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 dataset contains Medicaid data from patients under 18 years of age, byZIP Code Tabulation Areas (ZCTAs), in Michigan in 2017. This dataset contains percentage of visits to the Emergency Room, Hospital, and Urgent Care, noting Asthma and Diabetes patients. Medicaid data was provided by the Michigan Department of Health and Human Services (MDHHS) to Data Driven Detroit in 2018. Data Driven Detroit aggregated the dataset for a statewide analysis. Null values represent no Medicaid data or suppressed numbers (smaller than 6) to protect the information of individuals.Click here for metadata (descriptions of the fields).

Analysis of ‘Medicaid Claims (MAX) - Vision and Eye Health Surveillance’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/48613398-7f2e-4826-8469-fabe387aa236 on 12 February 2022.

--- Dataset description provided by original source is as follows ---

2013, 2014. This dataset is a de-identified summary table of prevalence rates for vision and eye health data indicators from the Medicaid Analytic eXtract (MAX) data. Medicaid MAX are a set of de-identified person-level data files with information on Medicaid eligibility, service utilization, diagnoses, and payments. The MAX data contain a convenience sample of claims processed by Medicaid and Children’s Health Insurance Program (CHIP) fee for service and managed care plans. Not all states are included in MAX in all years, and as of November 2019, 2014 data is the latest available. Prevalence estimates are stratified by all available combinations of age group, gender, and state. Detailed information on VEHSS Medicare analyses can be found on the VEHSS Medicaid MAX webpage (cdc.gov/visionhealth/vehss/data/claims/medicaid.html). Information on available Medicare claims data can be found on the ResDac website (www.resdac.org). The VEHSS Medicaid MAX dataset was last updated November 2019.

--- Original source retains full ownership of the source dataset ---

This dataset contains Medicaid data from patients under 18 years of age, by Metropolitan Statistical Area (MSA), in Michigan in 2017. This dataset contains percentage of visits to the Emergency Room, Hospital, and Urgent Care, noting Asthma and Diabetes patients. Medicaid data was provided by the Michigan Department of Health and Human Services (MDHHS) to Data Driven Detroit in 2018. Data Driven Detroit aggregated the dataset for a statewide analysis. Null values represent no Medicaid data or suppressed numbers (smaller than 6) to protect the information of individuals.Click here for metadata (descriptions of the fields).

In the U.S., every hospital that receives payments from Medicare and Medicaid is mandated to provide quality data to The Centers for Medicare and Medicaid Services (CMS) annually. This data helps gauge patient satisfaction levels across the country. While overall hospital scores can be influenced by the quality of customer services, there may also be variations in satisfaction based on the type of hospital or its location.

Year: 2016 - 2020

The Star Rating Program, implemented by The Centers for Medicare & Medicaid Services (CMS), employs a five-star grading system to evaluate the experiences of Medicare beneficiaries with their respective health plans and the overall healthcare system. Health plans receive scores ranging from 1 to 5 stars, with 5 stars denoting the highest quality.

Benefits:

Historical Analysis: With data spanning from 2016 to 2020, researchers and analysts can observe trends over time, understanding how patient satisfaction has evolved over these years.

Benchmarking: Hospitals can compare their performance against national averages or against peer institutions to see where they stand.

Identifying Areas for Improvement: By analyzing specific metrics and feedback, hospitals can pinpoint areas where their services may be lacking and need enhancement.

Policy and Decision Making: Governments and healthcare administrators can use the data to make informed decisions about healthcare policies, funding allocations, and other strategic decisions.

Research and Academic Purposes: Academics and researchers can use the dataset for various studies, including correlational studies, predictions, and more.

Geographical Insights: The dataset may provide insights into regional variations in patient satisfaction, helping to identify areas or states with particularly high or low scores.

Understanding Factors Affecting Satisfaction: By correlating satisfaction scores with other variables (e.g., hospital type, size, location), it might be possible to determine which factors play the most significant role in patient satisfaction.

Performance Evaluation: Hospitals can use the data to evaluate the efficacy of any interventions or changes they've made over the years in terms of improving patient satisfaction.

Enhancing Patient Trust: Demonstrating transparency and a commitment to improvement can enhance patient trust and loyalty.

Informed Patients: By making such data publicly available, potential patients can make more informed decisions about where to seek care based on the satisfaction ratings of previous patients.

Source: https://data.cms.gov/provider-data/archived-data/hospitals

Analysis of ‘Medicaid CY2017 byCountySub 20181106’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/bb1a7427-442e-49a0-a723-a0528dce0dd5 on 26 January 2022.

