This layer contains 2010-2014 American Community Survey (ACS) 5-year data, and contains estimates and margins of error. The layer shows health insurance coverage sex and race by age group. This is shown by tract, county, and state boundaries. There are also additional calculated attributes related to this topic, which can be mapped or used within analysis. Sums may add to more than the total, as people can be in multiple race groups (for example, Hispanic and Black). Later vintages of this layer have a different age group for children that includes age 18. This layer is symbolized to show the percent of population with no health insurance coverage. To see the full list of attributes available in this service, go to the "Data" tab, and choose "Fields" at the top right. Vintage: 2010-2014ACS Table(s): B27010, C27001B, C27001C, C27001D, C27001E, C27001F, C27001G, C27001H, C27001I (Not all lines of these tables are available in this layer.)Data downloaded from: Census Bureau's API for American Community Survey Date of API call: November 28, 2020National Figures: data.census.govThe United States Census Bureau's American Community Survey (ACS):About the SurveyGeography & ACSTechnical DocumentationNews & UpdatesThis ready-to-use layer can be used within ArcGIS Pro, ArcGIS Online, its configurable apps, dashboards, Story Maps, custom apps, and mobile apps. Data can also be exported for offline workflows. For more information about ACS layers, visit the FAQ. Please cite the Census and ACS when using this data.Data Note from the Census:Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see Accuracy of the Data). The effect of nonsampling error is not represented in these tables.Data Processing Notes:This layer has associated layers containing the most recent ACS data available by the U.S. Census Bureau. Click here to learn more about ACS data releases and click here for the associated boundaries layer. The reason this data is 5+ years different from the most recent vintage is due to the overlapping of survey years. It is recommended by the U.S. Census Bureau to compare non-overlapping datasets.Boundaries come from the US Census TIGER geodatabases. Boundary vintage (2014) appropriately matches the data vintage as specified by the Census. These are Census boundaries with water and/or coastlines clipped for cartographic purposes. For census tracts, the water cutouts are derived from a subset of the 2010 AWATER (Area Water) boundaries offered by TIGER. For state and county boundaries, the water and coastlines are derived from the coastlines of the 500k TIGER Cartographic Boundary Shapefiles. The original AWATER and ALAND fields are still available as attributes within the data table (units are square meters). The States layer contains 52 records - all US states, Washington D.C., and Puerto RicoCensus tracts with no population that occur in areas of water, such as oceans, are removed from this data service (Census Tracts beginning with 99).Percentages and derived counts, and associated margins of error, are calculated values (that can be identified by the "_calc_" stub in the field name), and abide by the specifications defined by the American Community Survey.Field alias names were created based on the Table Shells file available from the American Community Survey Summary File Documentation page.Negative values (e.g., -4444...) have been set to null, with the exception of -5555... which has been set to zero. These negative values exist in the raw API data to indicate the following situations:The margin of error column indicates that either no sample observations or too few sample observations were available to compute a standard error and thus the margin of error. A statistical test is not appropriate.Either no sample observations or too few sample observations were available to compute an estimate, or a ratio of medians cannot be calculated because one or both of the median estimates falls in the lowest interval or upper interval of an open-ended distribution.The median falls in the lowest interval of an open-ended distribution, or in the upper interval of an open-ended distribution. A statistical test is not appropriate.The estimate is controlled. A statistical test for sampling variability is not appropriate.The data for this geographic area cannot be displayed because the number of sample cases is too small.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
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.
This layer shows Health Insurance Coverage. This is shown by state boundaries. This service is updated annually to contain the most currently released American Community Survey (ACS) 5-year data, and contains
estimates and margins of error. There are also additional calculated attributes related to this topic, which can be mapped or used within analysis.
