The Medicare Telehealth Trends dataset provides information about people with Medicare who used telehealth services between January 1, 2020 and June 30, 2024. The data were used to generate the Medicare Telehealth Trends Report.

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

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?

Content

The following dataset demonstrates the Medicare-enrolled MDPP suppliers from which eligible Medicare beneficiaries may be furnished MDPP services. If you receive your Medicare coverage via a Medicare Advantage plan, please consult your health plan to identify the specific MDPP suppliers that are available to you with no cost sharing

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 Philipp Mandler on Unsplash
Unsplash Images are distributed under a unique Unsplash License.

NCHS has linked data from various surveys with Medicare program enrollment and health care utilization and expenditure data from the Centers for Medicare & Medicaid Services (CMS). Linkage of the NCHS survey participants with the CMS Medicare data provides the opportunity to study changes in health status, health care utilization and costs, and prescription drug use among Medicare enrollees. Medicare is the federal health insurance program for people who are 65 or older, certain younger people with disabilities, and people with End-Stage Renal Disease.

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

2014-2019. This dataset is a de-identified summary table of vision and eye health data indicators from Medicare claims, stratified by all available combinations of age group, race/ethnicity, gender, and state. Medicare claims for VEHSS includes beneficiaries who were fully enrolled in Medicare Part B Fee-for-Service (FFS) for the duration of the year. Medicare claims provide a convenience sample that includes approximately 30 million individuals annually, which represents nearly 89% of the US population aged 65 and older and 3.3% of the US population younger than 65, including persons disabled due to blindness. Medicare data for VEHSS include Service Utilization and Medical Diagnoses indicators. Data were suppressed for de-identification to ensure protection of patient privacy. Data will be updated as it becomes available. Detailed information on VEHSS Medicare analyses can be found on the VEHSS Medicare webpage (cdc.gov/visionhealth/vehss/data/claims/medicare.html). Information on available Medicare claims data can be found on the ResDac website (www.resdac.org). The VEHSS Medicare dataset was last updated May 2023.

analyze the basic stand alone medicare claims public use files (bsapufs) with r and monetdb the centers for medicare and medicaid services (cms) took the plunge. the famous medicare 5% sample has been released to the public, free of charge. jfyi - medicare is the u.s. government program that provides health insurance to 50 million elderly and disabled americans. the basic stand alone medicare claims public use files (bsapufs) contain either person- or event-level data on inpatient stays, durable medical equipment purchases, prescription drug fills, hospice users, doctor visits, home health provision , outpatient hospital procedures, skilled nursing facility short-term residents, as well as aggregated statistics for medicare beneficiaries with chronic conditions and medicare beneficiaries living in nursing homes. oh sorry, there's one catch: they only provide sas scripts to analyze everything. cue the villian music. that bored old game of monopoly ends today. the initial release of the 2008 bsapufs was accompanied by some major fanfare in the world of health policy , a big win for government transparency. unfortunately, the final files that cleared the confidentiality hurdles are heavily de-identified and obfuscated. prime examples: none of the files can be linked to any other file. not across years, not across expenditure categories costs are rounded to the nearest fifth or tenth dollar at lower values, nearest thousandth at higher values ages are categorized into five year bands so these files are baldly inferior to the unsquelched, linkable data only available through an expensive formal application process. any researcher with a budget flush enough to afford a sas license (the only statistical software mentioned in the cms official documentation) can probably also cough up the money to buy the identifiable data through resdac (resdac, btw, rocks). soapbox: cms released free public data sets that could only be analyzed with a software package costing thousands of dollars. so even though the actual data sets were free, researchers still needed deep pock ets to buy sas. meanwhile, the unsquelched and therefore superior data sets are also available for many thousands of dollars. researchers with funding would (reasonably) just buy the better data. researchers without any financial resources - the target audience of free, public data - were left out in the cold. no wonder these bsapufs haven't been used much. that ends now. using r, monetdb, and the personal computer you already own (mine cost $700 in 2009), researchers can, for the first time, seriously analyze these medicare public use files without spending another dime. woah. plus hey guess what all you researcher fat-cats with your federal grant streams and your proprietary software licenses: r + monetdb runs one heckuva lot faster than sas. woah^2. dump your sas license water wings and learn how to swim. the scripts below require monetdb . click here for step-by-step instructions of how to install it on windows and click here for speed tests. vroom. since the bsapufs comprise 5% of the medicare population, ya generally need to multiply any counts or sums by twenty. although the individuals represented in these claims are randomly sampled, this data should not be treated like a complex survey sample, meaning that the creation of a survey object is unnecessary. most bsapufs generalize to either the total or fee-for-service medicare population, but each file is different so give the documentation a hard stare before that eureka moment. this new github repository contains three scripts: 2008 - download all csv files.R loop through and download every zip file hosted by cms unzip the contents of each zipped file to the working directory 2008 - import all csv files into monetdb.R create the batch (.bat) file needed to initiate the monet database in the f uture loop through each csv file in the current working directory and import them into the monet database create a well-documented block of code to re-initiate the monetdb server in the future 2008 - replicate cms publications.R initiate the same monetdb server instance, unsing the same well-documented block of code as above replicate nine sets of statistics found in data tables provided by cms < a href="https://github.com/ajdamico/usgsd/tree/master/Basic%20Stand%20Alone%20Medicare%20Claims%20Public%20Use%20Files">click here to view these three scripts for more detail about the basic stand alone medicare claims public use files (bsapufs), visit: the centers for medicare and medicaid's bsapuf homepage a joint academyhealth webinar given by the organizations that partnered to create these files - cms, impaq, norc notes: the replication script has oodles of easily-modified syntax and should be viewed for analysis examples. if you know the name of the data table you want to examine, you can quickly modify these general monetdb analysis examples too. just run sql queries - sas users, that's "proc...