--- Dataset description provided by original source is as follows ---

This dataset contains Medicaid data from patients under 18 years of age, by county subdivision, in Michigan in 2017. This dataset contains percentage of visits to the Emergency Room, Hospital, and Urgent Care, noting Asthma and Diabetes patients. Medicaid data was provided by the Michigan Department of Health and Human Services (MDHHS) to Data Driven Detroit in 2018. Data Driven Detroit aggregated the dataset for a statewide analysis. Null values represent no Medicaid data or suppressed numbers (smaller than 6) to protect the information of individuals.

--- Original source retains full ownership of the source dataset ---

Summary of generalized linear model analysis for Medicaid coverage factors predicting emergency department self-harm visit rate in the general population older than 14 years.

15,660 U.S nursing homes from the fourth quarter of 2017 Nursing Home Compare archived data were geocoded with exact addresses.

Summary of generalized linear model analysis for Medicaid coverage factors predicting emergency department self-harm visit rate in middle-aged adults (35–64 years old).

This dataset contains Medicaid data from patients under 18 years of age, by county subdivision, in Michigan in 2017. This dataset contains percentage of visits to the Emergency Room, Hospital, and Urgent Care, noting Asthma and Diabetes patients. Medicaid data was provided by the Michigan Department of Health and Human Services (MDHHS) to Data Driven Detroit in 2018. Data Driven Detroit aggregated the dataset for a statewide analysis. Null values represent no Medicaid data or suppressed numbers (smaller than 6) to protect the information of individuals.

Analysis of ‘Center for Medicare & Medicaid Services (CMS) , Medicare Claims data’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/46975378-a51c-42ad-b06e-5aae9db45d16 on 12 February 2022.

--- Dataset description provided by original source is as follows ---

2003 forward. CMS compiles claims data for Medicare and Medicaid patients across a variety of categories and years. This includes Inpatient and Outpatient claims, Master Beneficiary Summary Files, and many other files. Indicators from this data source have been computed by personnel in CDC's Division for Heart Disease and Stroke Prevention (DHDSP). This is one of the datasets provided by the National Cardiovascular Disease Surveillance System. The system is designed to integrate multiple indicators from many data sources to provide a comprehensive picture of the public health burden of CVDs and associated risk factors in the United States. The data are organized by location (national and state) and indicator. The data can be plotted as trends and stratified by sex and race/ethnicity.

--- Original source retains full ownership of the source dataset ---

This dataset contains Medicaid data from patients under 18 years of age, by congressional district, in Michigan in 2017. This dataset contains percentage of visits to the Emergency Room, Hospital, and Urgent Care, noting Asthma and Diabetes patients. Medicaid data was provided by the Michigan Department of Health and Human Services (MDHHS) to Data Driven Detroit in 2018. Data Driven Detroit aggregated the dataset for a statewide analysis. Null values represent no Medicaid data or suppressed numbers (smaller than 6) to protect the information of individuals.

This dataset contains Medicaid data from patients under 18 years of age, by school district, in Michigan in 2017. This dataset contains percentage of visits to the Emergency Room, Hospital, and Urgent Care, noting Asthma and Diabetes patients. Medicaid data was provided by the Michigan Department of Health and Human Services (MDHHS) to Data Driven Detroit in 2018. Data Driven Detroit aggregated the dataset for a statewide analysis. Null values represent no Medicaid data or suppressed numbers (smaller than 6) to protect the information of individuals.

Graph and download economic data for Personal current transfer receipts: Government social benefits to persons: Medicaid (W729RC1A027NBEA) from 1966 to 2024 about transfers, social assistance, receipts, benefits, government, personal, GDP, and USA.

Trend in no health insurance coverage and Medicaid coverage by marital status, sex, and state Medicaid expansion status, American Community Survey 2010–16, N = 3,874,432 Medicaid eligible respondents.

