In 2022, registered nurses in the United States were predominantly white, accounting for over ** percent of all registered nurses. According to the U.S. census, however, roughly ** percent of the U.S. population are white.

In 2022, of the 458,590 nursing assistants in nursing homes in the United States, roughly four in ten were white. Meanwhile, Black or African American accounted for another 37 percent. Nursing assistants were therefore made up of predominantly racial minorities.

This graph shows the distribution of nursing home residents in the U.S. in 2014, by ethnicity. In the year 2014, around 78 percent of all nursing home residents were white, while 5.3 percent were Hispanic or Latino.

associate-degree bachelor-s-degree bhw bureau-of-health community-health doctorate-degree education eligibility ethnic-background financed general-information health-care-providers health-workforce hrsa master-s-degree national-center-for-health-workforce-analysis national-sample-survey-of-registered-nurses nchwa nssrs nurse nurse-anesthetist nurse-midwife nurse-practitioner nurses racial-background

We analyse job grading within the UK National Health Service nursing profession, using 1994 survey data. We start from the ordered probit model, for which we develop and apply appropriate specification tests. Threshold constancy and covariate exogeneity are rejected, with important consequences for estimates of the influence of gender, ethnicity, training and career interruptions. We find little evidence of disadvantage for females relative to males, but significant differences in speed of promotion between ethnic groups, implying non-negligible differences in lifetime earnings.

This dataset tracks annual two or more races student percentage from 2011 to 2015 for Hphs Nursing And Health Sciences Academy vs. Connecticut and Hartford School District

In 2020, nursing home residents in the United States were mostly white, non-Hispanic, female and over the age of 85 years. The gender distribution was roughly six women to four men. Despite a third of residents being over 85 years, some 18 percent were under the age of 65 years.

This dataset tracks annual two or more races student percentage from 2021 to 2022 for Marie Curie High School-nursing vs. New York and New York City Geographic District #10 School District

This dataset provides information gathered in 1973 from facilities providing nursing care to their residents. Nursing homes, their staff, and residents were surveyed. Data from the facility questionnaire include services offered, type of ownership, total number of beds, total number of residents, whether facility participated in Medicare and Medicaid, 1972 admissions, discharges, and deaths, number of patients receiving specific services and treatments, number of physicians, staff hours and payroll, and expenses. The resident questionnaire generated information on each resident's age, race, marital status, date of admission, prior living arrangements, reason for admission, diagnosis, chronic conditions, services received, medication, assistance with daily activities, frequency of doctor visits, and source of payment. The staff questionnaire data include sex, race, occupation, hours worked per week, salary, and education.

As of 2019, the distribution of selected healthcare professionals in the United State by race and ethnicity revealed deep disparities. During that year, the vast majority of healthcare workers in the US identified as white. For instance, only 11 percent of registered nurses were Black and roughly eight percent Hispanic.

A. SUMMARY This archived dataset includes data for population characteristics that are no longer being reported publicly. The date on which each population characteristic type was archived can be found in the field “data_loaded_at”.

B. HOW THE DATASET IS CREATED Data on the population characteristics of COVID-19 cases are from:  * Case interviews  * Laboratories  * Medical providers    These multiple streams of data are merged, deduplicated, and undergo data verification processes.  

Race/ethnicity * We include all race/ethnicity categories that are collected for COVID-19 cases. * The population estimates for the "Other" or “Multi-racial” groups should be considered with caution. The Census definition is likely not exactly aligned with how the City collects this data. For that reason, we do not recommend calculating population rates for these groups.

Gender * The City collects information on gender identity using these guidelines.

Skilled Nursing Facility (SNF) occupancy * A Skilled Nursing Facility (SNF) is a type of long-term care facility that provides care to individuals, generally in their 60s and older, who need functional assistance in their daily lives.  * This dataset includes data for COVID-19 cases reported in Skilled Nursing Facilities (SNFs) through 12/31/2022, archived on 1/5/2023. These data were identified where “Characteristic_Type” = ‘Skilled Nursing Facility Occupancy’.

Sexual orientation * The City began asking adults 18 years old or older for their sexual orientation identification during case interviews as of April 28, 2020. Sexual orientation data prior to this date is unavailable. * The City doesn’t collect or report information about sexual orientation for persons under 12 years of age. * Case investigation interviews transitioned to the California Department of Public Health, Virtual Assistant information gathering beginning December 2021. The Virtual Assistant is only sent to adults who are 18+ years old. https://www.sfdph.org/dph/files/PoliciesProcedures/COM9_SexualOrientationGuidelines.pdf">Learn more about our data collection guidelines pertaining to sexual orientation.

