Overview

The Abortion Surveillance System documents the number and characteristics of women obtaining legal induced abortions in the United States.

Coverage

The system includes women of all ages, including adolescents, who obtain legal induced abortions.

Methodology

Each year, CDC requests tabulated data from the central health agencies of 52 reporting areas (the 50 states, the District of Columbia [D.C.], and New York City) to document the number and characteristics of women obtaining abortions in the United States. For the purpose of surveillance, a legal induced abortion is defined as an intervention performed within the limits of state law by a licensed clinician (e.g., a physician, nurse-midwife, nurse practitioner, or physician assistant) that is intended to terminate a suspected or known ongoing intrauterine pregnancy and produce a nonviable fetus.

In most states, collection of abortion data is facilitated by the legal requirement for hospitals, facilities, and physicians to report abortions to a central health agency. These central health agencies voluntarily report abortion data to CDC and provide only the aggregate numbers for the abortion data they have collected through their independent surveillance systems. Although reporting to CDC is voluntary, most reporting areas provide aggregate abortion numbers; during 2005-2014, a total of 48 reporting areas provided CDC a continuous annual record of abortion numbers.

Issues Affecting Interpretation

Because reporting areas establish their own reporting requirements for abortion and send their data to CDC voluntarily, CDC is unable to obtain the total number of abortions performed in the United States. Although most states legally require medical providers to submit a report for all the abortions they perform, enforcement of this requirement varies. Additionally, although most reporting areas collect and send abortion data to CDC, during 2005-2014, 4 of the 52 reporting areas did not provide CDC with data on a consistent annual basis (the four states that did not report continuously for the period 2005-2014 were California, Louisiana, Maryland, and New Hampshire). Because of these limitations, during the period covered by this report, the total annual number of abortions recorded by CDC was consistently approximately 71% of the number recorded by the Guttmacher Institute, which uses numerous active follow-up techniques to increase the completeness of the data obtained through its periodic national census of abortion providers. (See Appendix I, Guttmacher Institute Abortion Provider Census.)

Reference

• Jatlaoui TC, Shah J, Mandel MG, Krashin JW, Suchdev DB, Jamieson DJ, Pazol K. Abortion surveillance-United States, 2014. MMWR Surveill Summ 66(24):1–48. 2017. Available from: https://www​.cdc.gov/mmwr​/volumes/66/ss/ss6624a1.htm. [PubMed: 29166366]

For More Information. See the NCCDPHP surveillance and research website at: https://www.cdc.gov/reproductivehealth/Data_Stats/index.htm.

Overview

ACS provides annual estimates of income, education, employment, health insurance coverage, and housing costs and conditions for U.S. residents. Estimates from ACS complement population data collected by the U.S. Census Bureau during the decennial census. Topics currently included annually in ACS were previously collected once a decade through the decennial census long form.

Coverage

Since full implementation began in 2005, ACS covers U.S. residents residing in all 3,141 counties in the 50 states and the District of Columbia, and all 78 municipalities in Puerto Rico. ACS began data collection for U.S. residents residing in housing units in January 2005 and for residents residing in group quarters facilities in January 2006. Annual ACS estimates are available every year for states and for specific geographic areas with populations of 65,000 or more.

Methodology

Starting with 2013 data, the ACS data collection operation uses up to four modes to collect information: Internet, mail, telephone, and personal visit interviews. The first mode includes a mailed request to respond to the ACS questionnaire via Internet, followed by an option to complete a paper questionnaire and return it by mail. If neither an Internet nor mail questionnaire is received, a follow-up interview by phone or personal visit is attempted for a sample of nonrespondents. Prior to 2013, Internet collection was not used and only three modes of collection were used. Each month, a sample of housing unit addresses and residents of group quarters facilities receive questionnaires. Housing units include a house; apartment; mobile home or trailer; a group of rooms; and a single room occupied as separate living quarters, or if vacant, intended for occupancy as separate living quarters. Group quarters are places where people live or stay that are normally owned or managed by an entity or organization providing housing and services for residents. These services may include custodial or medical care as well as other types of assistance, and residency is commonly restricted to persons receiving these services The group quarters population comprises both the institutional and noninstitutional group quarters populations. The institutional group quarters population includes residents under formally authorized supervised care, such as those in skilled nursing facilities, adult correctional facilities, and psychiatric hospitals.

The noninstitutional group quarters population includes residents of colleges or university housing, military barracks, and group homes.

ACS creates two sets of weights: a weight for each sample person record (both household and group-quarters persons) and a weight for each sample housing unit record. For information on the weighting procedure, see the ACS methodology website at: https://www.census.gov/programs-surveys/acs/methodology.html.

Sample Size and Response Rate

Each year from 2005 through 2010, approximately 2.9 million housing unit addresses in the United States and 36,000 in Puerto Rico were selected to participate in ACS. Starting in 2011, the housing unit sample was increased to 3.54 million addresses per year. For 2005-2012, the housing unit response rate was 97%-98%; in 2013, the housing unit response rate was 90%; in 2014-2016, it was 94%-97%. Beginning in 2006, the ACS sample was expanded to include 2.5% of the population living in group quarters, which included approximately 20,000 group quarters facilities and 195,000 residents of group quarters in the United States and Puerto Rico. In 2013, the group quarters sample for college dormitories was restricted to the nonsummer months. The group quarters response rate ranged between 95% and 98% for 2006-2016. For year-specific response rates, see: https://www.census.gov/acs/www/methodology/sample-size-and-data-quality/response-rates/index.php.

Issues Affecting Interpretation

Several changes were made to the ACS questionnaire at the beginning of 2008, including the introduction of new questions on health insurance coverage. Health insurance coverage estimates are methodologically consistent for data year 2009 and subsequent years (O’Hara and Medalia). In addition, the methodology for weighting the group quarters survey changed starting in 2011.

References

• Torrieri N, Program Staff. American Community Survey design and methodology (January 2014). U.S. Census Bureau. 2014. Available from: https://www2​.census.gov​/programs-surveys​/acs/methodology/design_and_methodology​/acs​_design_methodology_report_2014.pdf
• O’Hara B, Medalia C. CPS and ACS health insurance estimates: Consistent trends from 2009-2012. SEHSD working paper 2014-29. U.S. Census Bureau, Social, Economic, and Housing Statistics Division. 2014. Available from: https://www​.census.gov​/content/dam/Census​/library/working-papers​/2014/demo/sehsd_wp_2014-29.pdf

For More Information

See the ACS website at: https://www.census.gov/programs-surveys/acs.

Overview

CFOI compiles comprehensive and timely information on fatal work injuries to monitor workplace safety and to inform private and public health efforts to improve workplace safety.

Coverage

The data cover all 50 states and the District of Columbia. In selected years, data are available for Puerto Rico, the Virgin Islands, and Guam but are not included in Health, United States because of data comparability issues.

Methodology

CFOI is administered by BLS, in conjunction with participating state agencies, to compile counts that are as complete as possible to identify, verify, and profile fatal work injuries. Key information about each workplace fatal injury (occupation and other worker characteristics, equipment or machinery involved, and circumstances of the event) is obtained by cross-referencing source documents. For a fatal occupational injury to be included in the census, decedents must have been employed (i.e., self-employed, working for pay, or volunteering) at the time of the event, engaged in a legal work activity, or present at the site of the incident as a requirement of their job. These criteria are generally broader than those used by federal and state agencies administering specific laws and regulations. Fatal work injuries that occur during a person’s commute to or from work are excluded from the census counts. Fatal work injuries to volunteer workers who are exposed to the same work hazards and perform the same duties or functions as paid employees and who meet the CFOI work relationship criteria are included. For more information on workplace fatalities included in CFOI, see: https://www.bls.gov/iif/cfoiscope.htm.

Data for CFOI are compiled from various federal, state, and local administrative sources, including death certificates, workers’ compensation reports and claims, reports to various regulatory agencies, medical examiner reports, police reports, and news reports. Diverse sources are used because studies have shown that no single source captures all job-related fatal injuries. Source documents are matched so that each fatal work injury is counted only once. To ensure that a fatal work injury occurred while the decedent was at work, information is verified from two or more independent source documents or from a source document and a follow-up questionnaire.

Issues Affecting Interpretation

Prior to the release of 2015 data, the number of fatal occupational injuries was revised once after the initial preliminary release. States had up to 8 months to identify additional cases following their initial published counts before data collection closed for a reference year. Fatal work injuries initially excluded from the published count due to insufficient information may have been subsequently verified as work-related and included in the revised counts. Increases in the published counts from 2010 through 2014 based on additional information averaged 159 fatal occupational injuries per year, or less than 4% of the annual total. Beginning with 2015 data, preliminary releases were no longer produced, and only final CFOI data were produced.

CFOI classifies industries by the North American Industry Classification System (NAICS), which is revised periodically. Industry data for the reference years 2003-2008 were classified based on the 2002 NAICS, while industry data for reference years 2009-2013 were classified based on the 2007 NAICS. For reference year 2014 onwards, CFOI used the 2012 NAICS. In Health, United States, industry data are presented at the two-digit level. Most of the differences between the versions of NAICS were at a more detailed level; therefore, changes in NAICS over time are unlikely to affect the trend of CFOI data presented in Health, United States. (See Appendix II, Industry of employment; Table IX.)

References

• Bureau of Labor Statistics. Census of Fatal Occupational Injuries summary, 2016 [news release]. December 19, 2017. Available from: https://www​.bls.gov/news​.release/cfoi.nr0.htm.
• Bureau of Labor Statistics. Revisions to the 2014 Census of Fatal Occupational Injuries (CFOI). 2016. Available from: https://www​.bls.gov/iif​/oshwc/cfoi/cfoi_revised14.htm

For More Information

See the CFOI website at: https://www.bls.gov/iif/oshcfoi1.htm and the CFOI section of the BLS Handbook of Methods at: https://www.bls.gov/opub/hom/pdf/homch9.pdf.

Overview

CPS provides current estimates and trends in employment, unemployment, and other characteristics of the general labor force. The Annual Social and Economic (ASEC) Supplement—commonly called the March CPS supplement—of CPS provides supplemental data on work experience, income, noncash benefits, and migration, and is the source of the poverty estimates presented in Health, United States.

Coverage

The CPS sample, referred to as the basic CPS, is based on the results of the decennial census, with coverage in all 50 states and the District of Columbia (D.C.). When files from the most recent decennial census become available, the U.S. Census Bureau gradually introduces a new sample design for CPS. The CPS sample based on Census 2000 was introduced in April 2004 and implemented by July 2005. The CPS sample based on Census 2010 was introduced in April 2014 and implemented by July 2015.

For the basic CPS, persons aged 15 and over in the civilian noninstitutionalized population are eligible to participate; persons living in institutions such as prisons, long-term care hospitals, and nursing homes are not eligible for the survey. The CPS ASEC sample size is slightly larger than that of the basic CPS because it includes members of the Armed Forces living in civilian housing units on a military base or in households not on a military base. The CPS ASEC sample also includes additional Hispanic households that are not included in the monthly CPS estimates.

Methodology

The basic CPS sample is selected from multiple frames using multiple stages of selection. Each unit is selected with a known probability to represent similar units in the universe. The sample design is state-based, with the sample in each state being independent of the others. One person generally responds for all eligible members of a household.

