied here to all discharges regardless of payer. Note: It is not meaningful to add the CMI values together.

Metrics from individual Marketplaces during the current reporting period. The report includes data for the states using HealthCare.gov. As of August 2024, CMS is no longer releasing the “HealthCare.gov” metrics. Historical data between July 2023-July 2024 will remain available. The “HealthCare.gov Transitions” metrics, which are the CAA, 2023 required metrics, will continue to be released.
Sources: HealthCare.gov application and policy data through May 5, 2024, and T-MSIS Analytic Files (TAF) through March 2024 (TAF version 7.1 with T-MSIS enrollment through the end of March 2024). Data include consumers in HealthCare.gov states where the first unwinding renewal cohort is due on or after the end of reporting month (state identification based on HealthCare.gov policy and application data). State data start being reported in the month when the state's first unwinding renewal cohort is due. April data include Arizona, Arkansas, Florida, Indiana, Iowa, Kansas, Nebraska, New Hampshire, Ohio, Oklahoma, South Dakota, Utah, West Virginia, and Wyoming. May data include the previous states and the following new states: Alaska, Delaware, Georgia, Hawaii, Montana, North Dakota, South Carolina, Texas, and Virginia. June data include the previous states and the following new states: Alabama, Illinois, Louisiana, Michigan, Missouri, Mississippi, North Carolina, Tennessee, and Wisconsin. July data include the previous states and Oregon. All HealthCare.gov states are included in this version of the report.
Notes:

1. This table includes Marketplace consumers who: 1) submitted a HealthCare.gov application on or after the start of each state’s first reporting month; and 2) who can be linked to an enrollment record in TAF that shows Medicaid or CHIP enrollment between March 2023 and the latest reporting month.
2. Cumulative counts show the number of unique consumers from the included population who had a Marketplace application submitted or a HealthCare.gov Marketplace policy on or after the start of each state’s first reporting month through the latest reporting month. Net counts show the difference between the cumulative counts through a given reporting month and previous reporting months.
3. The data used to produce the metrics are organized by week. Reporting months start on the first Monday of the month and end on the first Sunday of the next month when the last day of the reporting month is not a Sunday. For example, the April 2023 reporting period extends from Monday, April 3 through Sunday, April 30.
4. Data are preliminary and will be restated over time to reflect consumers most recent HealthCare.gov status. Data may change as states resubmit T-MSIS data or data quality issues are identified.
5. Data do not represent Marketplace consumers who had a confirmed Medicaid/CHIP loss. Future reporting will look at coverage transitions for people who lost Medicaid/CHIP.
6. See the data and methodology documentation for a full description of the data sources, measure definitions, and general data limitations.

1. Virginia operated a Federally Facilitated Exchange (FFE) on the HealthCare.gov platform during 2023. In 2024, the state started operating a State Based Marketplace (SBM) platform. This table only includes data on 2023 applications and policies obtained through the HealthCare.gov Marketplace. Due to limited Marketplace activity on the HealthCare.gov platform in December 2023, data from December 2023 onward are excluded. The cumulative count and percentage for Virginia and the HealthCare.gov total reflect Virginia data from April 2023 through November 2023.
2. The report may include negative 'net counts,' which reflect that there were cumulatively fewer counts from one month to the next.
3. Wyoming has negative ‘net counts’ for most of its metrics in March 2024, including 'Marketplace Consumers with Previous M

Hospitals Registered with MedicareThis feature layer, utilizing data from the Centers of Medicare and Medicaid Services (CMS), depicts all hospitals that are currently registered with Medicare in the U.S. Per NIH, "Since the passage of Medicare legislation in 1965, Section 1861 of the Social Security Act has stated that hospitals participating in Medicare must meet certain requirements specified in the act and that the Secretary of the Department of Health, Education and Welfare (HEW) [now the Department of Health and Human Services (DHHS)] may impose additional requirements found necessary to ensure the health and safety of Medicare beneficiaries receiving services in hospitals. On this basis, the Conditions of Participation, a set of regulations setting minimum health and safety standards for hospitals participating in Medicare, were promulgated in 1966 and substantially revised in 1986."Ascension Columbia St Mary's HospitalData currency: 11/26/2024Data modification: This data was created using the geocoding process on the CSV file.Data downloaded from: Hospital General InformationFor more information: HospitalsSupport documentation: Data dictionaryFor feedback, please contact: ArcGIScomNationalMaps@esri.comCenters of Medicare and Medicaid ServicesPer USA.gov, "The Centers for Medicare and Medicaid Services (CMS) provides health coverage to more than 100 million people through Medicare, Medicaid, the Children’s Health Insurance Program, and the Health Insurance Marketplace. The CMS seeks to strengthen and modernize the Nation’s health care system, to provide access to high quality care and improved health at lower costs."