Comorbidities * Underlying conditions are reported when a person has one or more underlying health conditions at the time of diagnosis or death.

Homelessness Persons are identified as homeless based on several data sources: * self-reported living situation * the location at the time of testing * Department of Public Health homelessness and health databases * Residents in Single-Room Occupancy hotels are not included in these figures. These methods serve as an estimate of persons experiencing homelessness. They may not meet other homelessness definitions.

Single Room Occupancy (SRO) tenancy * SRO buildings are defined by the San Francisco Housing Code as having six or more "residential guest rooms" which may be attached to shared bathrooms, kitchens, and living spaces. * The details of a person's living arrangements are verified during case interviews.

Transmission Type * Information on transmission of COVID-19 is based on case interviews with individuals who have a confirmed positive test. Individuals are asked if they have been in close contact with a known COVID-19 case. If they answer yes, transmission category is recorded as contact with a known case. If they report no contact with a known case, transmission category is recorded as community transmission. If the case is not interviewed or was not asked the question, they are counted as unknown.

C. UPDATE PROCESS This dataset has been archived and will no longer update as of 9/11/2023.

D. HOW TO USE THIS DATASET Population estimates are only available for age groups and race/ethnicity categories. San Francisco po

The National Nursing Home Survey (NNHS) is a survey of nursing homes and related care facilities in the United States. Between July and December 1999, information regarding facility and financial characteristics was gathered from 1,423 facilities, along with current resident information for 8,215 residents. For Part 1, Facility Questionnaire Data, personal interviews with facility administrators provided information on topics such as certification, availability of beds, and kinds of services provided, including dental, hospice, and nutrition. Part 2, Current Resident Questionnaire Data, provides information on age, race, marital status, level of care, and use of aids such as walkers, hearing aids, and crutches. Part 3, Discharged Resident Questionnaire Data, includes date of admission, reason for discharge, admission diagnosis, discharge diagnosis, assistive devices used, help needed with daily activities, services provided (health, mental health, transportation, social, educational), and payment sources.

This is a monthly report on publicly funded community services for children, young people and adults using data from the Community Services Data Set (CSDS) reported in England for November 2017. The CSDS is a patient-level dataset providing information relating to publicly funded community services for children, young people and adults. These services can include district nursing services, school nursing services, health visiting services and occupational therapy services, among others. The data collected includes personal and demographic information, diagnoses including long-term conditions and disabilities and care events plus screening activities. It has been developed to help achieve better outcomes for children, young people and adults. It provides data that will be used to commission services in a way that improves health, reduces inequalities, and supports service improvement and clinical quality. Prior to October 2017, the predecessor Children and Young People's Health Services (CYPHS) Data Set collected data for children and young people aged 0-18. The CSDS superseded the CYPHS data set to allow adult community data to be submitted, expanding the scope of the existing data set by removing the 0-18 age restriction. The structure and content of the CSDS remains the same as the previous CYPHS data set. Further information about the CYPHS and related statistical reports is available from https://digital.nhs.uk/data-and-information/data-collections-and-data-sets/data-sets/children-and-young-people-s-health-services-data-set References to children and young people covers records submitted for 0-18 year olds and references to adults covers records submitted for those aged over 18. Where analysis for both groups have been combined, this is referred to as all patients. These statistics are classified as experimental and should be used with caution. Experimental statistics are new official statistics undergoing evaluation. They are published in order to involve users and stakeholders in their development and as a means to build in quality at an early stage. More information about experimental statistics can be found on the UK Statistics Authority website. We hope this information is helpful and would be grateful if you could spare a couple of minutes to complete a short customer satisfaction survey. Please use this form to provide us with any feedback or suggestions for improving the report. Update 6 April 2018: Please note since the removal of the age restriction to include adult data in CSDS, some of our Data Quality measures may not take into account items intended for children only. We are currently reviewing these measures and will look to reflect this in future reports.