The CPS interview is divided into three parts: (a) household and demographic information, (b) labor force information, and (c) supplemental information for months that include supplements.

Estimates of poverty presented in Health, United States from CPS are derived from ASEC. ASEC collects the usual monthly labor force data in addition to data on migration, longest held job during the year, weeks worked, time spent looking for work or on layoff from a job, and income from all sources including noncash sources (e.g., food stamps, school lunch program, employer-provided group health insurance plan, personal health insurance, Medicaid, Medicare, TRICARE or military health care, and energy assistance).

The additional Hispanic sample in CPS ASEC is based on the previous November’s basic CPS sample. If a person is identified as being of Hispanic origin from the November interview and is still residing at the same address in March, that housing unit is eligible for the March survey. This amounts to a near-doubling of the Hispanic sample because there is no overlap of housing units between the basic CPS samples in November and March.

The ASEC sample weight is an adjusted version of the final CPS sample weight. The final CPS sample weight is the product of the basic weight, the adjustments for special weighting, the noninterview adjustment, the first-stage ratio adjustment factor, and the second-stage ratio adjustment factor. Due to differences in the questionnaire, sample, and data uses for the ASEC supplement, the ASEC sample weight should be used for poverty estimates.

Sample Size and Response Rate

The 2016 data from the 2017 CPS ASEC were based on a sample of about 95,000 addresses collected in the 50 states and DC The basic CPS household-level nonresponse rate was 13.5%, while the household-level CPS ASEC nonresponse rate was an additional 14.0%. These two nonresponse rates resulted in a combined supplement nonresponse rate of 25. 6%.

Beginning with 2001, the Children’s Health Insurance Program (CHIP) sample expansion was introduced. This included an increase in the basic CPS sample to about 60,000 households per month in 2001. Prior to 2001, estimates were based on about 50,000 households per month. The expansion also included an additional 12,000 households that were allocated differentially across states based on prior information about the low-income, uninsured children in each state This expansion was made to improve the reliability of state estimates on the number of children who lived in low-income families and lacked health insurance coverage.

Issues Affecting Interpretation

Over the years, the number of income questions has expanded, questions on work experience and other characteristics have been added, and the month of interview was moved to March. In 2002, an ASEC sample increase was implemented, requiring more time for data collection. Thus, additional ASEC interviews are now taking place in February and April. However, even with this sample increase, most of the data collection still occurs in March.

In 1994, major changes were introduced that included a complete redesign of the questionnaire and the introduction of computer-assisted interviewing for the entire survey. In addition, some of the labor force concepts and definitions were revised. Prior to this redesign, CPS data were primarily collected using a paper-and-pencil form. Beginning in 1994, population controls were based on the 1990 Census and adjusted for the estimated population undercount. Starting with Health, United States, 2003, poverty estimates for data years 2000 and beyond were recalculated based on the expanded CHIP sample, and Census 2000-based population controls were implemented Starting with 2002 data, race-specific estimates are tabulated according to the 1997 Revisions to the Standards for the Classification of Federal Data on Race and Ethnicity and are not strictly comparable with estimates for earlier years. Starting with Health, United States, 2012, Census 2010-based population controls were implemented for poverty estimates for 2010 and beyond. For a discussion of the impact of the implementation of the Census 2010-based controls on poverty estimate trends, see DeNavas-Walt et al.

For 2013 data, the CPS ASEC used a split panel to test a new set of income questions. Starting with Health, United States, 2015, estimates for 2013 are presented two ways: using questions consistent with previous ASEC surveys and using the new set of income questions. Because data for 2013 (using the new income questions) and data for 2014 and beyond are based on the new set of income questions from the redesigned questionnaire, data trends need to be interpreted with caution.

References

• U.S. Census Bureau. Current Population Survey: Design and methodology. Technical paper 66. 2006. Available from: https://www​.census.gov​/prod/2006pubs/tp-66.pdf.
• DeNavas-Walt C, Proctor BD, Smith JC. Income, poverty, and health insurance coverage in the United States: 2011. Current Population Reports, P60-243. 2012. Available from: https://www​.census.gov​/prod/2012pubs/p60-243.pdf
• Semega JL, Fontenot KR, Kollar MA. Income and poverty in the United States: 2016 Current Population Reports, P60-259. 2017. Available from: https://www​.census.gov​/content/dam/Census​/library/publications​/2017/demo/P60-259.pdf

For More Information

See the CPS website at: https://www.census.gov/programs-surveys/cps.html.

Overview

The VA compiles and analyzes multiple data sets on the health and health care of its clients and other veterans. Monitoring access and quality of care enables the VA to conduct program and policy evaluations. The VA maintains nationwide systems that contain a statistical record for each episode of care provided under VA auspices, as well as in VA and non-VA hospitals, nursing homes, VA residential rehabilitation treatment programs (formerly called domiciliaries), and VA outpatient clinics. The VA also maintains enrollment information for each veteran enrolled in the VA health care system.

Coverage

U.S. veterans who receive services within the VA medical system are included. Data are available for some nonveterans who receive care at VA facilities.

Methodology

Encounter data from VA clinical information systems are collected locally at each VA medical center and transmitted electronically to the VA’s Austin Automation Center for use in providing nationwide statistics, reports, and comparisons.

Issues Affecting Interpretation

The databases include users of the VA health care system. VA eligibility is a hierarchy based on service-connected disabilities, income, age, and availability of services. Therefore, the population served by VA programs may have sociodemographic characteristics that differ from populations served by other health care systems.

For More Information

See the VA Information Resource Center website at: https://www.virec.research.va.gov/.

Overview

HCUP is a family of health care databases and related software tools developed through a federal-state-industry partnership to build a multistate health data system for health care research and decision making. The National (Nationwide) Inpatient Sample (HCUP-NIS), a component of HCUP, is the largest all-payer inpatient care database that is publicly available in the United States.

HCUP-NIS contains a core set of clinical and nonclinical information found in a typical discharge abstract, including all-listed diagnoses and procedures, discharge status, patient demographics, and charges for all patients regardless of payer (e.g., persons covered by Medicare, Medicaid, and private insurance, as well as those without insurance coverage).

Coverage

In 2014, HCUP-NIS covered about 95% of all U.S. community hospital discharges (excluding discharges from rehabilitation or long-term acute care hospitals) from 44 states and the District of Columbia (D.C.). Community hospitals are defined by the American Hospital Association as nonfederal, short-term, general, and other specialty hospitals, excluding hospital units of institutions.

The number of states participating in HCUP-NIS has generally increased each year. In the years of data presented in Health, United States, the number of states participating was 28 in 2000, 37 in 2005, 45 in 2010, 46 in 2011, 44 in 2012, 43 states and D.C. in 2013, and 44 states and D.C. in 2014. In 2014, all states except Alabama, Alaska, Delaware, Idaho, Mississippi, and New Hampshire were included.

Methodology

On October 1, 2015, the United States transitioned to the International Classification of Diseases, 10th Revision, Clinical Modification (ICD-10-CM) diagnosis coding system for most inpatient and outpatient medical encounters and the International Classification of Diseases, 10th Revision, Procedure Coding System (ICD-10-PCS) for inpatient hospital procedures. Because of the impact of this transition to ICD-10-CM/PCS, and because full calendar year data for 2015 are not available using one ICD system, the Health, United States Table 96 has not been updated with 2015 data.

In 2012, HCUP-NIS was redesigned to improve national estimates. To highlight the design change, beginning with 2012 data, AHRQ renamed HCUP-NIS from “Nationwide Inpatient Sample” to the “National Inpatient Sample.” The redesigned HCUP-NIS is now a sample of discharge records from all HCUP-participating hospitals It approximates a 20% stratified sample of discharges from U.S. community hospitals, excluding rehabilitation and long-term acute care hospitals. The information abstracted from hospital discharge records is translated into a uniform format to facilitate both multistate and national-state comparisons and analyses.

Prior to 2012, HCUP-NIS was designed to approximate a 20% stratified sample of U.S. community hospitals, rather than a sample of discharges. The pre-2012 HCUP-NIS was a stratified probability sample of hospitals in the frame, with sampling probabilities proportional to the number of U.S. community hospitals in each stratum (ownership and control, bed size, teaching status, urban or rural location, and U.S. region). Discharge records for all patients in the sampled hospitals were included in the pre-2012 HCUP-NIS. To permit longitudinal analysis, the statistics for years prior to 2012 presented in Health, United States were regenerated using new trend weights taking into account the redesign.

Hospital costs are derived from total hospital charges using hospital-specific cost-to-charge ratios based on hospital cost reports from the Centers for Medicare & Medicaid Services. Hospital charges reflect the amount the hospital billed for the entire hospital stay and do not include professional (physician) fees. Costs will tend to reflect the actual costs to produce hospital services, whereas charges represent what the hospital billed for the care. Costs are adjusted for economy-wide inflation using the Bureau of Economic Analysis Gross Domestic Product Price Index to remove economy-wide inflation that reflects the effect of changing average prices for the same goods and services. Additional inflation that is specific to the hospital sector is not removed in this calculation.

Sample Size and Response Rate

The 2014 HCUP-NIS contains data from 7. 1 million hospital stays sampled from 4,411 hospitals.

Issues Affecting Interpretation

Weights are produced to create national estimates, but because the number of participating states has increased over time, estimates from earlier years may be biased if omitted states have substantially different hospitalization patterns than states that provided data. In 2012, the survey was redesigned. HCUP-NIS is now a sample of discharge records from all HCUP-participating hospitals, rather than a sample of hospitals from which all discharges were retained. The statistics for years prior to 2012 presented in Health, United States were regenerated using new trend weights taking into account the redesign.

References

• Agency for Healthcare Research and Quality. Introduction to the HCUP National Inpatient Sample (NIS), 2014. 2016. Available from: https://www​.hcup-us.ahrq​.gov/db/nation/nis​/NISIntroduction2014.pdf.
• Houchens R, Ross D, Elixhauser A, Jiang J. Nationwide Inpatient Sample (NIS) redesign final report. HCUP Methods Series Report No 2014-04. 2014. U.S. Agency for Healthcare Research and Quality. Available from: https://www​.hcup-us.ahrq​.gov/reports/methods/2014-04.pdf.

For More Information

See the HCUP website at: https://www.hcup-us.ahrq.gov/.

Overview

CMS works with its state partners to collect data on each person served by the Medicaid program in order to monitor and evaluate access to and quality of care, trends in program eligibility, characteristics of enrollees, changes in payment policy, and other program-related issues. MSIS is the primary data source for Medicaid statistical information. Data collected include claims for services and their associated payments for each Medicaid beneficiary by type of service. MSIS also collects information on the characteristics of every Medicaid-eligible individual, including eligibility and demographic information.

Coverage

Medicaid data for all 50 states and the District of Columbia are available starting from 1999. The data include information about all individuals enrolled in the Medicaid program, the services they receive, and the payments made for those services.