This data set accompanies the Profile of the California Medicare Population chartbook, published by the Office of Medicare Innovation and Integration in February 2022, and available at (https://www.dhcs.ca.gov/services/Documents/OMII-Medicare-Databook-February-18-2022.pdf). The three data files in this data set were analyzed from federal administrative data (the Medicare Master Beneficiary Summary File) for beneficiary characteristics as of March 2021. These datasets include: Medicare enrollment, Medicare Advantage enrollment (and its converse fee-for-service Medicare enrollment), dual Medi-Cal eligibility and enrollment (and its converse Medicare-only enrollment), by county. Medicare Savings Program enrollees were considered Medicare-only and not dually enrolled in Medi-Cal. All Medicare Part C beneficiaries, including PACE, Cal MediConnect and Special Needs Plans, were considered to have Medicare Advantage.

DHCS partnered with The SCAN Foundation and ATI Advisory in 2021 and 2022 to develop a series of chartbooks that provide information about Medicare beneficiaries in California. This work is supported by a grant from The SCAN Foundation to advance a coordinated and easily navigated system of high-quality services for older adults that preserve dignity and independence. For more information, visit www.TheSCANFoundation.org.

The datasets include the monthly count of individuals who are enrolled in Medicare Savings Programs (MSP), by aid code and county. The counts reflect the total number of eligible individuals enrolled during the month. MSP help individuals with limited income and resources pay for some of the out-of-pocket costs for Medicare, including Medicare Part A and Part B premiums, deductibles, copayments, and coinsurance. There are four Medicare Savings Programs: Qualified Medicare Beneficiary (QMB), Specified Low Income Medicare Beneficiary (SLMB), Qualifying Individual (QI), and Qualified Working Disabled Individual (QWDI). Individuals who are eligible for QMB, SLMB, and QI also automatically qualify for the Low Income Subsidy (or “Extra Help”) program, which helps lower the cost of prescription drugs. Counties and aid codes with zero individuals enrolled during a reporting period are not included in the dataset.

Content

The hospital readmission rate PUF presents nation-wide information about inpatient hospital stays that occurred within 30 days of a previous inpatient hospital stay (readmissions) for Medicare fee-for-service beneficiaries. The readmission rate equals the number of inpatient hospital stays classified as readmissions divided by the number of index stays for a given month. Index stays include all inpatient hospital stays except those where the primary diagnosis was cancer treatment or rehabilitation. Readmissions include stays where a beneficiary was admitted as an inpatient within 30 days of the discharge date following a previous index stay, except cases where a stay is considered always planned or potentially planned. Planned readmissions include admissions for organ transplant surgery, maintenance chemotherapy/immunotherapy, and rehabilitation.

This dataset has several limitations. Readmissions rates are unadjusted for age, health status or other factors. In addition, this dataset reports data for some months where claims are not yet final. Data published for the most recent six months is preliminary and subject to change. Final data will be published as they become available, although the difference between preliminary and final readmission rates for a given month is likely to be less than 0.1 percentage point.