This layer is symbolized to show percent uninsured. To see the full list of attributes available in this service, go to the "Data" tab, and choose "Fields"
at the top right. Current Vintage: 2015-2019ACS Table(s): B27010, DP03Data downloaded from: Census Bureau's API for American Community Survey
Date of API call: February 10, 2021National Figures: data.census.gov
The United States Census Bureau's American Community Survey (ACS):
About the SurveyGeography & ACSTechnical Documentation
News & UpdatesThis ready-to-use layer can be used within ArcGIS Pro, ArcGIS Online,
its configurable apps, dashboards, Story Maps, custom apps, and mobile apps. Data can also be exported for offline workflows. Please cite the Census and ACS when
using this data.Data Note from the
Census:Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate
arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can
be interpreted as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error
(the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a
discussion of nonsampling variability, see Accuracy of the Data). The effect of nonsampling error is not represented in these tables.
Data Processing Notes:
Boundaries come from the US Census TIGER geodatabases. Boundaries are updated at the same time as the data updates
(annually), and the boundary vintage appropriately matches the data vintage as specified by the Census. These are Census boundaries with water and/or
coastlines clipped for cartographic purposes. For census tracts, the water cutouts are derived from a subset of the 2010 AWATER (Area Water) boundaries offered by TIGER. For
state and county boundaries, the water and coastlines are derived from the coastlines of the 500k TIGER Cartographic Boundary Shapefiles. The original AWATER and ALAND fields are still available as attributes
within the data table (units are square meters). The States layer contains 52 records - all US states, Washington D.C., and Puerto RicoCensus tracts with no
population that occur in areas of water, such as oceans, are removed from this data service (Census Tracts beginning with 99).Percentages and derived counts, and associated
margins of error, are calculated values (that can be identified by the "_calc_" stub in the field name), and abide by the specifications
defined by the American Community Survey.Field alias names were created
based on the Table Shells file available from the
American Community Survey Summary File Documentation page.Margin of error (MOE) values of -555555555 in the API
(or "*****" (five asterisks) on data.census.gov) are displayed as 0 in this dataset. The estimates associated with these MOEs have been controlled to independent
counts in the ACS weighting and have zero sampling error. So, the MOEs are effectively zeroes, and are treated as zeroes in MOE calculations. Other negative values on the API,
such as -222222222, -666666666, -888888888, and -999999999, all represent estimates or MOEs that can't be calculated or can't be published, usually due to small sample sizes.
All of these are rendered in this dataset as null (blank) values.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Triple differences linear probability model for no health insurance coverage by marital status, sex, age, and state Medicaid expansion status, American Community Survey 2010–16.
analyze the current population survey (cps) annual social and economic supplement (asec) with r the annual march cps-asec has been supplying the statistics for the census bureau's report on income, poverty, and health insurance coverage since 1948. wow. the us census bureau and the bureau of labor statistics ( bls) tag-team on this one. until the american community survey (acs) hit the scene in the early aughts (2000s), the current population survey had the largest sample size of all the annual general demographic data sets outside of the decennial census - about two hundred thousand respondents. this provides enough sample to conduct state- and a few large metro area-level analyses. your sample size will vanish if you start investigating subgroups b y state - consider pooling multiple years. county-level is a no-no. despite the american community survey's larger size, the cps-asec contains many more variables related to employment, sources of income, and insurance - and can be trended back to harry truman's presidency. aside from questions specifically asked about an annual experience (like income), many of the questions in this march data set should be t reated as point-in-time statistics. cps-asec generalizes to the united states non-institutional, non-active duty military population. the national bureau of economic research (nber) provides sas, spss, and stata importation scripts to create a rectangular file (rectangular data means only person-level records; household- and family-level information gets attached to each person). to import these files into r, the parse.SAScii function uses nber's sas code to determine how to import the fixed-width file, then RSQLite to put everything into a schnazzy database. you can try reading through the nber march 2012 sas importation code yourself, but it's a bit of a proc freak show. this new github repository contains three scripts: 2005-2012 asec - download all microdata.R down load the fixed-width file containing household, family, and person records import by separating this file into three tables, then merge 'em together at the person-level download the fixed-width file containing the person-level replicate weights merge the rectangular person-level file with the replicate weights, then store it in a sql database