The Facility-Level Minimum Data Set (MDS) Frequency dataset provides information for active nursing home residents on topics, such as race/ethnicity, age, or marital status; discharge dispositions; hearing, speech, and vision; cognitive patterns; mood; functional abilities and goals; bladder and bowel; active diagnoses; health conditions; swallowing/nutritional status; oral/dental status; skin conditions; medications; special treatments, procedures, and programs; restraints and alarms; and participation in assessment and goal setting.

Note: The MDS dataset contains more records than most spreadsheet programs can handle. The use of a database or statistical software is generally required. The dataset can be filtered to a more manageable size for use in a spreadsheet program by clicking on the “View Data” button. Additional filter information can be found in the methodology, if needed.

This layer contains a Vermont-only subset of census tract level 2020 Decennial Census redistricting data as reported by the U.S. Census Bureau for all states plus DC and Puerto Rico. The attributes come from the 2020 Public Law 94-171 (P.L. 94-171) tables.Data download date: August 12, 2021Census tables: P1, P2, P3, P4, H1, P5, HeaderDownloaded from: Census FTP siteProcessing Notes:Data was downloaded from the U.S. Census Bureau FTP site, imported into SAS format and joined to the 2020 TIGER boundaries. Boundaries are sourced from the 2020 TIGER/Line Geodatabases. Boundaries have been projected into Web Mercator and each attribute has been given a clear descriptive alias name. No alterations have been made to the vertices of the data.Each attribute maintains it's specified name from Census, but also has a descriptive alias name and long description derived from the technical documentation provided by the Census. For a detailed list of the attributes contained in this layer, view the Data tab and select "Fields". The following alterations have been made to the tabular data:Joined all tables to create one wide attribute table:P1 - RaceP2 - Hispanic or Latino, and not Hispanic or Latino by RaceP3 - Race for the Population 18 Years and OverP4 - Hispanic or Latino, and not Hispanic or Latino by Race for the Population 18 Years and OverH1 - Occupancy Status (Housing)P5 - Group Quarters Population by Group Quarters Type (correctional institutions, juvenile facilities, nursing facilities/skilled nursing, college/university student housing, military quarters, etc.)HeaderAfter joining, dropped fields: FILEID, STUSAB, CHARITER, CIFSN, LOGRECNO, GEOVAR, GEOCOMP, LSADC, BLOCK, BLKGRP, and TBLKGRP.GEOCOMP was renamed to GEOID and moved be the first column in the table, the original GEOID was dropped.Placeholder fields for future legislative districts have been dropped: CD118, CD119, CD120, CD121, SLDU22, SLDU24, SLDU26, SLDU28, SLDL22, SLDL24 SLDL26, SLDL28.P0020001 was dropped, as it is duplicative of P0010001. Similarly, P0040001 was dropped, as it is duplicative of P0030001.In addition to calculated fields, County_Name and State_Name were added.The following calculated fields have been added (see long field descriptions in the Data tab for formulas used): PCT_P0030001: Percent of Population 18 Years and OverPCT_P0020002: Percent Hispanic or LatinoPCT_P0020005: Percent White alone, not Hispanic or LatinoPCT_P0020006: Percent Black or African American alone, not Hispanic or LatinoPCT_P0020007: Percent American Indian and Alaska Native alone, not Hispanic or LatinoPCT_P0020008: Percent Asian alone, Not Hispanic or LatinoPCT_P0020009: Percent Native Hawaiian and Other Pacific Islander alone, not Hispanic or LatinoPCT_P0020010: Percent Some Other Race alone, not Hispanic or LatinoPCT_P0020011: Percent Population of Two or More Races, not Hispanic or LatinoPCT_H0010002: Percent of Housing Units that are OccupiedPCT_H0010003: Percent of Housing Units that are VacantPlease note these percentages might look strange at the individual tract level, since this data has been protected using differential privacy.*VCGI exported a Vermont-only subset of the nation-wide layer to produce this layer--with fields limited to this popular subset: OBJECTID: OBJECTID GEOID: Geographic Record Identifier NAME: Area Name-Legal/Statistical Area Description (LSAD) Term-Part Indicator County_Name: County Name State_Name: State Name P0010001: Total Population P0010003: Population of one race: White alone P0010004: Population of one race: Black or African American alone P0010005: Population of one race: American Indian and Alaska Native alone P0010006: Population of one race: Asian alone P0010007: Population of one race: Native Hawaiian and Other Pacific Islander alone P0010008: Population of one race: Some Other Race alone P0020002: Hispanic or Latino Population P0020003: Non-Hispanic or Latino Population P0030001: Total population 18 years and over H0010001: Total housing units H0010002: Total occupied housing units H0010003: Total vacant housing units P0050001: Total group quarters population PCT_P0030001: Percent of Population 18 Years and Over PCT_P0020002: Percent Hispanic or Latino PCT_P0020005: Percent White alone, not Hispanic or Latino PCT_P0020006: Percent Black or African American alone, not Hispanic or Latino PCT_P0020007: Percent American Indian and Alaska Native alone, not Hispanic or Latino PCT_P0020008: Percent Asian alone, not Hispanic or Latino PCT_P0020009: Percent Native Hawaiian and Other Pacific Islander alone, not Hispanic or Latino PCT_P0020010: Percent Some Other Race alone, not Hispanic or Latino PCT_P0020011: Percent Population of two or more races, not Hispanic or Latino PCT_H0010002: Percent of Housing Units that are Occupied PCT_H0010003: Percent of Housing Units that are Vacant SUMLEV: Summary Level REGION: Region DIVISION: Division COUNTY: County (FIPS) COUNTYNS: County (NS) TRACT: Census Tract AREALAND: Area (Land) AREAWATR: Area (Water) INTPTLON: Internal Point (Longitude) INTPTLAT: Internal Point (Latitude) BASENAME: Area Base Name POP100: Total Population Count HU100: Total Housing Count *To protect the privacy and confidentiality of respondents, data has been protected using differential privacy techniques by the U.S. Census Bureau. This means that some individual tracts will have values that are inconsistent or improbable. However, when aggregated up, these issues become minimized. Download Census redistricting data in this layer as a file geodatabase.Additional links:U.S. Census BureauU.S. Census Bureau Decennial CensusAbout the 2020 Census2020 Census2020 Census data qualityDecennial Census P.L. 94-171 Redistricting Data Program