Data consist of CMS Medicare data files which are restricted access and cannot be released publicly. 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. EPA cannot release CBI, or data protected by copyright, patent, or otherwise subject to trade secret restrictions. Request for access to CBI data may be directed to the dataset owner by an authorized person by contacting the party listed. It can be accessed through the following means: CMS Medicare data are available from: https://www.cms.gov/data-research/files-for-order/data-disclosures-and-data-use-agreements-duas/limited-data-set-lds with the requirement of a signed Data Use Agreement. . Weather data are available at https://prism.oregonstate.edu/. Format: The data that support the findings of this study are available from the Centers for Medicare and Medicaid Services (CMS). Restrictions apply to the availability of these data, which were provided under a Data Use Agreement specific to this study. Data are available from: https://www.cms.gov/data-research/files-for-order/data-disclosures-and-data-use-agreements-duas/limited-data-set-lds with the requirement of a signed Data Use Agreement. Data do not contain personally identifiable information but contain are classified as Limited Data Set files and their distribution require an agreement and between CMS and the requester and approval by CMS. Weather data are available at https://prism.oregonstate.edu/. Because the data do not contain identifiable private information and were not obtained through interaction or intervention with individuals, the Institutional Review Board for the University of North Carolina and the US Environmental Protection Agency Human Research Protocol Officer determined that use of this data does not constitute human subjects research. This dataset is associated with the following publication: Wade, T., and C. Herbert. Weather conditions and legionellosis: a nationwide case-crossover study among Medicare recipients. EPIDEMIOLOGY AND INFECTION. Cambridge University Press, Cambridge, UK, 152: E125, (2024).

Methodology

None

Usage

This dataset page includes some of the tables from the Medicare Data in PHS's possession. Other Medicare tables are included on other dataset pages on the PHS Data Portal. Depending upon your research question and your DUA with CMS, you may only need tables from a subset of the Medicare dataset pages, or you may need tables from all of them.

The location of each of the Medicare tables (i.e. a chart of which tables are included in each Medicare dataset page) is shown here.

Before Manuscript Submission

All manuscripts (and other items you'd like to publish) must be submitted to

support@stanfordphs.freshdesk.com for approval prior to journal submission.

We will check your cell sizes and citations.

For more information about how to cite PHS and PHS datasets, please visit:

https:/phsdocs.developerhub.io/need-help/citing-phs-data-core

Documentation

CMS has created a set of analytical files that contain data from the Medicare Shared Saving Program. There are two separate files in this data set:

• The Shared Savings Program Beneficiary-Level Research Identifiable File (RIF)
• The Shared Savings Program Provider-Level RIF

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Section 2

Metadata access is required to view this section.

Context

This public dataset was created by the Centers for Medicare & Medicaid Services. The data summarize counts of enrollees who are dually-eligible for both Medicare and Medicaid program, including those in Medicare Savings Programs. “Duals” represent 20 percent of all Medicare beneficiaries, yet they account for 34 percent of all spending by the program, according to the Commonwealth Fund . As a representation of this high-needs, high-cost population, these data offer a view of regions ripe for more intensive care coordination that can address complex social and clinical needs. In addition to the high cost savings opportunity to deliver upstream clinical interventions, this population represents the county-by-county volume of patients who are eligible for both state level (Medicaid) and federal level (Medicare) reimbursements and potential funding streams to address unmet social needs across various programs, waivers, and other projects. The dataset includes eligibility type and enrollment by quarter, at both the state and county level. These data represent monthly snapshots submitted by states to the CMS, which are inherently lower than ever-enrolled counts (which include persons enrolled at any time during a calendar year.) For more information on dually eligible beneficiaries

Querying BigQuery tables

You can use the BigQuery Python client library to query tables in this dataset in Kernels. Note that methods available in Kernels are limited to querying data. Tables are at bigquery-public-data.sdoh_cms_dual_eligible_enrollment.

