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?

Big “p” policy changes at the state and federal level are certainly important to health equity, such as eligibility for and generosity of Medicaid benefits. Medicaid expansion has significantly expanded the number of people who are eligible for Medicaid and the creation of the health insurance exchanges (Marketplace) under the Affordable Care Act created a very visible avenue through which people can learn that they are eligible. Although many applications are now submitted online, physical access to state, county, and tribal government Medicaid offices still plays a critical role in understanding eligibility, getting help in applying, and navigating required documentation for both initial enrollment and redetermination of eligibility. However, as more government functions have moved online, in-person office locations and/or staff may have been cut to reduce costs, and gentrification has shifted where minoritized, marginalized, and/or low-income populations live, it is unclear if this key local connection point between residents and Medicaid has been maintained. Our objective was to identify and geocode all Medicaid offices in the United States for pairing with other spatial data (e.g., demographics, Medicaid participation, health care use, health outcomes) to investigate policy-relevant research questions. Three coders identified Medicaid office addresses in all 50 states and the District of Columbia by searching state government websites (e.g., Department of Health and Human Services or analogous state agency) during late 2021 and early 2022 for the appropriate Medicaid agency and its office locations, which were then reviewed for accuracy by a fourth coder. Our corpus of Medicaid office addresses was then geocoded using the Census Geocoder from the US Census Bureau (https://geocoding.geo.census.gov/geocoder/) with unresolved addresses investigated and/or manually geocoded using Google Maps. The corpus was updated in August through December 2023 following the end of the COVID-19 public health emergency by a fifth coder as several states closed and/or combined offices during the pandemic. After deduplication (e.g., where multiple counties share a single office) and removal of mailing addresses (e.g., PO Boxes), our dataset includes 3,027 Medicaid office locations. 1 (December 19, 2023) – original version 2 (January 25, 2024) – added related publication (Data in Brief), corrected two records that were missing negative signs in longitude 3 (February 6, 2024) – corrected latitude and longitude for one office (1340 State Route 9, Lake George, NY 12845) 4 (March 4, 2024) – added one office for Vermont after contacting relevant state agency (280 State Road, Waterbury, VT 05671)

Abstract (en): In January 2013, the Urban Institute launched the Health Reform Monitoring Survey (HRMS), a quarterly survey of the nonelderly population, to explore the value of cutting-edge, Internet-based survey methods to monitor the Affordable Care Act (ACA) before data from federal government surveys are available. Topics covered by the second round of the survey (second quarter 2013) include self-reported health status, type of and satisfaction with current health insurance coverage, access to and use of health care, health care affordability, whether the respondent considered purchasing or tried to purchase health insurance coverage directly from an insurance company, whether the respondent considered obtaining coverage through Medicaid or other government sponsored assistance plan based on income or disability, sources of information about health insurance, and the importance of various criteria in choosing a health insurance plan. Additional information collected by the survey includes age, education, race, Hispanic origin, gender, income, household size, housing type, marital status, employment status, number of employees at place of work, United States citizenship, smoking, internet access, home ownership, body mass index, sexual orientation, and whether the respondent reported an ambulatory care sensitive condition or a mental or behavioral condition. ICPSR data undergo a confidentiality review and are altered when necessary to limit the risk of disclosure. ICPSR also routinely creates ready-to-go data files along with setups in the major statistical software formats as well as standard codebooks to accompany the data. In addition to these procedures, ICPSR performed the following processing steps for this data collection: Checked for undocumented or out-of-range codes.. Response Rates: The HRMS response rate is roughly five percent each quarter. Datasets:DS0: Study-Level FilesDS1: Public-use DataDS2: Restricted-use Data Household population aged 18-64. Each quarterly HRMS sample is drawn from the KnowledgePanel, a probability-based, nationally representative Internet panel maintained by GfK Custom Research. Beginning with the second quarter of 2013, the HRMS includes oversamples of adults with family incomes at or below 138 percent of the federal poverty level and adults from selected state groups based on (1) the potential for gains in insurance coverage in the state under the ACA as estimated by the Urban Institute's microsimulation model and (2) states of specific interest to the HRMS funders. Additional funders have supported oversamples of adults from individual states or subgroups of interest (including children). However, ICPSR received data only for the adults in the general national sample and the income and state group oversamples. 2019-07-10 Variable Q7_F was removed from public dataset. An updated codebook excluding this variable was provided for public use. Current release will feature DS1 as public-use data only and DS2 as restricted-use data. Previous release included both public and restricted versions of DS1. Study title updated to include geographic information.2017-06-20 The principal investigators added a new weight variable to the data file and the technical documentation was updated accordingly.2015-03-23 The principal investigators deleted the multiple imputation variables _1_famsize, _2_famsize, _3_famsize, _4_famsize and _5_famsize. ICPSR revised the codebook accordingly and added to the collection a plain text version of the data with a Stata setup and record layout file. Funding institution(s): Ford Foundation. Urban Institute. Robert Wood Johnson Foundation (71390). web-based survey