Methodology

Beginning in fiscal year (FY) 1999, as a result of legislation enacted from the Balanced Budget Act of 1997, states were required to submit individual eligibility and claims data tapes to CMS quarterly through MSIS. Prior to FY 1999, states were required to submit an annual Health Care Financing Administration-2082 report, designed to collect aggregated statistical data on eligibles, recipients, services, and expenditures during a federal fiscal year (October 1 through September 30), or at state option, to submit eligibility data and claims through MSIS. The claims data reflect bills resolved or processed during the year, rather than services used during the year.

Issues Affecting Interpretation

Starting with 2011 data, estimates were derived from Medicaid claims files and a new methodology was used to obtain estimates. Therefore, caution should be used when comparing data for 2010 and earlier with more recent data. Not all states had reported data as of the date the statistics were obtained. States not reporting are listed in the table notes. For more information on data and analytic issues, see: https://www.cms.gov/Research-Statistics-Data-and-Systems/Computer-Data-and-Systems/MedicaidDataSourcesGenInfo/MSIS-Tables.html.

For More Information

See the CMS website at: https://www.medicaid.gov/index.html and the Research Data Assistance Center website at: https://www.cms.gov/Research-Statistics-Data-and-Systems/Research/ResearchGenInfo/ResearchDataAssistanceCenter.html. (Also see Appendix II, Medicaid.)

Overview

MEPS produces nationally representative estimates of health care use, expenditures, sources of payment, insurance coverage, and quality of care. MEPS consists of three components: the Household Component (HC), the Medical Provider Component (MPC), and the Insurance Component. Data from MEPS-HC and MEPS-MPC are used in Health, United States.

Coverage

The U.S. civilian noninstitutionalized population is represented.

Methodology

MEPS-HC is a national probability survey conducted annually since 1996. The panel design of the survey features five rounds of interviewing covering 2 full calendar years. The HC is a nationally representative survey of the civilian noninstitutionalized population drawn from a subsample of households that participated in the prior year’s National Health Interview Survey. Missing expenditure data in the HC are imputed largely from data collected in the MPC.

The MPC collects data from hospitals, physicians, home health care providers, and pharmacies that were reported in the HC as providing care to MEPS sample persons. Data are collected in the MPC to improve the accuracy of the expenditure estimates that would be obtained if derived solely from the HC. The MPC is particularly useful in obtaining expenditure information for persons enrolled in managed care plans and Medicaid recipients Sample sizes for the MPC vary from year to year depending on the HC sample size and the MPC sampling rates for providers.

The MEPS predecessor, the 1987 National Medical Expenditure Survey (NMES), consisted of two components: the Household Survey (HS) and the Medical Provider Survey (MPS). The NMES-HS component was designed to provide nationally representative estimates for the U.S. civilian noninstitutionalized population for the calendar year 1987. Data from the NMES-MPS component were used in conjunction with HS data to produce estimates of health care expenditures. NMES-HS consisted of four rounds of household interviews. Income information was collected in a special supplement administered early in 1988. Events under the scope of NMES-MPS included medical services provided by or under the direction of a physician, all hospital events, and home health care.

Sample Size and Response Rate

In the 2014 MEPS, 13,421 families were covered, and 33,162 respondents over the course of the year. For the same year, the overall annual response rate was 48.5%, reflecting nonresponse to the National Health Interview Survey from which the MEPS sample was selected, as well as nonresponse and attrition in MEPS.

Issues Affecting Interpretation

The 1987 estimates are based on NMES, and 1996 and later years’ estimates are based on MEPS. Because expenditures in NMES were based primarily on charges, whereas those for MEPS were based on payments, data for NMES were adjusted to be more comparable with MEPS by using estimated charge-to-payment ratios for 1987. For a detailed explanation of this adjustment, see Zuvekas and Cohen.

References

• Ezzati-Rice TM, Rohde F, Greenblatt J. Sample design of the Medical Expenditure Panel Survey Household Component, 1998-2007. Methodology report no 22. Agency for Healthcare Research and Quality. 2008. Available from: https://meps​.ahrq.gov​/mepsweb/data_files​/publications/mr22/mr22.shtml.
• Zuvekas SH, Cohen JW. A guide to comparing health care expenditures in the 1996 MEPS to the 1987 NMES. Inquiry 39(1):76–86. 2002. [PubMed: 12067078]

For More Information

See the MEPS website at: https://meps.ahrq.gov/mepsweb/.

Overview

CMS collects and synthesizes Medicare enrollment, spending, and claims data to monitor and evaluate access to and quality of care, trends in utilization, changes in payment policy, and other program-related issues. Data include claims information for services furnished to Medicare fee-for-service beneficiaries and Medicare enrollment data. Claims data include type of service, procedures, diagnoses, dates of service, charge amounts, and payment amounts. Enrollment data include date of birth, sex, race, and reason for entitlement.

Coverage

Enrollment data are for all persons enrolled in the Medicare program. Claims data include data for Medicare fee-for-service beneficiaries who received services and for whom claims were filed. Claims data are not included for beneficiaries enrolled in managed care plans.

Methodology

The claims and utilization data files contain extensive utilization information at various levels of summarization for a variety of providers and services. There are many types and levels of these files: National Claims History (NCH) files, Standard Analytic files (SAFs), Medicare Provider and Analysis Review (MedPAR) files, Medicare enrollment files, and various other files.

The NCH files contain all institutional and noninstitutional claims submitted during a calendar year, including adjustment claims. SAFs contain “final action” claims data in which all adjustments have been resolved. Both the NCH and SAF files contain information collected by Medicare to pay for health care services provided to a Medicare beneficiary. SAFs are available for each institutional (inpatient, outpatient, skilled nursing facility, hospice, or home health agency) and noninstitutional (physician and durable medical equipment providers) claim type The record unit of SAFs is the claim (some episodes of care may have more than one claim).

MedPAR files contain inpatient hospital and skilled nursing facility (SNF) final action stay records. Each MedPAR record represents a stay in an inpatient hospital or SNF. An inpatient stay record summarizes all services rendered to a beneficiary from the time of admission to a facility, through discharge. Each MedPAR record may represent one claim or multiple claims, depending on the length of a beneficiary’s stay and the amount of inpatient services used throughout the stay.

The Denominator file contains demographic and enrollment information about each beneficiary enrolled in Medicare during a calendar year. The information in the Denominator file is frozen in March of the following calendar year. Some of the information contained in this file includes the beneficiary unique identifier, state and county codes, ZIP code, date of birth, date of death, sex, race, age, monthly entitlement indicators (for Medicare Part A, Medicare Part B, or Part A and Part B), reasons for entitlement, state buy-in indicators, and monthly managed care indicators (yes or no). The Denominator file is used to determine beneficiary demographic characteristics, entitlement, and beneficiary participation in Medicare managed care organizations (MCOs).

The Chronic Conditions Data Warehouse (CCW) includes files with 100% of Medicare enrollment and fee-for-service claims data. Detailed information on the CCW is available from the CCW website: https://www.ccwdata.org.

Issues Affecting Interpretation

Because Medicare MCOs might not file claims, files based only on claims data will exclude care for persons enrolled in Medicare MCOs. In addition, to maintain a manageable file size, some files are based on a sample of enrollees rather than on all Medicare enrollees. Coding and the interpretation of Medicare coverage rules have also changed over the life of the Medicare program.

For More Information

See the CMS Research Data Assistance Center website at: https://www.resdac.org and the CMS website at: https://www.cms.gov/Research-Statistics-Data-and-Systems/Research-Statistics-Data-and-Systems.html. (Also see Appendix II, Medicare.)

Overview

MCBS produces nationally representative estimates of health and functional status, health care use and expenditures, health insurance coverage, and socioeconomic and demographic characteristics of Medicare beneficiaries. It is used to estimate expenditures and sources of payment for all services used by Medicare beneficiaries, including copayments, deductibles, and noncovered services; to determine all types of health insurance coverage and relate coverage to sources of payment; and to trace outcomes over time, such as changes in health status and the effects of program changes.

Coverage

MCBS is a continuous survey of a nationally representative sample of aged, institutionalized, and disabled Medicare beneficiaries.

Methodology

The overlapping panel design of the survey allows each sample person (or his or her proxy) to be interviewed three times a year for 4 years, regardless of whether he or she resides in the community, resides in a facility, or moves between the two settings—the version of the questionnaire appropriate to the setting is used. Sampled people are interviewed using computer-assisted personal interviewing (CAPI) survey instruments. Because residents of long-term care facilities are often in poor health, information about institutionalized residents is collected from proxy respondents such as nurses and other primary caregivers affiliated with the facility. The sample is selected from the Medicare enrollment files, with oversampling among disabled persons under age 65 and among persons aged 85 and over.

MCBS has two components: the Cost supplement (formerly known as the Cost and Use file) and the Survey file (formerly known as the Access to Care file). Medicare claims are linked to survey-reported events to produce the Cost supplement, which provides complete expenditure and source-of-payment data on all health care services, including those not covered by Medicare. The Survey file contains information on beneficiaries’ access to health care, satisfaction with care, and usual source of care. The sample for both files represents the ever-enrolled population, including those who entered Medicare and those who died during the year. Additionally, the Survey file provides survey weights that represent the always-enrolled population—those who participated in the Medicare program for the entire year.

Sample Size and Response Rate

Each fall, about one-third of the MCBS sample is retired, and roughly 6,000 new sample persons are included in the survey; the exact number chosen is based on projections of target samples of 14,000 persons with 3 years of cost and use information distributed appropriately across the sample cells. In the community, response rates for initial interviews are approximately 60%; once respondents have completed the first interview, their participation in subsequent rounds is 80% or more. In recent rounds, data have been collected from approximately 16,000 beneficiaries. Roughly 90% of the sample is made up of persons who live in the community, with the remaining made up of persons living in long-term care facilities. Response rates for facility interviews approach 100%.

Issues Affecting Interpretation

Because only Medicare beneficiaries are included in MCBS, the survey excludes a small proportion of persons aged 65 and over who are not enrolled in Medicare This should be noted when using MCBS to make estimates of the entire population aged 65 and over in the United States. Starting with 2012 data, the Cost supplement estimates were created with a new imputation methodology; therefore some utilization estimates may not be comparable with previous years. Due to changes in sampling and data collection methodologies, 2014 data are not available.

References

• Adler GS. A profile of the Medicare Current Beneficiary Survey. Health Care Financ Rev 15(4):153–63. 1994. Available from: https://www​.ncbi.nlm​.nih.gov/pmc/articles​/PMC4193434/pdf/hcfr-15-4-153.pdf. [PMC free article: PMC4193434] [PubMed: 10138483]
• Lo A, Chu A, Apodaca R. Redesign of the Medicare Current Beneficiary Survey sample. Rockville, MD: Westat, Inc 2003.

For More Information

See the MCBS website at: https://www.cms.hhs.gov/MCBS.

Overview

MTF is an ongoing study that uses annual surveys to track the behaviors, attitudes, and values of U.S. secondary school students, college students, and adults through age 55. Data collected include lifetime, annual, and 30-day prevalence of use of many illegal drugs, inhalants, tobacco, and alcohol.

Coverage

MTF surveys a sample of 12th, 10th, and 8th graders in public and private high schools in the coterminous United States. Follow-up questionnaires are mailed to a randomly selected sample from each graduating class for a number of years after their initial participation, to gather information on college students, young adults, and older adults.