Description: The demonstration of Direct Certification with Medicaid for Free and Reduced-Price Meals (DCM-F/RP) allows authorized States and school districts to use information from Medicaid to identify students eligible to receive meals under the National School Lunch Program (NSLP) and School Breakfast Program (SBP) for free or at a reduced price. District-level administrative records data on certification and NSLP and SBP participation were collected to evaluate the demonstration. The analysis sample includes 5,966 public, private, and charter school districts in the 15 States participating in the DCM-F/RP demonstration in school year (SY) 2019-20.Study date(s) and duration: Data were collected from each State child nutrition agency for SY 2019–2020, a baseline year, and any years in between (if applicable). States started the demonstration in different years, so the baseline year is the year before the demonstration began in that state: SY 2015–2016 for Florida, Massachusetts, Nebraska, Utah, Virginia, and West Virginia; SY 2016–2017 for California, Connecticut, Indiana, Iowa, Michigan, Texas, Washington, and Wisconsin; and SY 2017–2018 for Nevada.Study spatial scale: Fifteen States participated in the DCM-F/RP demonstration. Six began conducting DCM-F/RP statewide in SY 2016–2017 (Florida, Massachusetts, Nebraska, Utah, Virginia, and West Virginia), and one implemented DCM-F/RP in 14 districts that year and expanded to statewide implementation in SY 2017–2018 (California). Eight States began implementing DCM-F/RP in in SY 2017–2018 (Connecticut, Indiana, Iowa, Michigan, Nevada, Texas, Washington, and Wisconsin), although one State did not certify students through DCM-F/RP until SY 2018–2019 (Nevada).Level of true replication: UnknownSampling precision: No sampling was involved in the collection of this data.Level of subsampling: No sampling was involved in the collection of this data.Study design: None – Non-experimentalDescription of any data manipulation, modeling, or statistical analysis undertaken: This file contains a public use version of the data collected and analyzed for states in the DCM-F/RP demonstration in SY 2019-20, including both variables collected from the States and variables constructed for use in analysis. The file contains one observation for each of the districts in the analysis sample. Several types of edits were used to protect the confidentiality of respondents, including removing identifying information, rounding percentage variables to the nearest tenth, and rounding continuous variables representing numbers of schools, students, meals or dollars.Description of any gaps in the data or other limiting factors: Specific certification data elements were unavailable for some States or districts (namely, Iowa and Wisconsin did not provide data on reduced-price certifications). In addition, some districts—including notable subsets in Indiana and Virginia—were excluded from the analysis sample due to incomplete or erroneous administrative data.See the full Direct Certification with Medicaid for Free and Reduced-Price Meals (DCM-F/RP) Demonstration, SY 2019-20 report [https://www.fns.usda.gov/cn/usda-dcm-frp-demonstration] for a detailed explanation of the study’s limitations.Outcome measurement methods and equipment used: The effects of DCM-F/RP on certification, participation, and Federal reimbursement outcomes were estimated by comparing measures in the baseline year to the same measure in SY 2019–2020. A fixed effects model was used to control for changes in outcomes between years and to improve the precision of the estimates.Resources in this dataset:Resource Title: Dataset - Direct Certification with Medicaid for Free and Reduced-Price Meals (DCM-F/RP) Demonstration .File Name: DCM_FRP.csvResource Description: Dataset - Direct Certification with Medicaid for Free and Reduced-Price Meals (DCM-F/RP) Demonstration CSV FileResource Title: Codebook/Data Dictionary - Direct Certification with Medicaid for Free and Reduced-Price Meals (DCM-F/RP) Demonstration .File Name: DCM-FRP SY 2019-2020 Codebook.pdfResource Description: Codebook/Data Dictionary for the Dataset Direct Certification with Medicaid for Free and Reduced-Price Meals (DCM-F/RP) DemonstrationResource Title: User Guide - Direct Certification with Medicaid for Free and Reduced-Price Meals (DCM-F/RP) Demonstration .File Name: DCM-FRP SY 2019-2020 Public Use File User Guide REV.pdfResource Description: User Guide for the Data Direct Certification with Medicaid for Free and Reduced-Price Meals (DCM-F/RP) DemonstrationResource Title: SAS Stata R SPSS Data Sets - Direct Certification with Medicaid for Free and Reduced-Price Meals (DCM-F/RP) Demonstration .File Name: DCM_FRP.ZIPResource Description: SAS Stata R SPSS Data Sets for the Data Direct Certification with Medicaid for Free and Reduced-Price Meals (DCM-F/RP) Demonstration. These datasets are identical to the CSV and each other but provide multiple formats to meet user preference in statistical software.

The Health Insurance Marketplace Public Use Files contain data on health and dental plans offered to individuals and small businesses through the US Health Insurance Marketplace.

Exploration Ideas

To help get you started, here are some data exploration ideas:

• How do plan rates and benefits vary across states?
• How do plan benefits relate to plan rates?
• How do plan rates vary by age?
• How do plans vary across insurance network providers?

See this forum thread for more ideas, and post there if you want to add your own ideas or answer some of the open questions!

Data Description

This data was originally prepared and released by the Centers for Medicare & Medicaid Services (CMS). Please read the CMS Disclaimer-User Agreement before using this data.