Data Source: The primary data source for these data is the CMS Chronic Condition Data Warehouse (CCW), a database with 100% of Medicare enrollment and fee-for-service claims data. For complete information regarding data in the CCW, visit http://ccwdata.org/index.php. Study Population: Medicare fee-for-service beneficiaries with inpatient hospital stays.

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 Justyn Warner on Unsplash
Unsplash Images are distributed under a unique Unsplash License.

This dataset is distributed under NA

Verify the accuracy of SSNs of all individual Medicare providers, owners, managing/directing employees, authorized representatives, ambulance service medical directors, ambulance crew members, technicians, chain organization administrators, Independent Diagnostic Test Facility (IDTF), supervising/directing physicians, and IDTF interpretation service providers. Also included in this Agreement are individual health care providers who apply for a National Provider Identification Number (NPI).

Abstract

The MarketScan Medicare Supplemental Database provides detailed cost, use and outcomes data for healthcare services performed in both inpatient and outpatient settings.

It Include Medicare Supplemental records for all years, and Medicare Advantage records starting in 2020. This page also contains the MarketScan Medicare Lab Database starting in 2018.

Starting in 2026, there will be a data access fee for using the full dataset. Please refer to the 'Usage Notes' section of this page for more information.

Methodology

MarketScan Research Databases are a family of data sets that fully integrate many types of data for healthcare research, including:

• De-identified records of more than 250 million patients (medical, drug and dental)

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• Laboratory results

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• Hospital discharges

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The MarketScan Databases track millions of patients throughout the healthcare system. The data are contributed by large employers, managed care organizations, hospitals, EMR providers and Medicare.

Usage

This page contains the MarketScan Medicare Database.

We also have the following on other pages:

• The MarketScan Commercial Database
• The MarketScan Dental Database
• The MarketScan Benefit Plan Design data
• MarketScan Redbook (The MarketScan Code Reference Book)

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**Starting in 2026, there will be a data access fee for using the full dataset **

(though the 1% sample will remain free to use). The pricing structure and other

**relevant information can be found in this **FAQ Sheet.

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

Data Documentation

Data access is required to view this section.

Section 2

Metadata access is required to view this section.

Section 3

Metadata access is required to view this section.

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

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 from: https://data.medicare.gov/Hospital-Compare/Payment-and-value-of-care-Hospital/c7us-v4mf More information coming soon!

Context

There's a story behind every dataset and here's your opportunity to share yours.

Content

What's inside is more than just rows and columns. Make it easy for others to get started by describing how you acquired the data and what time period it represents, too.

Acknowledgements

We wouldn't be here without the help of others. If you owe any attributions or thanks, include them here along with any citations of past research.

Inspiration

Your data will be in front of the world's largest data science community. What questions do you want to see answered?

The dataset contains information about the prevalence of chronic conditions among Original Medicare beneficiaries as well as about the spending and co-occurring conditions for those with each condition. The data are available for California and for the rest of the United States, overall and by demographic and geographic groups. Additionally, the data are available for each of 19 California geographic regions overall and by demographic and geographic groups. The data represent Medicare beneficiaries who are in the Original Medicare program. Medicare offers health care coverage for older adults and certain individuals with disabilities. The Original Medicare program is Parts A and B of Medicare, administered by the U.S. Centers for Medicare & Medicaid Services. The analysis excludes enrollees of the Medicare Advantage program, administered by private insurers, because Medicare Advantage data are incomplete.

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).

The Medicaid Managed Care Enrollment Report profiles enrollment statistics on Medicaid managed care programs on a plan-specific level. The managed care enrollment statistics include enrollees receiving comprehensive benefits and limited benefits and are point-in-time counts.

1. Because Medicaid beneficiaries may be enrolled concurrently in more than one type of managed care program (e.g., a Comprehensive MCO and a BHO), users should not sum enrollment across all program types, since the total would count individuals more than once and, in some states, exceed the actual number of Medicaid enrollees.

2. Comprehensive MCOs cover acute, primary, and specialty medical care services; they may also cover behavioral health, long-term services and supports, and other benefits in some states. Limited benefit managed care programs, including PCCM, MLTSS only, BHO, Dental, Transportation, and Other cover a narrower set of services.

3. The “Total Medicaid Enrollees” column represents an unduplicated count of all beneficiaries in FFS and any type of managed care, including Medicaid-only and dually eligible individuals receiving full Medicaid benefits or Medicaid cost sharing.

"--" indicates states that do not operate programs of a given type. 0 signifies that a state operated a program of this type in 2014, but it ended before July 1, 2014, or began after that date.

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.