Methodology

The survey design is a multistage random sample, with stage 1 being the selection of particular geographic areas, stage 2 being the selection of one or more high schools in each area, and stage 3 being the selection of students within each school. Data are collected using self-administered questionnaires conducted in the classroom by representatives of the University of Michigan’s Institute for Social Research. Dropouts and students who are absent from school or class at the time of data collection are excluded Recognizing that the dropout population is at higher risk for drug use, MTF was expanded in 1991 to include two nationally representative samples of 8th and 10th graders, who have lower dropout rates than 12th graders, and to include future high-risk 12th grade dropouts. Separate samples of schools and students are drawn at each grade level, and the survey procedures used for the 8th and 10th grade students closely parallel those used for the 12th grade students. For more information on MTF adjustments for absentees and dropouts, see Johnston etal. (data years 2014 and preceding); and Miech RA et al. (data years 2015 onward).

Sample Size and Response Rate

In 2016, a total of 45,473 students in 372 public and private schools in the coterminous United States participated. The annual 12th grade sample comprised 12,600 12th graders in 120 public and private high schools nationwide. The 10th grade sample comprised 15,230 students in 110 schools, while the 8th grade sample comprised 17,643 students in 142 schools. Response rates were 80% for the 12th grade, 88% for the 10th grade, and 90% for the 8th grade sample and have been relatively constant across time. Absentees constitute virtually all of the nonresponding students.

Issues Affecting Interpretation

Estimates of substance use among youth based on the National Survey on Drug Use and Health (NSDUH) are not directly comparable with estimates based on MTF and the Youth Risk Behavior Surveillance System (YRBSS). In addition to the fact that MTF excludes dropouts and absentees, rates are not directly comparable across these surveys because of differences in populations covered, sample design, questionnaires, interview setting, and data-cleaning procedures NSDUH collects data in residences, whereas MTF and YRBSS collect data in school classrooms. In addition, NSDUH estimates are tabulated by age, whereas MTF and YRBSS estimates are tabulated by grade, representing different ages as well as different populations.

References

• Johnston LD, O’Malley PM, Bachman JG, Schulenberg JE, Miech RA. Monitoring the Future national survey results on drug use, 1975-2013: Volume I, Secondary school students. 2014.
• Miech RA, Johnston LD, O’Malley PM, Bachman JG, Schulenberg JE, Patrick, ME. Monitoring the Future national survey results on drug use: 1975-2016. Volume I, Secondary school students. 2017. Available from: http://www​.monitoringthefuture​.org/pubs/monographs​/mtf-vol1_2016.pdf.
• Cowan CD. Coverage, sample design, and weighting in three federal surveys. J Drug Issues 31(3):599–614. 2001.

For More Information

See the NIDA website at: https://www.drugabuse.gov/publications/drugfacts/monitoring-future-survey-high-school-youth-trends, and the MTF website at: http://www.monitoringthefuture.org.

Overview

NAMCS provides national data about the provision and use of medical care services in office-based physician practices in the United States, using information collected from medical records. Data are collected on type of providers seen; reason for visit; diagnoses; drugs ordered, provided, or continued; and selected procedures and tests ordered or performed during the visit. Patient data include age, sex, race, and expected source of payment. Data are also collected on selected characteristics of physician practices, including the adoption and use of electronic health record (EHR) systems.

Coverage

NAMCS covers patient visits to the offices of nonfederally employed physicians classified by the American Medical Association (AMA) or American Osteopathic Association (AOA) as “office-based, patient care” physicians in the United States. Physicians in the specialties of anesthesiology, pathology, and radiology, as well as physicians who are principally engaged in teaching, research, or administration, are excluded from the physician universe. Patient visits with physicians engaged in prepaid practices (health maintenance organizations, independent practice organizations, and other prepaid practices) are included in NAMCS, while telephone contacts and nonoffice visits are excluded. In 2006, a separate sample of community health centers (CHCs) was added to NAMCS. The CHC component samples visits to physicians and nonphysician clinicians. Starting with 2014 data, the sample was expanded to include hospital-based physicians. In 2012, the NAMCS survey sample size was temporarily increased to allow for state-level estimates in the 34 most populous states and the U.S. Census Bureau divisions. In 2014, the state-based sample included 18 states. In 2015, the sample size was refined to include the 16 most populous states.

Methodology

A multistage probability design is employed. In 1989-2011, the first-stage sample consisted of 112 primary sampling units (PSUs) that were selected from about 1,900 such units into which the United States had been divided. In each sample PSU, a sample of practicing nonfederal, office-based physicians was selected from master files maintained by AMA and AOA. The final stage involved systematic random samples of office visits during randomly assigned 7-day reporting periods. Starting with the 2012 survey, the sampling design was changed to a list sample of physicians, instead of an area sample, to ensure adequate representation for state-level estimates. Another major change, which began in 2012, was in the mode of data collection, which changed from in-person interviews with a paper questionnaire to laptop-assisted data collection by Census field representatives using automated survey instruments.

To sample CHC physicians and nonphysician clinicians, a dual-sampling procedure was used. First, the traditional NAMCS sample was selected using the methods described above. Second, information from the Health Resources and Services Administration and the Indian Health Service was used to select a sample of CHCs. Within CHCs, a maximum of three health care providers—which included physicians as well as nonphysician practitioners—were selected. Nonphysician practitioners included physicians, physician assistants, nurse practitioners, or nurse midwives. After selection, CHC providers followed traditional NAMCS methods for selecting patient visits.

In 2008, a supplemental mail survey on EHR systems was conducted in addition to the core NAMCS. This supplement was known as the National Ambulatory Medical Care Survey-Electronic Medical Records Supplement Starting in 2010, the mail survey sample size was increased fivefold to allow for state-level estimates. Starting in 2012, the survey was changed from a supplement to become the National Electronic Health Records Survey (NEHRS). Survey questions have been added since the introduction of NEHRS.

Sample data are weighted to produce national estimates. The estimation procedure used in NAMCS has four basic components: inflation by the reciprocal of the probability of selection, adjustment for nonresponse, ratio adjustment to fixed totals, and weight smoothing.

Sample Size and Response Rate

The physician and visit sample sizes have varied over the years. Most recently, the numbers of eligible physicians were 6,999 in 2013, 6,016 in 2014, and 4,910 in 2015. The numbers of visits included were 54,360 in 2013, 45,710 in 2014, and 28,332 in 2015. The unweighted response rates in the past 3 years were 41%, 39%, and 29%, respectively.

Issues Affecting Interpretation

The NAMCS patient record form is modified approximately every 2 to 4 years to reflect changes in physician practice characteristics, patterns of care, and technological innovations. Examples of recent changes include increasing the number of drugs recorded on the patient record form and adding checkboxes for specific tests or procedures performed. Sample sizes vary by survey year. For some years it is suggested that analysts combine 2 or more years of data if they wish to examine relatively rare populations or events. The 2012 sampling design change may affect trending 2012 and subsequent data with earlier data. For more information on the new sampling design, see Hing E et al.

References

• Hing E, Shimizu IM, Talwalkar A. Nonresponse bias in estimates from the 2012 National Ambulatory Medical Care Survey. Vital Health Stat 2(171). National Center for Health Statistics. 2016. Available from: https://www​.cdc.gov/nchs​/data/series/sr_02/sr02_171.pdf. [PubMed: 27301078]
• National Center for Health Statistics. 2015 NAMCS micro-data file documentation. Available from: ftp://ftp​.cdc.gov/pub​/Health_Statistics/NCHS​/Dataset_documentation​/namcs/doc2015.pdf.

For More Information

See the National Health Care Surveys website at: https://www.cdc.gov/nchs/dhcs/index.htm, and the Ambulatory Health Care Data website at: https://www.cdc.gov/nchs/ahcd/index.htm.

Overview

NCS provides comprehensive measures of occupational earnings, compensation cost trends, benefit incidence, and detailed health and retirement plan provisions based on surveys of a sample of employers.

Coverage

NCS provides information for the country on both full- and part-time workers who are paid a wage or salary and includes data for the civilian economy, including both private industry and state and local government. It excludes agriculture, private household workers, the self-employed, and the federal government.

Methodology

NCS is conducted quarterly by BLS’ Office of Compensation and Working Conditions. The sample is selected using a three-stage design. The first stage is the selection of geographic areas for the state and local government sample and the private industry sample. In the second stage, establishments are selected systematically, with the probability of selection proportionate to their relative employment size within sampled areas. Use of this technique means that the larger an establishment’s employment, the greater its chance of selection. The third stage of sampling is a probability sample of occupations within a sampled establishment. This step is performed by the BLS field economist during an interview with the respondent establishment in which selection of an occupation is based on probability of selection proportionate to employment in the establishment, and each occupation is classified under its corresponding major occupational group.

Data collection is conducted by BLS field economists. Data are gathered from each establishment on the primary business activity of the establishment; types of occupations; number of employees; wages, salaries, and benefits; hours of work; and duties and responsibilities. Data are collected for the pay period including the 12th day of the survey months of March, June, September, and December.

Sample Size and Response Rate

The March 2017 sample consists of about 6,700 establishments in private industry and about 1,400 establishments in state and local government.

Issues Affecting Interpretation

Prior to 1999, estimates were based on multiple surveys that were replaced by NCS; therefore, trend analyses based on estimates prior to 1999 should be interpreted with care.

The state and local government sample is revised every 10 years and was replaced in its entirety in December 2007. As a result of this update, the number of state and local government occupations and establishments increased substantially. The private industry sample is fully replaced over an approximately 5-year period, which makes the sample more representative of the economy and reduces respondent burden The sample is replaced on a cross-area, cross-establishment basis.

Compensation cost levels in state and local government should not be directly compared with levels in private industry. Differences between these sectors stem from factors such as variation in work activities and occupational structures.

References

• U.S. Bureau of Labor Statistics. Employer costs for employee compensation-March 2017 [press release] USDL-17-0770. June 9, 2017. Available from: https://www​.bls.gov/news​.release/archives/ecec_06092017.pdf.
• Wiatrowski WJ. The National Compensation Survey: Compensation statistics for the 21st century. Compensation and Working Conditions. Winter: 5–14. 2000. Available from: https://www​.bls.gov/opub​/mlr/cwc/the-national-compensation-survey-compensation-statistics-for-the-21st-century.pdf.
• U.S. Bureau of Labor Statistics. Chapter 8: National compensation measures. In: BLS handbook of methods. 2007. Available from: https://www​.bls.gov/opub/hom/pdf/homch8​.pdf

For More Information

See the NCS website at: https://www.bls.gov/ncs.

Overview

NHANES is designed to assess the health and nutritional status of adults and children in the United States. The survey is unique in that it combines interviews and physical examinations. NHANES collects data on the prevalence of chronic diseases and conditions (including undiagnosed conditions) and on risk factors such as obesity, elevated serum cholesterol levels, hypertension, diet and nutritional status, and numerous other measures.

Coverage

NHANES III, conducted during 1988-1994, and the continuous NHANES, which began in 1999, target the civilian noninstitutionalized U.S. population.