Here, we've processed the data to facilitate analytics. This processed version has three components:

1. Original versions of the data

The original versions of the 2014, 2015, 2016 data are available in the "raw" directory of the download and "../input/raw" on Kaggle Scripts. Search for "dictionaries" on this page to find the data dictionaries describing the individual raw files.

2. Combined CSV files that contain

In the top level directory of the download ("../input" on Kaggle Scripts), there are six CSV files that contain the combined at across all years:

• BenefitsCostSharing.csv
• BusinessRules.csv
• Network.csv
• PlanAttributes.csv
• Rate.csv
• ServiceArea.csv

Additionally, there are two CSV files that facilitate joining data across years:

• Crosswalk2015.csv - joining 2014 and 2015 data
• Crosswalk2016.csv - joining 2015 and 2016 data

3. SQLite database

The "database.sqlite" file contains tables corresponding to each of the processed CSV files.

The code to create the processed version of this data is available on GitHub.

Access 118 report feeds sourced from the Centers for Medicare & Medicaid Services (CMS), with 25.8B+ rows of data dating back to 2007. Updated monthly, this dataset is ideal for tracking healthcare metrics over time, with cleaned and aligned attributes for easy ingestion and comprehensive analysis.

This dataset represents preliminary weekly hospital respiratory data and metrics aggregated to national and state/territory levels reported to CDC’s National Health Safety Network (NHSN) beginning August 2020. This dataset updates weekly on Wednesdays with preliminary data reported to NHSN for the previous reporting week (Sunday – Saturday).

Data for reporting dates through April 30, 2024 represent data reported during a previous mandated reporting period as specified by the HHS Secretary. Data for reporting dates May 1, 2024 – October 31, 2024 represent voluntarily reported data in the absence of a mandate. Data for reporting dates beginning November 1, 2024 represent data reported during a current mandated reporting period. All data and metrics capturing information on respiratory syncytial virus (RSV) were voluntarily reported until November 1, 2024. All data included in this dataset represent aggregated counts, and include metrics capturing information specific to hospital capacity, occupancy, hospitalizations, and new hospital admissions with corresponding metrics indicating reporting coverage for a given reporting week. NHSN monitors national and local trends in healthcare system stress and capacity for all acute care and critical access hospitals in the United States.

For more information on the reporting mandate per the Centers for Medicare and Medicaid Services (CMS) requirements, visit: Updates to the Condition of Participation (CoP) Requirements for Hospitals and Critical Access Hospitals (CAHs) To Report Acute Respiratory Illnesses.

For more information regarding NHSN’s collection of these data, including full reporting guidance, visit: NHSN Hospital Respiratory Data.

For data that is considered final for a given reporting week (Sunday – Saturday), and reflects that which is used in NHSN HRD dashboards for publication each Friday, visit: https://data.cdc.gov/Public-Health-Surveillance/Weekly-Hospital-Respiratory-Data-HRD-Metrics-by-Ju/ua7e-t2fy/about_data.

CDC coordinates weekly forecasts of hospitalization admissions based on this data set. More information about flu forecasting can be found at About Flu Forecasting | FluSight | CDC, and information about COVID-19 forecasting and other modeling analyses for the Respiratory Virus Season are available at CFA's Insights for Respiratory Virus Season | CFA | CDC.

Source: CDC National Healthcare Safety Network (NHSN).

• Data source description (updated November 15, 2024): As of October 9, 2024, Hospital Respiratory Data (HRD; formerly Respiratory Pathogen, Hospital Capacity, and Supply data or 'COVID-19 hospital data') are reported to HHS through CDC's National Healthcare Safety Network (NHSN) based on updated requirements from the Centers for Medicare and Medicaid Services (CMS). These data were voluntarily reported to NHSN May 1, 2024 until November 1, 2024, at which time CMS began requiring acute care and critical access hospitals to electronically report information via NHSN about COVID-19, influenza, and RSV, hospital bed census and capacity. Hospital bed capacity and occupancy data for all patients and for patients with COVID-19 or influenza for collection dates prior to May 1, 2024, represent data reported during a previously mandated reporting

Analysis of ‘Medicaid Opioid Prescribing Rates - by Geography’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/1fad91a7-803a-4b00-a788-746d0a998aac on 11 February 2022.

--- Dataset description provided by original source is as follows ---

The Medicaid Opioid Prescribing Rates by Geography dataset provides information on state comparisons of the number and percentage of Medicaid opioid prescriptions.

--- Original source retains full ownership of the source dataset ---