create a new variable - one - in the data table 2012 asec - analysis examples.R connect to the sql database created by the 'download all microdata' progr am create the complex sample survey object, using the replicate weights perform a boatload of analysis examples replicate census estimates - 2011.R connect to the sql database created by the 'download all microdata' program create the complex sample survey object, using the replicate weights match the sas output shown in the png file below 2011 asec replicate weight sas output.png statistic and standard error generated from the replicate-weighted example sas script contained in this census-provided person replicate weights usage instructions document. click here to view these three scripts for more detail about the current population survey - annual social and economic supplement (cps-asec), visit: the census bureau's current population survey page the bureau of labor statistics' current population survey page the current population survey's wikipedia article notes: interviews are conducted in march about experiences during the previous year. the file labeled 2012 includes information (income, work experience, health insurance) pertaining to 2011. when you use the current populat ion survey to talk about america, subract a year from the data file name. as of the 2010 file (the interview focusing on america during 2009), the cps-asec contains exciting new medical out-of-pocket spending variables most useful for supplemental (medical spending-adjusted) poverty research. confidential to sas, spss, stata, sudaan users: why are you still rubbing two sticks together after we've invented the butane lighter? time to transition to r. :D
-This data is a compilation of the CMS Medicare Part B National Summary Data for CPT/HCPCS Medicine Codes 90281-99xx for 2000-2022. - The information in Part B National Summary Data Files is limited to Medicare Fee-For- Service (FFS) Part B Physician/Supplier data. It does not include information on physician/supplier services for beneficiaries in the managed care portion of the program (Medicare Advantage). -Items/columns include: year, HCPCS/CPT, total annual allowed services, total annual allowed charges, and total annual allowed payment. - These are national annual aggregates. - Note that, per CMS, fields labeled “N/A” mean that the data cannot be disclosed due to Privacy rules. Cell sizes less than 11 have been screened for privacy and replaced with N/A. A zero indicates there were no services or payments rendered for a particular code. - The .csv and .xlsx files hold the same data, just in different formats. - CPT only copyright 2000-2022 American Medical Association. All rights reserved.
Allowed Services: A count of the number of services performed for a procedure.
Allowed Charges: The amount Medicare determines to be reasonable payment for a provider or service covered under Part B. This includes the coinsurance and deductible amounts.
Description: The category corresponding to the HCPCS code, for example: Evaluation and Management, Anesthesia, Dental Services, Pathology/Lab Tests, Chemotherapy Drugs, Medicine, etc
HCPCS (Healthcare Common Procedure Coding System): The HCPCS is a coding system for all services performed by a physician or supplier. It is based on the American Medical Association Physicians Current Procedural Terminology (CPT) codes and is augmented with codes for physician and non-physician services (such as ambulance and durable medical equipment (DME), which are not included in CPTs.
Modifiers: Modifiers denote that a certain procedure/service has been altered by a particular circumstance, but not changed in its definition, therefore the same code is used and a modifier is added to denote what has been altered.
Payment: In the Original Medicare Plan, this is the amount a doctor or supplier that accepts assignment can be paid. It includes what Medicare pays and any deductible, coinsurance, or copayment that the beneficiary must pay. It may be less than the actual amount a doctor or supplier charges.
Additional details can be found in the Medicare Part B National Summary Data Read Me files: file:///C:/Users/sybil/AppData/Local/Temp/3dce003b-ea02-4b37-aaae-c4ef3e6f43a9_PartBNational2010.zip.3a9/PartBNationalSummaryReadmeFile2010.pdf
CMS has no responsibility for the data after it has been converted, processed or otherwise altered. Data that has been manipulated or reprocessed by the user is the responsibility of the user. The user may not present data that has been altered in any way as CMS data. Any alteration of the original data, including conversion to other media or other data formats, is the responsibility of the requestor. Cell sizes less than 11 have been screened for privacy and replaced with N/A. A zero indicates there were no services or payments rendered for a particular code.
*End User Agreement:
License for Use of Current Procedural Terminology, ANY Edition ("CPT®")
CPT codes, descriptions and other data only are copyright 1995 - 2023 American Medical Association. All rights reserved. CPT is a registered trademark of the American Medical Association (AMA).
You, your employees and agents are authorized to use CPT only as contained in the following authorized materials of Centers for Medicare and Medicaid Services (CMS) internally within your organization within the United States for the sole use by yourself, employees and agents. Use is limited to use in Medicare, Medicaid or other programs administered by CMS. You agree to take all necessary steps to insure that your employees and agents abide by the terms of this agreement.