Methodology

NHANES includes clinical examinations, selected medical and laboratory tests, and self-reported data NHANES interviews persons in their homes and conducts medical examinations in a mobile examination center (MEC), including laboratory analysis of blood, urine, and other tissue samples. Medical examinations and laboratory tests follow very specific protocols and are standardized as much as possible to ensure comparability across sites and providers. During 1988-1994, as a substitute for the MEC examinations, a small number of survey participants received an abbreviated health examination in their homes if they were unable to come to the MEC.

The survey for NHANES III was conducted from 1988 to 1994 using a stratified, multistage probability design to sample the civilian noninstitutionalized U.S. population About 40,000 persons aged 2 months and over were selected and asked to complete an extensive interview and a physical examination. Participants were selected from households in 81 survey units across the United States. Children aged 2 months to 5 years, persons aged 60 and over, black persons, and persons of Mexican origin were oversampled to provide precise descriptive information on the health status of selected population groups in the United States.

Beginning in 1999, NHANES became a continuous annual survey, collecting data every year from a representative sample of the civilian noninstitutionalized U.S. population, newborns and older, through in-home personal interviews and physical examinations in the MEC. The sample design is a complex, multistage, clustered design using unequal probabilities of selection. The first-stage sample frame for continuous NHANES during 1999-2001 was the list of primary sampling units (PSUs) selected for the design of the National Health Interview Survey. Typically, an NHANES PSU is a county. For 2002, an independent sample of PSUs (based on current census data) was selected This independent design was used for the period 2002-2006. In 2007-2010 and 2011-2014, the sample was redesigned. For 1999, because of a delay in the start of data collection, 12 distinct PSUs were in the annual sample. For each year during 2000-2016, 15 PSUs were selected. The within-PSU design involves forming secondary sampling units that are nested within census tracts, selecting dwelling units within secondary units, and then selecting sample persons within dwelling units. Selection of the final sample person involves differential probabilities of selection according to the demographic variables of sex (male or female), race and ethnicity, and age. Because of the differential probabilities of selection, dwelling units are screened for potential sample persons.

Beginning in 1999, NHANES oversampled low-income persons, adolescents aged 12-19, persons aged 60 and over, African-American persons, and persons of Mexican origin. The sample for data years 1999-2006 was not designed to give a nationally representative sample for the total Hispanic population residing in the United States. Starting with 2007-2010 data collection, all Hispanic persons were oversampled, not just persons of Mexican origin, and adolescents were no longer oversampled. In 2011-2014, the sampling design was changed and the following groups were oversampled: Hispanic persons; non-Hispanic black persons; non-Hispanic Asian persons; non-Hispanic white and other persons at or below 130% of poverty; and non-Hispanic white and other persons aged 80 and over. In 2015-2016, the sampling design was revised again, changing the cut-point for low-income oversampling from at or below 130% of poverty to at or below 185% of poverty. For more information on the sample design for 1999-2006, see: https://www.cdc.gov/nchs/data/series/sr_02/sr02_155.pdf; for 2007-2010, see: https://www.cdc.gov/nchs/data/series/sr_02/sr02_160.pdf; for 2011-2014, see: https://www.cdc.gov/nchs/data/series/sr_02/sr02_162.pdf; and for 2015-2016, see: https://wwwn.cdc.gov/nchs/nhanes/continuousnhanes/Overview.aspx?BeginYear=2015.

The estimation procedure used to produce national statistics for all NHANES involved inflation by the reciprocal of the probability of selection, adjustment for nonresponse, and poststratified ratio adjustment to population totals. Sampling errors also were estimated, to measure the reliability of the statistics.

Sample Size and Response Rate

Over the 6-year survey period of NHANES III, 39,695 persons were selected; the household interview response rate was 86% (33,994), and the medical examination response rate was 78% (30,818). For NHANES 1999-2000 to NHANES 2011-2012, the number of persons selected ranged from 12,160 to 13,431. The percentage who were interviewed ranged from 73% to 84%, while the percentage who were examined ranged from 70% to 80%. For NHANES 2013-2014, a total of 14,332 persons were eligible, of which 71% (10,175) were interviewed and 68% (9,813) completed the health examination component. For NHANES 2015-2016, a total of 15,327 persons were eligible, of which 61% (9,971) were interviewed and 59% (9,544) completed the health examination component. For more detailed information on unweighted NHANES response rates and response weights using sample size weighted to Current Population Survey population totals, see: https://wwwn.cdc.gov/nchs/nhanes/ResponseRates.aspx.

Issues Affecting Interpretation

Data elements, laboratory tests performed, and the technological sophistication of medical examination and laboratory equipment have changed over time. Therefore, trend analyses should carefully examine how specific data elements were collected across the various survey years. Data files are revised periodically. If the file changes are minor and the impact on estimates is small, then the data are not revised in Health, United States. Major data changes are incorporated.

Periodically, NHANES changes its sampling design to oversample different groups. Because the total sample size in any year is fixed due to operational constraints, sample sizes for the other oversampled groups (including Hispanic persons and non-low-income white and other persons) were decreased. Therefore, trend analyses on demographic subpopulations should be carefully evaluated to determine if the sample sizes meet the NHANES Analytic Guidelines. In general, any 2-year data cycle in NHANES can be combined with adjacent 2-year data cycles to create analytic data files based on 4 or more years of data, in order to improve precision. However, because of the sample design change in 2011-2012, the data user should be aware of the implications if these data are combined with data from earlier survey cycles. Users are advised to examine their estimates carefully to see if the 4-year estimates (and sampling errors) are consistent with each set of 2-year estimates.

References

• Ezzati TM, Massey JT, Waksberg J, Chu A, Maurer KR. Sample design: Third National Health and Nutrition Examination Survey. National Center for Health Statistics. Vital Health Stat 2(113). 1992. Available from: https://www​.cdc.gov/nchs​/data/series/sr_02/sr02_113.pdf. [PubMed: 1413563]
• National Center for Health Statistics. Plan and operation of the Third National Health and Nutrition Examination Survey, 1988-94. National Center for Health Statistics. Vital Health Stat 1(32). 1994. Available from: https://www​.cdc.gov/nchs​/data/series/sr_01/sr01_032.pdf. [PubMed: 7975354]
• Johnson CL, Paulose-Ram R, Ogden CL, Carroll MD, Kruszon-Moran D, Dohrmann SM, Curtin LR. National Health and Nutrition Examination Survey: Analytic guidelines, 1999-2010. National Center for Health Statistics. Vital Health Stat 2(161). 2013. Available from: https://www​.cdc.gov/nchs​/data/series/sr_02/sr02_161.pdf
• Johnson CL, Dohrmann SM, Burt VL, Mohadjer LK. National Health and Nutrition Examination Survey: Sample design, 2011-2014. National Center for Health Statistics. Vital Health Stat 2(162). 2014. Available from: https://www​.cdc.gov/nchs​/data/series/sr_02/sr02_162.pdf [PubMed: 25569458]

For More Information

See the NHANES website at: https://www.cdc.gov/nchs/nhanes/index.htm.

Overview

NHEA provides estimates of aggregate health care expenditures in the United States from 1960 onward. NHEA contains all of the main components of the health care system within a unified, mutually exclusive, and exhaustive structure. The accounts measure spending for health care in the United States by type of good or service delivered (e.g., hospital care, physician and clinical services, or retail prescription drugs) and by the source of funds that pay for that care (e.g., private health insurance, Medicare, Medicaid, or out of pocket). A consistent set of definitions is used for health care goods and services and for sources of funds that finance health care expenditures, allowing for comparisons over time.

Methodology

NHEA estimates health care spending using an expenditures approach to national economic accounting. NHEA includes all of the main components of the health care system within a comprehensive and mutually exclusive structure. Expenditures are estimated for the payers, as well as the categories of medical goods and services. A common set of definitions allows comparison among categories and over time. In addition, estimates are benchmarked to revenue estimates from the Census Bureau’s quinquennial Economic Census.

An assortment of government and private sources are used to create NHEA. In addition to the Economic Census, government sources include data from the Census Bureau’s Services Annual Survey, the Bureau of Economic Analysis, the National Income and Product Accounts, and Medicare claims data Private data sources include the American Hospital Association’s Annual Survey and the Kaiser Health Research and Educational Trust Employer Health Benefits Survey.

For example, private health insurance spending for health care goods and services is derived using data from the Census Bureau, the American Medical Association, the American Hospital Association, IQVIA (formerly IMS Health), and the Medical Expenditure Panel Surveys (MEPS) data from the Agency for Healthcare Research and Quality. For a matrix of data sources used for NHEA, see Exhibit 4 of “National Health Expenditure Accounts: Methodology Paper, 2016 “

Issues Affecting Interpretation

Every 5 years, NHEA undergoes a comprehensive revision that includes the incorporation of newly available source data, methodological and definitional changes, and benchmark estimates from the Economic Census. During these comprehensive revisions, the entire NHEA time series is opened for revision.

References

• Hartman M, Martin AB, Espinosa N, Catlin A, the National Health Expenditure Accounts Team. National health care spending in 2016: Spending and enrollment growth slow after initial coverage expansions. Health Aff (Millwood) 37(1):150–60 2018. [PubMed: 29211503]
• Centers for Medicare & Medicaid Services. National Health Expenditure Accounts: Methodology paper, 2016. Definitions, sources, and methods. 2017. Available from: https://www​.cms.gov/Research-Statistics-Data-and-Systems​/Statistics-Trends-and-Reports​/NationalHealthExpendData​/downloads/dsm-16.pdf.
• Centers for Medicare & Medicaid Services. Summary of 2014 comprehensive revision to the National Health Expenditure Accounts. 2015. Available from: https://www​.cms.gov/Research-Statistics-Data-and-Systems​/Statistics-Trends-and-Reports​/NationalHealthExpendData​/Downloads/benchmark2014.pdf.

For More Information

See the CMS National Health Expenditure Accounts website at: https://www.cms.gov/Research-Statistics-Data-and-Systems/Statistics-Trends-and-Reports/NationalHealthExpendData/NationalHealthAccountsHistorical.html.

Overview

NHIS monitors the health of the U.S. population through the collection and analysis of data on a broad range of health topics. A major strength of this survey lies in its ability to analyze health measures by many demographic and socioeconomic characteristics During household interviews, NHIS obtains information on activity limitation, illnesses, injuries, chronic conditions, health insurance coverage (or lack thereof), utilization of health care, and other health topics.

Coverage

The survey covers the civilian noninstitutionalized population of the United States. Among those excluded are patients in long-term care facilities, persons on active duty with the Armed Forces (although their dependents are included), incarcerated persons, and U.S. nationals living in foreign countries.

Methodology

NHIS is a cross-sectional household interview survey. Sampling and interviewing are continuous throughout each year. The sample design follows a multistage area probability design that permits the representative sampling of households and noninstitutional group quarters (e.g., college dormitories). The sample design for NHIS is redesigned approximately every 10 years to better measure the changing U.S. population and to meet new survey objectives. A new sample design was implemented in 2016.

The current sample design has many similarities to the design that was in place from 2006 to 2015, but there are some key differences. Sample areas were reselected to take into account changes in the distribution of the U.S. population since 2006, when the previous sample design was first implemented. Commercial address lists were used as the main source of addresses, rather than field listing; and the oversampling procedures for black, Hispanic, and Asian persons that were a feature of the previous sample design were not implemented in 2016. However, persons aged 65 or over who are black, Hispanic, or Asian continue to have a higher chance of being selected for the sample adult selection stage.