The productivity of economically valuable focal trees in mixtures is often improved by inclusion of lower- value nursing species, but the mechanisms underpinning such effects are poorly resolved. This gap in understanding limits the capacity to develop efficient planting strategies for forests and woodlands to contribute to net-zero and other critical ecosystem functions. Here, we undertook a plant-soil feedback experiment to test the hypothesis that feedback effects improve the biomass of Sitka spruce (Picea sitchensis (Bong.) Carr) in soil conditioned by monocultures of heterospecific nurse species, and a mixture comprising Sitka spruce and heterospecifics, compared to soil conditioned by only Sitka spruce. Sitka spruce saplings had greater biomass in soil conditioned by Scots pine monocultures (Pinus sylvestris L.) and the mixture compared to their own soil or soil conditioned by silver birch (Betula pendula Roth). Statistical models showed that colonisation of ectomycorrhizal fungi ..., , , # Plant-soil feedback drives the nursing effect on Sitka spruce

https://doi.org/10.5061/dryad.4tmpg4fmh

Description of the data and file structure

Author: Yichen Zhou, University of Manchester

Contact: yichenzhou22yc@gmail.com

Date:2024/11/13

Contains material related to the paper:

Plant-soil feedback drives the ‘nursing effect’ on Sitka spruce.

Authors: Yichen Zhou, Tingting Tao, Filipa cox, David Johnson

Description:

This README file describes the model code associated with the above publication. All unites and methods are described in the publication.

Files and variables

File: Zhou_et.al-data.xlsx

Description: We have compiled all the data into “Zhou et.al-data†, which contains different sheets, including "Plant properties“ which includes the plant properties after the feedback phase, †Condition soil“ which includes the soil properties after the conditioning phase, "PSF" which ...

Total number of residents in each Kane Regional Center facility by race and gender. The Kane Regional Centers are skilled nursing and rehabilitation centers run by Allegheny County. A census of residents recorded once a week. NOTE: The feed updating this dataset is currently not functioning. We're working to update the available data and get a new feed working. The reports from the legacy system broke before that system was taken offline, and so the reports from September 2019 to February 2020 cannot be run.