Any use not authorized herein is prohibited, including by way of illustration and not by way of limitation, making copies of CPT for resale and/or license, transferring copies of CPT to any party not bound by this agreement, creating any modified or derivative work of CPT, or making any commercial use of CPT. License to use CPT for any use not authorized herein must be obtained through the AMA, CPT Intellectual Property Services, AMA Plaza, 330 N. Wabash Ave., Suite 39300, Chicago, IL 60611-5885. Applications are available at the AMA Web site, http://www.ama-assn.org/go/cpt. Applicable FARSDFARS Restrictions Apply to Government Use
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This layer contains 2010-2014 American Community Survey (ACS) 5-year data, and contains estimates and margins of error. The layer shows health insurance coverage sex and race by age group. This is shown by tract, county, and state boundaries. There are also additional calculated attributes related to this topic, which can be mapped or used within analysis. Sums may add to more than the total, as people can be in multiple race groups (for example, Hispanic and Black). Later vintages of this layer have a different age group for children that includes age 18. This layer is symbolized to show the percent of population with no health insurance coverage. To see the full list of attributes available in this service, go to the "Data" tab, and choose "Fields" at the top right. Vintage: 2010-2014ACS Table(s): B27010, C27001B, C27001C, C27001D, C27001E, C27001F, C27001G, C27001H, C27001I (Not all lines of these tables are available in this layer.)Data downloaded from: Census Bureau's API for American Community Survey Date of API call: November 28, 2020National Figures: data.census.govThe United States Census Bureau's American Community Survey (ACS):About the SurveyGeography & ACSTechnical DocumentationNews & UpdatesThis ready-to-use layer can be used within ArcGIS Pro, ArcGIS Online, its configurable apps, dashboards, Story Maps, custom apps, and mobile apps. Data can also be exported for offline workflows. For more information about ACS layers, visit the FAQ. Please cite the Census and ACS when using this data.Data Note from the Census:Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see Accuracy of the Data). The effect of nonsampling error is not represented in these tables.Data Processing Notes:This layer has associated layers containing the most recent ACS data available by the U.S. Census Bureau. Click here to learn more about ACS data releases and click here for the associated boundaries layer. The reason this data is 5+ years different from the most recent vintage is due to the overlapping of survey years. It is recommended by the U.S. Census Bureau to compare non-overlapping datasets.Boundaries come from the US Census TIGER geodatabases. Boundary vintage (2014) appropriately matches the data vintage as specified by the Census. These are Census boundaries with water and/or coastlines clipped for cartographic purposes. For census tracts, the water cutouts are derived from a subset of the 2010 AWATER (Area Water) boundaries offered by TIGER. For state and county boundaries, the water and coastlines are derived from the coastlines of the 500k TIGER Cartographic Boundary Shapefiles. The original AWATER and ALAND fields are still available as attributes within the data table (units are square meters). The States layer contains 52 records - all US states, Washington D.C., and Puerto RicoCensus tracts with no population that occur in areas of water, such as oceans, are removed from this data service (Census Tracts beginning with 99).Percentages and derived counts, and associated margins of error, are calculated values (that can be identified by the "_calc_" stub in the field name), and abide by the specifications defined by the American Community Survey.Field alias names were created based on the Table Shells file available from the American Community Survey Summary File Documentation page.Negative values (e.g., -4444...) have been set to null, with the exception of -5555... which has been set to zero. These negative values exist in the raw API data to indicate the following situations:The margin of error column indicates that either no sample observations or too few sample observations were available to compute a standard error and thus the margin of error. A statistical test is not appropriate.Either no sample observations or too few sample observations were available to compute an estimate, or a ratio of medians cannot be calculated because one or both of the median estimates falls in the lowest interval or upper interval of an open-ended distribution.The median falls in the lowest interval of an open-ended distribution, or in the upper interval of an open-ended distribution. A statistical test is not appropriate.The estimate is controlled. A statistical test for sampling variability is not appropriate.The data for this geographic area cannot be displayed because the number of sample cases is too small.