Medically Unlikely Edits (MUEs) define for each HCPCS / CPT code the maximum units of service (UOS) that a provider would report under most circumstances for a single beneficiary on a single date of service.

Practitioner services also refers to ambulatory surgical centers.
DME refers to provider claims for durable medical equipment.

The CMS National Correct Coding Initiative (NCCI) promotes national correct coding methodologies and reduces improper coding which may result in inappropriate payments of Medicare Part B claims and Medicaid claims. NCCI procedure-to-procedure (PTP) edits define pairs of Healthcare Common Procedure Coding System (HCPCS)/Current Procedural Terminology (CPT) codes that should not be reported together for a variety of reasons. The purpose of the PTP edits is to prevent improper payments when incorrect code combinations are reported. The edits in this dataset are active for the dates indicated within. This file should NOT be used by state Medicaid programs as their edit file. Current Procedural Terminology (CPT) codes, descriptions and other data only are copyright 2017 American Medical Association. All rights reserved. CPT® is a registered trademark of the American Medical Association. Applicable FARS\DFARS Restrictions Apply to Government Use. Fee schedules, relative value units, conversion factors and/or related components are not assigned by the AMA, are not part of CPT, and the AMA is not recommending their use. The AMA does not directly or indirectly practice medicine or dispense medical services. The AMA assumes no liability for the data contained or not contained herein.

For more information, visit https://www.medicaid.gov/medicaid/program-integrity/ncci/index.html.

Abstract (en): In January 2013, the Urban Institute launched the Health Reform Monitoring Survey (HRMS), a survey of the nonelderly population, to explore the value of cutting-edge, Internet-based survey methods to monitor the Affordable Care Act (ACA) before data from federal government surveys are available. Topics covered by the 16th round of the survey (third quarter 2018) include self-reported health status, health insurance coverage, access to and use of health care, out-of-pocket health care costs, health care affordability, work experience, awareness of Medicaid work requirements, experiences with health care and social service providers, and health plan choice. Additional information collected by the survey includes age, gender, sexual orientation, marital status, education, race, Hispanic origin, United States citizenship, housing type, home ownership, internet access, income, employment status, and employer size. This study was conducted to provide information on health insurance coverage, access to and use of health care, health care affordability, and self-reported health status, as well as timely data on important implementation issues under the Affordable Care Act (ACA). The Health Reform Monitoring Survey (HRMS) provides data on health insurance coverage, access to and use of health care, health care affordability, and self-reported health status. Beginning in the second quarter of 2013, each round of the HRMS also contains topical questions focusing on timely ACA policy issues. In the first quarter of 2015, the HRMS shifted from a quarterly fielding schedule to a semiannual schedule. The variables include original survey questions, household demographic profile data, and constructed variables which can be used to link panel members who participated in multiple rounds. ICPSR data undergo a confidentiality review and are altered when necessary to limit the risk of disclosure. ICPSR also routinely creates ready-to-go data files along with setups in the major statistical software formats as well as standard codebooks to accompany the data. In addition to these procedures, ICPSR performed the following processing steps for this data collection: Created variable labels and/or value labels.; Created online analysis version with question text.; Performed recodes and/or calculated derived variables.; Checked for undocumented or out-of-range codes.. Response Rates: The HRMS response rate is roughly five percent each round. Datasets:DS0: Study-Level FilesDS1: Public-Use DataDS2: Restricted-Use Data Household population aged 18-64 Smallest Geographic Unit: Census region For each HRMS round a stratified random sample of adults ages 18-64 is drawn from the KnowledgePanel, a probability-based, nationally represented Internet panel maintained by Ipsos. The approximately 55,000 adults in the panel include households with and without Internet access. Panel members are recruited from an address-based sample frame derived from the United States Postal Service Delivery Sequence File, which covers 97 percent of United States households. The HRMS sample includes a random sample of approximately 9,500 nonelderly adults per quarter, including oversamples of adults with family incomes at or below 138 percent of the federal poverty line. Additional funders have supported oversamples of adults from individual states or subgroups of interest. However, the data file only includes data for adults in the general national sample and the income oversample. web-based survey