The first stage of the current 2016 sample design consists of a sample of 319 primary sampling units (PSUs) drawn from approximately 1,700 geographically defined PSUs, with some PSUs in each of the 50 states and the District of Columbia.

In the current 2016 sample design, PSUs with the largest populations (e.g., the New York City metropolitan area), also called self-representing (SR) PSUs, are sampled with certainty. The set of PSUs with smaller populations, called nonself-representing (NSR) PSUs, is stratified geographically by state. Independently within each state, a systematic sample of address clusters was selected. The NSR PSUs where these address clusters were located were then considered to be in the sample. Similarly, independently within each state, a systematic sample of address clusters was selected from the state’s SR PSUs.

The 2016 NHIS sampling frame consists of three nonoverlapping parts: the unit frame (a list of addresses); the area frame (geographic areas without addresses or where the unit frame did not sample sufficiently); and the college dormitory frame.

The total NHIS sample is subdivided into four separate panels such that each panel (and any combination of the panels) is representative of the U.S. civilian noninstitutionalized population. This design feature has a number of advantages, including flexibility for the total sample size.

The current NHIS questionnaire, implemented in 1997, has two basic parts: a Basic Module or Core and one or more supplements that vary by year. The Core remains largely unchanged from year to year and allows for trend analysis and for data from more than 1 year to be pooled to increase the sample size for analytic purposes. The Core contains three components: the Family, the Sample Adult, and the Sample Child. The Family component collects information on everyone in the family. From each family participating in NHIS, one adult is randomly selected to participate in the Sample Adult questionnaire. For families with children under age 18, one child is randomly selected to participate in the Sample Child questionnaire. For children, information is provided by a knowledgeable family member aged 18 or over residing in the household. Because some health issues are different for children and adults, these two questionnaires differ in some items, but both collect basic information on health status, use of health care services, health conditions, and health behaviors.

NHIS will implement a redesigned survey in January 2019. The redesign is intended to improve the measurement of covered health topics, reduce respondent burden by shortening the length of the questionnaire, harmonize overlapping content with other federal health surveys, establish a long-term structure of ongoing and periodic topics, and incorporate advances in survey methodology and measurement.

Sample Size and Response Rate

The NHIS sample size varies from year to year. It may be reduced for budgetary reasons or may be augmented if supplementary funding is available. The normal annual sample size (i.e., the number of households or persons for whom data are collected and publicly released) for the previous 2006-2015 sample design and for the new 2016 sample design is about 35,000 households containing about 87,500 persons.

In 2011-2016, the NHIS sample size was augmented in 32 states and the District of Columbia to increase the number of states for which reliable state-level estimates can be produced. Each year during 2011-2016, the sample size was augmented between 13% and 28%. In 2016, the sample size was augmented by approximately 15%: the sample numbered 97,169 persons, with 33,028 persons participating in the Sample Adult questionnaire and 11,107 participating in the Sample Child questionnaire. In 2016, the total household response rate was 68%. The final response rate in 2016 was 54% for the Sample Adult file and 62% for the Sample Child file.

Issues Affecting Interpretation

As part of the 1997 questionnaire redesign, some basic concepts were changed, and other concepts were measured in different ways. For some questions, there was a change in the reference period.

Also in 1997, the collection methodology changed from paper-and-pencil questionnaires to computer-assisted personal interviewing. Some indicators presented in Health, United States begin with 1997 data because the redesign caused a break in the trend. Also, starting with Health, United States, 2005, estimates for 2000-2002 were revised to use 2000-based weights and differ from previous editions of Health, United States that used 1990-based weights for those data years. The weights available in the public-use NHIS files for 2000-2002 are 1990-based. Data for 2003-2011 use weights derived from the 2000 Census. Data for 2012 and beyond use weights derived from the 2010 Census. In 2006-2010, the sample size was reduced, and this is associated with slightly larger variance estimates than in other years when a larger sample was fielded. Starting in 2010, a geographic nonresponse adjustment was made to both the sample adult weight and the sample child weight; see Moriarity.

References

• Moriarity C. 2009 National Health Interview Survey sample adult and sample child nonresponse bias analysis. 2010. Available from: https://www​.cdc.gov/nchs​/data/nhis/nr_bias​_analysis_report_2009_NHIS.pdf.
• National Center for Health Statistics. 2016 National Health Interview Survey (NHIS) public use data release. Available from: ftp://ftp​.cdc.gov/pub​/Health_Statistics/NCHS​/Dataset_Documentation​/NHIS/2016/srvydesc.pdf.

For More Information

See the NHIS website at: https://www.cdc.gov/nchs/nhis.htm.

Overview

Human immunodeficiency virus (HIV) surveillance data are used to detect and monitor cases of HIV infection in the United States, evaluate epidemiologic trends, identify unusual cases requiring follow-up, and inform public health efforts to prevent and control the disease. Data collected on persons with diagnosed HIV infection include age, sex, race, ethnicity, mode of exposure, and geographic region.

Coverage

All 50 states, the District of Columbia (D.C.), and 6 U.S. dependent areas (American Samoa, Guam, Northern Mariana Islands, Puerto Rico, Republic of Palau, and the U.S. Virgin Islands) report confirmed diagnoses of HIV infection to CDC using a uniform surveillance case definition and case report form. As of April 2008, all reporting areas had implemented confidential, name-based HIV infection reporting and agreed to participate in CDC’s National HIV Surveillance System. Health, United States only presents data for the 50 states and D.C.

Methodology

HIV surveillance includes case report data from 50 states, D.C., and 6 dependent areas. Using a standard confidential case report form, the health departments collect information that is then transmitted electronically, without personal identifiers, to CDC.

Issues Affecting Interpretation

Although the completeness of reporting of cases of HIV infection to state and local health departments differs by geographic region and patient population, studies conducted by state and local health departments indicate that the reporting of cases of HIV infection in most areas of the United States is more than 80% complete.

In 2014, the criteria used to define HIV diagnoses changed. Because of the change in case definition, HIV diagnoses prior to 2014 are not strictly comparable with HIV diagnoses for 2014. See Appendix II, Human immunodeficiency virus (HIV) disease and Acquired immunodeficiency syndrome (AIDS), for discussion of HIV diagnoses reporting definitions and other issues affecting interpretation of trends.

Reference

• Centers for Disease Control and Prevention. HIV surveillance reports. Published annually. Available from: https://www​.cdc.gov/hiv​/library/reports/hivsurveillance.html.

For More Information

See the NCHHSTP website at: https://www.cdc.gov/nchhstp.

Overview

NHAMCS provides national data on the provision and use of medical care services in hospital emergency and outpatient departments, using information collected from medical records. Data are collected on types of providers seen; reason for visit; diagnoses; drugs ordered, provided, or continued; and selected procedures and tests performed during the visit. Patient data include age, sex, race, and expected source of payment. Data are also collected on selected characteristics of the hospitals included in the survey.

Coverage

NHAMCS covers visits to emergency departments (EDs) and outpatient departments (OPDs) of nonfederal, short-stay, or general hospitals in the United States. Visits to federal, military, and Veterans Administration hospitals, as well as telephone contacts, are excluded. Starting in 2009, the survey includes visits to hospital-based ambulatory surgery centers (ASCs). Starting in 2010, visits to freestanding ASCs are included in the survey. In 2012 only, there was an oversample of hospitals in the five most populous states, which permits state-level estimates for these states.

Methodology

The four-stage probability sample design used in NHAMCS involves samples of (a) geographically defined primary sampling units (PSUs), (b) hospitals within PSUs, (c) clinics or emergency service areas within OPDs or EDs, and (d) patient visits within clinics or emergency service areas. EDs are treated as their own stratum, and all service areas within EDs are included. The first-stage sample of NHAMCS consists of 112 PSUs selected from 1,900 such units that make up the United States.

These PSUs were stratified by socioeconomic and demographic variables and then selected with a probability proportional to their 1980 population size. Stratification was done within four geographical regions by metropolitan statistical area (MSA) or non-MSA status using 1980 Census of Population data. The NHAMCS PSU sample included with certainty the 26 National Health Interview Survey (NHIS) PSUs with the largest populations. In addition, the NHAMCS sample included one-half of the next 26 largest PSUs, and 1 PSU from each of the 73 PSU strata formed from the remaining PSUs for the NHIS sample.

In 2013, the hospital universe and national sample were updated using data from IQVIA’s (formerly IMS Health) annual data product. Nonfederal and noninstitutional hospitals with six or more beds staffed for inpatient use and with an average length of stay of less than 30 days (short-stay), hospitals whose specialty was general (medical or surgical), or children’s general were eligible for NHAMCS. Hospitals were then classified into four groups on the basis of information in the hospital file: those with only an ED; those with an ED and an OPD; those with only an OPD; and those with neither an ED nor an OPD. Hospitals in the last class were considered as a separate stratum, and a sample of 50 hospitals was selected from this stratum to allow for estimation to the total universe of eligible hospitals. All hospitals with EDs or OPDs in noncertainty sample PSUs with five or fewer hospitals were selected with certainty In the original sample selected in 1991, there were 149 hospitals in 55 PSUs in this category In noncertainty sample PSUs with more than five hospitals, hospitals were arrayed by hospital class; type of ownership (not for profit, nonfederal government, and for profit); and hospital size. Hospital size was measured by the combined volume of ED and OPD visits. From the arrayed hospitals, five hospitals were selected using systematic random sampling with probability proportional to size from this group.

The hospital selections were made so that each hospital would be chosen only once to avoid multiple inclusions of very large hospitals. A fixed panel of 600 hospitals was initially selected for the NHAMCS sample; 550 hospitals had an ED, an OPD, or both; and 50 hospitals had neither an ED nor an OPD. To preclude hospitals participating during the same time period each year, the sample of 600 hospitals was randomly divided into 16 subsets of approximately equal size. Each subset was assigned to 1 of the 16 4-week reporting periods beginning December 2, 1991, which continues to rotate across each survey year. Therefore, the entire sample does not participate in a given year, and each hospital is inducted approximately once every 15 months.

Starting with the 2012 survey, the mode of data collection was changed from paper-and-pencil to computer-assisted. The U.S. Census Bureau field representatives use laptops containing an automated version of each survey instrument to 1) conduct the induction interviews with hospital staff; 2) determine the number of emergency department service areas to include; and 3) abstract and record data from medical charts. Another major change was the addition of questions on electronic health records to the hospital induction form.

Sample data are weighted to produce national estimates. The estimation procedure used in NHAMCS has three basic components: inflation by the reciprocal of the probability of selection, adjustment for nonresponse, and population weighting ratio adjustment.

Sample Size and Response Rate

In any given year when the sample is not supplemented (as done in 2012), the hospital sample consists of approximately 450 hospitals, of which 80% have EDs and about one-half have eligible OPDs. Typically, about 800 to 1,000 clinics are selected from participating hospital OPDs.