This layer contains census tract level 2020 Decennial Census redistricting data as reported by the U.S. Census Bureau for all states plus DC and Puerto Rico. The attributes come from the 2020 Public Law 94-171 (P.L. 94-171) tables.Data download date: August 12, 2021Census tables: P1, P2, P3, P4, H1, P5, HeaderDownloaded from: Census FTP siteProcessing Notes:Data was downloaded from the U.S. Census Bureau FTP site, imported into SAS format and joined to the 2020 TIGER boundaries. Boundaries are sourced from the 2020 TIGER/Line Geodatabases. Boundaries have been projected into Web Mercator and each attribute has been given a clear descriptive alias name. No alterations have been made to the vertices of the data.Each attribute maintains it's specified name from Census, but also has a descriptive alias name and long description derived from the technical documentation provided by the Census. For a detailed list of the attributes contained in this layer, view the Data tab and select "Fields". The following alterations have been made to the tabular data:Joined all tables to create one wide attribute table:P1 - RaceP2 - Hispanic or Latino, and not Hispanic or Latino by RaceP3 - Race for the Population 18 Years and OverP4 - Hispanic or Latino, and not Hispanic or Latino by Race for the Population 18 Years and OverH1 - Occupancy Status (Housing)P5 - Group Quarters Population by Group Quarters Type (correctional institutions, juvenile facilities, nursing facilities/skilled nursing, college/university student housing, military quarters, etc.)HeaderAfter joining, dropped fields: FILEID, STUSAB, CHARITER, CIFSN, LOGRECNO, GEOVAR, GEOCOMP, LSADC, BLOCK, BLKGRP, and TBLKGRP.GEOCOMP was renamed to GEOID and moved be the first column in the table, the original GEOID was dropped.Placeholder fields for future legislative districts have been dropped: CD118, CD119, CD120, CD121, SLDU22, SLDU24, SLDU26, SLDU28, SLDL22, SLDL24 SLDL26, SLDL28.P0020001 was dropped, as it is duplicative of P0010001. Similarly, P0040001 was dropped, as it is duplicative of P0030001.In addition to calculated fields, County_Name and State_Name were added.The following calculated fields have been added (see long field descriptions in the Data tab for formulas used): PCT_P0030001: Percent of Population 18 Years and OverPCT_P0020002: Percent Hispanic or LatinoPCT_P0020005: Percent White alone, not Hispanic or LatinoPCT_P0020006: Percent Black or African American alone, not Hispanic or LatinoPCT_P0020007: Percent American Indian and Alaska Native alone, not Hispanic or LatinoPCT_P0020008: Percent Asian alone, Not Hispanic or LatinoPCT_P0020009: Percent Native Hawaiian and Other Pacific Islander alone, not Hispanic or LatinoPCT_P0020010: Percent Some Other Race alone, not Hispanic or LatinoPCT_P0020011: Percent Population of Two or More Races, not Hispanic or LatinoPCT_H0010002: Percent of Housing Units that are OccupiedPCT_H0010003: Percent of Housing Units that are VacantPlease note these percentages might look strange at the individual tract level, since this data has been protected using differential privacy.**To protect the privacy and confidentiality of respondents, data has been protected using differential privacy techniques by the U.S. Census Bureau. This means that some individual tracts will have values that are inconsistent or improbable. However, when aggregated up, these issues become minimized. The pop-up on this layer uses Arcade to display aggregated values for the surrounding area rather than values for the tract itself.Download Census redistricting data in this layer as a file geodatabase.Additional links:U.S. Census BureauU.S. Census Bureau Decennial CensusAbout the 2020 Census2020 Census2020 Census data qualityDecennial Census P.L. 94-171 Redistricting Data Program