The Centers for Medicare & Medicaid Services (CMS) has prepared a public data set, the Medicare Provider Utilization and Payment Data: Part D Prescriber Public Use File (PUF), with information on prescription drugs prescribed by individual physicians and other health care providers and paid for under the Medicare Part D Prescription Drug Program. The Part D Prescriber PUF is based on information from CMS’s Chronic Conditions Data Warehouse, which contains Prescription Drug Event records submitted by Medicare Advantage Prescription Drug (MAPD) plans and by stand-alone Prescription Drug Plans (PDP). The dataset identifies providers by their National Provider Identifier (NPI) and the specific prescriptions that were dispensed at their direction, listed by brand name (if applicable) and generic name. For each prescriber and drug, the dataset includes the total number of prescriptions that were dispensed, which include original prescriptions and any refills, and the total drug cost. The total drug cost includes the ingredient cost of the medication, dispensing fees, sales tax, and any applicable administration fees and is based on the amount paid by the Part D plan, Medicare beneficiary, government subsidies, and any other third-party payers. Although the Part D Prescriber PUF has a wealth of information on payment and utilization for Medicare Part D prescriptions, the dataset has a number of limitations. Of particular importance is the fact that the data may not be representative of a physician’s entire practice or all of Medicare as it only includes information on beneficiaries enrolled in the Medicare Part D prescription drug program (i.e., approximately two-thirds of all Medicare beneficiaries). In addition, the data are not intended to indicate the quality of care provided. For additional limitations, please review the methodology document in the About tab.

The CMS National Correct Coding Initiative (NCCI) promotes national correct coding methodologies and reduces improper coding which may result in inappropriate payments of Medicare Part B claims and Medicaid claims.

NCCI procedure-to-procedure (PTP) edits define pairs of Healthcare Common Procedure Coding System (HCPCS)/Current Procedural Terminology (CPT) codes that should not be reported together for a variety of reasons. The purpose of the PTP edits is to prevent improper payments when incorrect code combinations are reported.

Practitioner services also refers to ambulatory surgical centers.
DME refers to provider claims for durable medical equipment.

The CMS National Correct Coding Initiative (NCCI) promotes national correct coding methodologies and reduces improper coding which may result in inappropriate payments of Medicare Part B claims and Medicaid claims. NCCI procedure-to-procedure (PTP) edits define pairs of Healthcare Common Procedure Coding System (HCPCS)/Current Procedural Terminology (CPT) codes that should not be reported together for a variety of reasons. The purpose of the PTP edits is to prevent improper payments when incorrect code combinations are reported. The edits in this dataset are active for the dates indicated within. This file should NOT be used by state Medicaid programs as their edit file. Current Procedural Terminology (CPT) codes, descriptions and other data only are copyright 2017 American Medical Association. All rights reserved. CPT® is a registered trademark of the American Medical Association. Applicable FARS\DFARS Restrictions Apply to Government Use. Fee schedules, relative value units, conversion factors and/or related components are not assigned by the AMA, are not part of CPT, and the AMA is not recommending their use. The AMA does not directly or indirectly practice medicine or dispense medical services. The AMA assumes no liability for the data contained or not contained herein.

For more information, visit https://www.medicaid.gov/medicaid/program-integrity/ncci/index.html.