In 2011, the number of patient record forms (PRFs) completed for EDs was 31,084 and for OPDs was 32,233, and the overall unweighted response rate was 80% for EDs and 67% for OPDs. OPD data for years after 2011 are not currently available, and at present, there is no timeline for their release. In 2012, the number of PRFs completed for EDs was 29,453, and the overall unweighted ED response rate was 64%. In 2013, 24,777 ED PRFs were completed for an ED response rate of 65%. In 2014, 23,844 ED PRFs were completed for an overall ED response rate of 61%. In 2015, 21,061 ED PRFs were completed for an overall ED response rate of 55%.

Issues Affecting Interpretation

The NHAMCS PRF is modified approximately every 2 to 4 years to reflect changes in physician practice characteristics, patterns of care, and technological innovations. Examples of recent changes include an increase in the number of drugs recorded on the PRF and adding checkboxes for specific tests or procedures performed.

References

• National Center for Health Statistics. 2012 NHAMCS micro-data file documentation. Available from: ftp://ftp​.cdc.gov/pub​/Health_Statistics/NCHS​/Dataset_Documentation​/NHAMCS/doc12_ed.pdf.
• National Center for Health Statistics. 2015 NHAMCS micro-data file documentation. Available from: ftp://ftp​.cdc.gov/pub​/Health_Statistics/NCHS​/Dataset_Documentation​/NHAMCS/doc15_ed.pdf.

For More Information

See the National Health Care Surveys website at: https://www.cdc.gov/nchs/dhcs/index.htm, and the Ambulatory Health Care Data website at: https://www.cdc.gov/nchs/ahcd/index.htm.

Overview

NIS is a continuing nationwide telephone sample survey to monitor vaccination coverage rates among children aged 19-35 months and among teenagers aged 13-17 (NIS-Teen). Data collection for children aged 19-35 months started in 1994, and data collection for teenagers aged 13-17 started in 2006.

Coverage

Children aged 19-35 months and adolescents aged 13-17 in the civilian noninstitutionalized population are represented in this survey. Estimates of vaccine-specific coverage are available for the country, the 50 states, the District of Columbia, and some U.S. territories.

Methodology

NIS is a nationwide telephone sample survey of households with age-eligible children. The survey uses a two-phase sample design. First, a random-digit-dialing sample of telephone numbers is drawn. When households with at least one age-eligible child are contacted, the interviewer collects demographic and access-related information on all age-eligible children, the mother, and the household, and obtains permission to contact the children’s vaccination providers. Second, identified providers are sent vaccination history questionnaires by mail. Final weighted estimates are adjusted for households without telephones and for nonresponse. All vaccination coverage estimates are based on provider-reported vaccination histories NIS-Teen followed the same sample design and data collection procedures as NIS, except that only one age-eligible adolescent was selected from each screened household for data collection.

Starting in 2011, the NIS sampling frame was expanded from a single-landline frame to dual-landline and cellular telephone sampling frames. This change increased the representativeness of the sample characteristics but had little effect on the final 2011 NIS and NIS-Teen national estimates of vaccination coverage overall and when stratified by poverty status. See details of the dual-frame sample design in the annual NIS data user’s guide on the NIS website, available from: https://www.cdc.gov/vaccines/imz-managers/nis/datasets.html.

Sample Size and Response Rate

In 2016, the overall Council of American Survey Research Organizations (CASRO) response rate for NIS was 33.9%. Response rates for the landline and cellular telephone samples were 55.7% and 32.1%, respectively. Of the 3,385 age-eligible children with completed household interviews from the landline sample, 1,983 (58.6%) had adequate provider data. From the cellular telephone sample, 13,005 of the 24,070 eligible children with completed household interviews had adequate provider data (54.0%).

The overall CASRO response rate for the 2016 NIS-Teen was 32.7%. Response rates for the landline and cellular telephone samples were 55.5% and 29. 5%, respectively. Of the 8,690 age-eligible adolescents with completed household interviews from the landline sample, 4,684 (23%) had adequate provider data. From the cellular telephone sample, 15,791 of the 33,304 (77%) eligible adolescents with completed household interviews had adequate provider data.

Issues Affecting Interpretation

The findings in recent years are subject to several limitations. Data year 2011 was the first year that NIS and NIS-Teen used a dual-frame sampling scheme that included landline and cellular telephone households. Estimates from 2011 and subsequent years might not be comparable with those from prior to 2011, when surveys were conducted via landline telephone only. NIS is a telephone survey, and statistical adjustments might not compensate fully for nonresponse and for households without landline telephones prior to 2011. Underestimates of vaccination coverage might have resulted in exclusive use of provider-reported vaccination histories because completeness of records is unknown. Finally, although national coverage estimates are precise, annual estimates and trends for state and local areas should be interpreted with caution because of smaller sample sizes and wider confidence intervals.

Before January 2009, NIS did not distinguish between Hib vaccine production types; therefore, children who received 3 doses of a vaccine product that requires 4 doses were misclassified as fully vaccinated. For more information, see: CDC. Changes in measurement of Haemophilus influenzae serotype b (Hib) vaccination coverage-National Immunization Survey, United States, 2009. MMWR Morb Mortal Wkly Rep 59(33):1069-72. 2010.

Starting in 2014, NIS-Teen defined an adolescent’s vaccination record as having adequate provider data if that adolescent had vaccination history data from one or more of the named vaccination providers, or if the parent reported that the adolescent was completely unvaccinated. Prior to 2014, the adequate provider data definition had more criteria, and it was based on a comparison of provider report of vaccination history with parental report of vaccination history, either by shot card report or recall.

To assess the effect of the change in the adequate provider definition criteria on vaccination coverage estimates, NIS recomputed estimates from the 2006-2013 survey. In general, 2013 NIS-Teen vaccination coverage estimates using the revised adequate provider data definition were different, and generally lower, than original 2013 NIS-Teen estimates. Differences between revised and original 2013 national vaccination estimates ranged from −0.1 percentage point to −2.2 percentage points. For more information on the revised adequate provider data criteria, see: https://www.cdc.gov/vaccines/imz-managers/coverage/nis/teen/apd-report.html, and for revised 2013 estimates based on the 2014 criteria, see: Reagan-Steiner S, Yankey D, Jeyarajah J, Elam-Evans LD, Singleton JA, Curtis CR, et al. National, regional, state, and selected local area vaccination coverage among adolescents aged 13-17 years-United States, 2014. MMWR Morb Mortal Wkly Rep 64(29):784-92. 2015. Available from: https://www.cdc.gov/mmwr/preview/mmwrhtml/mm6429a3.htm. Because of the revision in the adequate provider definition, NIS-Teen vaccination coverage estimates for 2013 and beyond cannot be directly compared with previously published 2006-2013 NIS-Teen survey vaccination coverage estimates based on the previous adequate provider definition.

References

• Hill HA, Elam-Evans LD, Yankey D, Singleton JA, Kang Y. Vaccination coverage among children aged 19-35 months-United States, 2016. MMWR Morb Mortal Wkly Rep 66(43):1171–7. 2017. Available from: https://www​.cdc.gov/mmwr​/volumes/66/wr/pdfs/mm6643a3-H.pdf. [PMC free article: PMC5689213] [PubMed: 29095807]
• Walker TY, Elam-Evans LD, Singleton JA, Yankey D, Markowitz LE, Fredua B, et al. National, regional, state, and selected local area vaccination coverage among adolescents aged 13-17 years-United States, 2016. MMWR Morb Mortal Wkly Rep 66(33):874–82. 2017. Available from: https://www​.cdc.gov/mmwr​/volumes/66/wr/pdfs/mm6633a2.pdf. [PMC free article: PMC5687818] [PubMed: 28837546]
• Smith PJ, Hoaglin DC, Battaqlia MP, Khare M, Barker LE. Statistical methodology of the National Immunization Survey, 1994-2002. National Center for Health Statistics. Vital Health Stat 2(138). 2005. Available from: https://www​.cdc.gov/nchs​/data/series/sr_02/sr02_138.pdf. [PubMed: 15789691]
• Centers for Disease Control and Prevention. Announcement: Addition of households with only cellular telephone service to the National Immunization Survey, 2011. Available from: https://www​.cdc.gov/mmwr​/preview/mmwrhtml/mm6134a5​.htm?s_cid=mm6134a5_e%0d%0a.
• Centers for Disease Control and Prevention. Changes in measurement of Haemophilus influenzae serotype b (Hib) vaccination coverage-National Immunization Survey, United States, 2009. MMWR Morb Mortal Wkly Rep 59(33):1069–72. 2010. Available from: https://www​.cdc.gov/mmwr​/preview/mmwrhtml/mm5933a3​.htm?s_cid=mm5933a3_e%0d%0a. [PubMed: 20798669]

For More Information

See the NIS website at: https://www.cdc.gov/vaccines/imz-managers/index.html.

Overview

NIPA are a set of economic accounts that provide detailed measures of the value and composition of national output and the incomes generated in the production of that output. Essentially, NIPA provides a detailed snapshot of the myriad transactions that make up the economy, such as buying and selling goods and services, hiring of labor, investing, renting property, and paying taxes. NIPA estimates show U.S. production, distribution, consumption, investment, and saving.

The best-known NIPA measure is the gross domestic product (GDP), which is defined as the market value of the goods, services, and structures produced by the economy in a given period. NIPA calculates GDP as the sum of the final expenditure components: personal consumption expenditures, private fixed investment, change in private inventories, net exports of goods and services, government spending, and government investment. However, GDP is just one of many economic measures presented in NIPA. Another key NIPA indicator presented in Health, United States is the implicit price deflator for GDP.

The conceptual framework of NIPA is illustrated by seven summary accounts: the domestic income and product account, the private enterprise income account, the personal income and outlay account, the government receipts and expenditures account, the foreign transactions current account, the domestic capital account, and the foreign transactions capital account. These summary accounts record a use (or expenditure) in one account for one sector and a corresponding source (or receipt) in an account of another sector or of the same sector. This integrated system provides a comprehensive measure of economic activity in a consistently defined framework without double counting.

Coverage

Source data for NIPA domestic estimates cover all 50 states and the District of Columbia. The U.S. national income and product statistics were first presented as part of a complete and consistent double-entry accounting system in the summer of 1947.

Methodology

NIPA estimates are revised quarterly, annually, and quinquennially. For GDP and most other NIPA series, a set of three current quarterly estimates is released each year. Quarterly estimates provide the first look at the path of U.S. economic activity. Annual revisions of NIPA are usually carried out each summer. These revisions incorporate source data that are based on more extensive annual surveys, on annual data from other sources, and on later revisions to the monthly and quarterly source data, and they generally cover the 3 previous calendar years. Comprehensive revisions are carried out at about 5-year intervals and may result in revisions that extend back many years. These estimates incorporate all of the best available source data, such as data from the quinquennial U.S. Economic Census.

NIPA measures are built up from a wide range of source data using a variety of estimating methods. To ensure consistency and accuracy, NIPA uses various adjustment and estimation techniques to estimate data. Three general types of adjustments are made to the source data that are incorporated into the NIPA estimates. The first consists of adjustments that are needed so that the data conform to appropriate NIPA concepts and definitions. The second type of adjustment involves filling gaps in coverage. The third type of adjustment involves time of recording and valuation. Source data must be adjusted occasionally to account for special circumstances that affect the accuracy of the data. For example, quarterly and monthly NIPA estimates are adjusted seasonally at the detailed-series level when the series demonstrate statistically significant seasonal patterns. Source data may also be used as indicators to extrapolate annual estimates. For more information, see “An Introduction to the National Income and Product Accounts. Methodology Papers: U.S. National Income and Product Accounts,” available from: https://www.bea.gov/scb/pdf/national/nipa/methpap/mpi1_0907.pdf; and “Concepts and Methods of the U.S. National Income and Product Accounts,” available from: https://www.bea.gov/national/pdf/NIPAhandbookch1-4.pdf.