This layer contains block level 2020 Decennial Census redistricting data as reported by the U.S. Census Bureau for the state of Massachusetts. The attributes come from the 2020 Public Law 94-171 (P.L. 94-171) tables.Data download date: August 12, 2021Census tables: P1, P2, P3, P4, H1, P5, HeaderDownloaded from: Census FTP siteProcessing Notes:Data was downloaded from the U.S. Census Bureau FTP site, imported into SAS format and joined to the 2020 TIGER boundaries. Boundaries are sourced from the 2020 TIGER/Line Geodatabases. Boundaries have been projected into Web Mercator and each attribute has been given a clear descriptive alias name. No alterations have been made to the vertices of the data.Each attribute maintains it's specified name from Census, but also has a descriptive alias name and long description derived from the technical documentation provided by the Census. For a detailed list of the attributes contained in this layer, view the Data tab and select "Fields". The following alterations have been made to the tabular data:Joined all tables to create one wide attribute table:P1 - RaceP2 - Hispanic or Latino, and not Hispanic or Latino by RaceP3 - Race for the Population 18 Years and OverP4 - Hispanic or Latino, and not Hispanic or Latino by Race for the Population 18 Years and OverH1 - Occupancy Status (Housing)P5 - Group Quarters Population by Group Quarters Type (correctional institutions, juvenile facilities, nursing facilities/skilled nursing, college/university student housing, military quarters, etc.)HeaderAfter joining, dropped fields: FILEID, STUSAB, CHARITER, CIFSN, LOGRECNO, GEOVAR, GEOCOMP, LSADC.GEOCOMP was renamed to GEOID and moved be the first column in the table, the original GEOID was dropped.Placeholder fields for future legislative districts have been dropped: CD118, CD119, CD120, CD121, SLDU22, SLDU24, SLDU26, SLDU28, SLDL22, SLDL24 SLDL26, SLDL28.P0020001 was dropped, as it is duplicative of P0010001. Similarly, P0040001 was dropped, as it is duplicative of P0030001.In addition to calculated fields, County_Name and State_Name were added.The following calculated fields have been added (see long field descriptions in the Data tab for formulas used): PCT_P0030001: Percent of Population 18 Years and OverPCT_P0020002: Percent Hispanic or LatinoPCT_P0020005: Percent White alone, not Hispanic or LatinoPCT_P0020006: Percent Black or African American alone, not Hispanic or LatinoPCT_P0020007: Percent American Indian and Alaska Native alone, not Hispanic or LatinoPCT_P0020008: Percent Asian alone, Not Hispanic or LatinoPCT_P0020009: Percent Native Hawaiian and Other Pacific Islander alone, not Hispanic or LatinoPCT_P0020010: Percent Some Other Race alone, not Hispanic or LatinoPCT_P0020011: Percent Population of Two or More Races, not Hispanic or LatinoPCT_H0010002: Percent of Housing Units that are OccupiedPCT_H0010003: Percent of Housing Units that are VacantPlease note these percentages might look strange at the individual block level, since this data has been protected using differential privacy.**To protect the privacy and confidentiality of respondents, data has been protected using differential privacy techniques by the U.S. Census Bureau. This means that some individual blocks will have values that are inconsistent or improbable. However, when aggregated up, these issues become minimized. The pop-up on this layer uses Arcade to display aggregated values for the surrounding area rather than values for the block itself.Additional links:U.S. Census BureauU.S. Census Bureau Decennial CensusAbout the 2020 Census2020 Census2020 Census data qualityDecennial Census P.L. 94-171 Redistricting Data Program

The National Medical Expenditure Survey (NMES) series provides information on health expenditures by or on behalf of families and individuals, the financing of these expenditures, and each person's use of services. The Institutional Population Component (IPC) is a survey of nursing and personal care homes and facilities for the mentally retarded and residents admitted to those facilities. Information was collected on facilities and their residents at several points during 1987. Use and expenditure estimates for institutionalized persons can be combined with those from the Household Component for composite estimates covering most of the civilian population. Information on facilities and residents was collected from facility administrators and caregivers, with additional information collected from next-of-kin or other knowledgeable respondents. These data were supplemented by Medicare claims information for covered sample persons. Research File 36 provides information from the Medicare Automated Data Retrieval System (MADRS) for a subset of persons from File 1 of NATIONAL MEDICAL EXPENDITURE SURVEY, 1987: INSTITUTIONAL POPULATION COMPONENT, FACILITY USE AND EXPENDITURE DATA FOR NURSING AND PERSONAL CARE HOME RESIDENTS PUBLIC USE TAPE 17 and a subset of persons from File 1 of NATIONAL MEDICAL EXPENDITURE SURVEY, 1987: INSTITUTIONAL POPULATION COMPONENT, FACILITY USE AND EXPENDITURE DATA FOR RESIDENTS OF FACILITIES FOR PERSONS WITH MENTAL RETARDATION RESEARCH FILE 22R. Six data files are provided for Research File 36R, all of which contain demographic data such as age, sex, and race. Other variables common to all parts are facility type, person number, sample person identifier, reimbursement amount by Medicare, and total charges reported by provider. Parts 1-6 cover, respectively, Part B Payment Records, Part B Outpatient Bill Records, Part B Home Health Bill Records, Part A Inpatient/Skilled Nursing Facilities Bill Records, Part A Home Health Bill Records, and Part A Hospice Bill Records.