Sample Query

In what counties in Michigan has the number of dual-eligible individuals increased the most from 2015 to 2018? Find the counties in Michigan which have experienced the largest increase of dual enrollment households

duals_Jan_2015 AS ( SELECT Public_Total AS duals_2015, County_Name, FIPS FROM bigquery-public-data.sdoh_cms_dual_eligible_enrollment.dual_eligible_enrollment_by_county_and_program WHERE State_Abbr = "MI" AND Date = '2015-12-01' ),

duals_increase AS ( SELECT d18.FIPS, d18.County_Name, d15.duals_2015, d18.duals_2018, (d18.duals_2018 - d15.duals_2015) AS total_duals_diff FROM duals_Jan_2018 d18 JOIN duals_Jan_2015 d15 ON d18.FIPS = d15.FIPS )

SELECT * FROM duals_increase WHERE total_duals_diff IS NOT NULL ORDER BY total_duals_diff DESC

This dataset provides maps of aboveground tidal marsh biomass (g/m2) at 30 m resolution for six estuarine regions of the conterminous United States: Cape Cod, MA; Chesapeake Bay, MD, Everglades, FL; Mississippi Delta, LA; San Francisco Bay, CA; and Puget Sound, WA. Estuarine and palustrine emergent tidal marsh areas were based on a 2010 NOAA Coastal Change Analysis Program (C-CAP) map. Aboveground biomass maps were generated from a random forest model driven by Landsat vegetation indices and a national scale dataset of field-measured aboveground biomass. The final model, driven by six Landsat vegetation indices, with the soil adjusted vegetation index as the most important, successfully predicted biomass for a range of marsh plant functional types defined by height, leaf angle, and growth form. Biomass can be converted to carbon stocks using a mean plant carbon content of 44.1%.

1. Enrollment includes both Medicaid-only and Medicare-Medicaid (“dual”) enrollees. For both types of enrollees, Medicaid covers LTSS. For dual enrollees, Medicaid may also cover Medicare cost-sharing for acute, primary care, and specialty services covered by Medicare, and other non-LTSS services that are not covered by Medicare.
2. Some comprehensive managed care programs enroll beneficiaries who may be at risk of needing LTSS but do not receive any LTSS. These counts only include individuals that receive LTSS. Moreover, states differ in their ability to report individuals who use MLTSS versus those who are enrolled (and may or may not be using LTSS). This table reports MLTSS users unless otherwise noted.
3. Comprehensive Managed Care Including LTSS does not include PACE programs.
4. MLTSS Only programs cover LTSS under capitation; acute, primary, and specialty care services for these enrollees may be covered by another Medicaid MCO, Medicaid FFS, or by Medicare for dual enrollees. These data include states that provide MLTSS plus other benefits in a package that does not include inpatient medical care.
5. The indicated territory was not able to supply data for this report. The Northern Mariana Islands reported that they have no Medicaid managed care enrollment, but they did not report total Medicaid enrollees.
6. Enrollment and user counts include both Medicaid-only enrollees and dually eligible individuals. For both types of enrollees, Medicaid covers LTSS. For dually eligible individuals, Medicaid may also cover Medicare cost-sharing for acute, primary care, and specialty services covered by Medicare, and other non-LTSS services that are not covered by Medicare.
7. The “Comprehensive Managed Care Including LTSS” column does not include PACE programs.
8. Columns indicating the "Number of enrollees using LTSS" reflect what states reported. In addition to the three states that reported LTSS users (Arizona, New York and Wisconsin), California and Delaware also offer LTSS services in a stand-alone program.
9. Note: "n/a" indicates that a state or territory was not able to report data or does not have a managed care program. "--" indicates that a state or territory does not operate programs of the type listed in the column heading. Enrollment and user counts include both Medicaid-only and dually eligible individuals. For both types of enrollees, Medicaid covers LTSS. For dually eligible individuals, Medicaid may also cover Medicare cost-sharing for acute, primary care, and specialty services covered by Medicare and other non-LTSS services that are not covered by Medicare.
10. Columns indicating the "Number of enrollees using LTSS" reflect what states reported. In addition to the three states that reported LTSS users (Arizona, New York and Wisconsin), California and Delaware also offer LTSS services in a stand-alone program.