Issues Affecting Interpretation

NIPA source data and estimates are revised frequently. Data are released at different times, estimates are updated as they become available, new concepts and definitions are incorporated, and source data may change due to improvements in collection and new methodologies. As a result, major estimates, such as GDP and its major components, undergo frequent revision, and historical data are changed. For more information, see the BEA (NIPA) website at: https://www.bea.gov/scb/pdf/2013/03%20March/0313_nipa_comprehensive_revision_preview.pdf.

Reference

• U.S. Bureau of Economic Analysis. A guide to the National Income and Product Accounts of the United States. 2006. Available from: https://www​.bea.gov/national​/pdf/nipaguid.pdf.

For More Information

See the BEA website at: https://www.bea.gov/national/index.htm.

Overview

NNDSS is a nationwide collaboration that enables all levels of public health (local, state, territorial, federal, and international) to share health information to monitor, control, and prevent the occurrence and spread of state-reportable and nationally notifiable infectious and some noninfectious diseases and conditions. NNDSS is a multifaceted program that includes the surveillance system for collection, analysis, and sharing of health data, resources, and information about policies and standards, at the local, state, and national levels. NNDSS provides weekly provisional and annual finalized information on the occurrence of diseases defined as notifiable by the Council of State and Territorial Epidemiologists (CSTE). Data include incidence of nationally notifiable reportable diseases, which are reported using uniform surveillance case definitions.

Coverage

Notifiable disease reports are received from health departments in the 50 states, 5 territories, the District of Columbia, and New York City. Policies for reporting notifiable disease cases can vary by disease or reporting jurisdiction, depending on case status classification (i.e., confirmed, probable, or suspect).

Methodology

CDC, in partnership with CSTE, administers NNDSS. Reportable disease surveillance is conducted by public health practitioners at local, state, and national levels to support disease prevention and control. Data on a subset of reportable conditions that have been designated nationally notifiable are then submitted to CDC. The system also provides annual summaries of the finalized data. CSTE and CDC annually review the status of national notifiable disease surveillance and recommend additions or deletions to the list of nationally notifiable diseases, based on the need to respond to emerging priorities. For example, Zika virus disease and Zika virus infection became nationally notifiable in 2016. However, reporting nationally notifiable diseases to CDC is voluntary. Because reporting is currently mandated by law or regulation only at the local and state levels, the list of diseases that are considered reportable varies by state. For example, reporting of coccidioidomycosis to CDC is not done by some states in which this disease is not reportable to local or state authorities.

State epidemiologists report cases of nationally notifiable diseases to CDC, which tabulates and publishes these data in Morbidity and Mortality Weekly Reports (MMWR) and in Summary of Notifiable Diseases, United States (titled Annual Summary before 1985). Beginning in 2016, national notifiable disease data are released via the NNDSS website, available from: www.cdc.gov/nndss/infectious-tables.html.

Issues Affecting Interpretation

NNDSS data must be interpreted in light of reporting practices. Some diseases that cause severe clinical illness (e.g., meningococcal disease, plague, and rabies) are likely reported accurately if diagnosed by a clinician. However, persons who have diseases that are clinically mild and infrequently associated with serious consequences (e.g., salmonellosis) may not seek medical care from a health care provider. Even if these less-severe diseases are diagnosed, they are less likely to be reported.

The degree of completeness of data reporting is also influenced by the diagnostic facilities available, the control measures in effect, public awareness of a specific disease, and the interests, resources, and priorities of state and local officials responsible for disease control and public health surveillance. Finally, factors such as changes in case definitions for public health surveillance, introduction of new diagnostic tests, or discovery of new disease entities can cause changes in disease reporting that are independent of the true incidence of disease.

References

• Centers for Disease Control and Prevention. MMWR: Summary of notifiable infectious diseases. Available from: https://www​.cdc.gov/mmwr/mmwr_nd/index​.html
• Centers for Disease Control and Prevention. National Notifiable Diseases Surveillance System. 2016 annual tables of infectious disease data. 2017. Available from: https://wonder​.cdc.gov​/nndss/nndss_annual_tables_menu.asp.

For More Information

See the NNDSS website at: https://wwwn.cdc.gov/nndss/.

Overview

NSFG gathers information on family life, marriage and divorce, pregnancy, infertility, use of contraception, and men’s and women’s health NSFG provides national data on factors affecting birth and pregnancy rates, adoption, and maternal and infant health. Data collected include sexual activity, marriage, divorce and remarriage, unmarried cohabitation, forced sexual intercourse, contraception and sterilization, infertility, breastfeeding, pregnancy loss, low birthweight, and use of medical care for family planning and infertility.

Coverage

Prior to the 2002 NSFG, the survey population of NSFG included women aged 15-44 in the noninstitutionalized population (household population) of the United States (50 states and the District of Columbia). Starting with the 2002 NSFG, the survey population additionally included men aged 15-44 in the household population. Excluded from the survey population were those living in institutions, such as prisons and long-term psychiatric hospitals, or on military bases. Beginning September 2015, the NSFG survey population was expanded for both men and women from those aged 15-44 to those aged 15-49.

Methodology

NSFG moved from a periodically conducted survey—conducted six times from 1973 to 2002—to a continuous survey design in 2006. NSFG data are currently based on a multistage probability-based, nationally representative sample of the household population aged 15-44, though since September 2015, the sample was expanded to those aged 15-49. Black and Hispanic adults, as well as all persons aged 15-19, are oversampled. Interviews are administered in person by trained female interviewers using a laptop or notebook computer with computer-assisted personal interviewing or audio computer-assisted self-interview programs.

To produce national estimates from the sample for the millions of women aged 15-44 in the United States, data for the interviewed sample women were (a) inflated by the reciprocal of the probability of selection at each stage of sampling, (b) adjusted for nonresponse, and (c) poststratified, or aligned with benchmark population sizes based on data from the U.S. Census Bureau.

For more information on the methodology for prior NSFG surveys, see: https://www.cdc.gov/nchs/nsfg/nsfg_products.htm.

Sample Size and Response Rate

For the 2011-2013 and 2013-2015 NSFG surveys, the sample size for women respondents was 5,601 and 5,699, respectively. The response rate for women respondents was 73% for the 2011-2013 NSFG and 71% for the 2013-2015 NSFG. Sample sizes and response rates for respondents have varied across survey years. For more information on sample size and response rates for past surveys, see the 2013-2015 NSFG user’s guide at: https://www.cdc.gov/nchs/data/nsfg/nsfg_2013_2015_userguide_maintext.pdf.

References

• National Center for Health Statistics. Public use data file documentation, 2011-2013: National Survey of Family Growth user’s guide. 2014. Available from: https://www​.cdc.gov/nchs​/data/nsfg/nsfg_2011-2013​_userguide_maintext.pdf.
• National Center for Health Statistics. Public use data file documentation, 2013-2015: National Survey of Family Growth user’s guide. 2016. Available from: https://www​.cdc.gov/nchs​/data/nsfg/nsfg_2013​_2015_userguide_maintext.pdf.

For More Information

See the NSFG website at: https://www.cdc.gov/nchs/nsfg/index.htm.

Overview

NSDUH reports on the prevalence, incidence, and patterns of illicit drug use and alcohol use among the U.S. civilian noninstitutionalized population aged 12 and over. NSDUH also reports on substance use disorders, substance use treatment, mental health problems, and mental health care.

Coverage

NSDUH is representative of persons aged 12 and over in the civilian noninstitutionalized population of the United States, and in each state and the District of Columbia (D.C.)

The survey covers residents of households (including those living in houses, townhouses, apartments, and condominiums), persons in noninstitutional group quarters (including those in shelters, boarding houses, college dormitories, migratory work camps, and halfway houses), and civilians living on military bases. Persons excluded from the survey include people experiencing homelessness who do not use shelters, active military personnel, and residents of institutional group quarters such as jails, nursing homes, mental institutions, and long-term care hospitals.

Methodology

Data are collected via in-person interviews conducted with a sample of individuals at their place of residence. Computer-assisted interviewing methods, including audio computer-assisted self-interviewing, are used to provide a private and confidential setting to complete the interview.

NSDUH uses a 50-state (and D.C.) sample design that is revised periodically. In 2014, NSDUH introduced an independent multistage area probability sample within each state and D.C. States are the first level of stratification, and each state was then stratified into approximately equally populated state sampling regions (SSRs). Census tracts within each SSR were then selected, followed by census block groups within census tracts and area segments (i.e., a collection of census blocks) within census block groups. Finally, dwelling units (DUs) were selected within segments, and within each selected DU, up to two residents who were at least 12 years old were selected for the interview.

Also starting in 2014, changes were made in the sample sizes allocated to each state and to different age groups, in order to increase the precision of national estimates, many state estimates, and estimates for older adults. In particular, samples sizes were increased in the 12 most populous states. States with sample increases will have more precise estimates than in previous years, whereas states with smaller sample sizes will have some reductions in precision However, all states will still have reasonable levels of precision. This allocation of sample to states is also thought to be more cost efficient. Starting in 2014, the sample size was redistributed by age group so that 25% of the sample is allocated to those aged 12-17, 25% to those aged 18-25, and 50% to those aged 26 and over. Although the sample sizes for age groups 12-17 and 18-25 were reduced, these two groups are still considered to be oversampled since they represent approximately 10% and 13% of the total population, respectively.

Sample Size and Response Rate

In 2016, screening was completed at 135,188 addresses, and 67,942 completed interviews were obtained, including 17,109 interviews from adolescents aged 12-17 and 50,833 interviews from adults aged 18 and over. Weighted response rates for household screening and for interviewing were 77.9% and 68.4%, respectively, for an overall response rate of 53.3% for people aged 12 and over. The weighted interview response rates were 77.0% for adolescents and 67.6% for adults.

Issues Affecting Interpretation

Several improvements to NSDUH were implemented in 2002. The data collected in 2002 represent a new baseline for tracking trends in substance use and other measures. Special questions on methamphetamine were added in 2005 and 2006. Data for years prior to 2007 were adjusted for comparability. Starting with 2011 data, 2010 Census-based control totals were used in the weighting process. Analysis weights in the 2002 through 2010 NSDUHs were derived from the 2000 Census data. This reweighting to the 2010 Census data could affect comparisons between estimates for 2011 and subsequent years and those from prior years. However, an analysis of the impact of reweighting showed that the percentages of substance users were largely unaffected. For more information, see: https://archive.samhsa.gov/data/NSDUH/NSDUHCensusEffects/Index.aspx.

The NSDUH questionnaire underwent a partial redesign in 2015 to improve the quality of data and to address the changing needs of policymakers and researchers with regard to substance use and mental health issues. Due to the changes, only 2015 and 2016 data are presented for certain estimates until comparability with prior years can be established. Trends continue to be presented for estimates that are assumed to have remained comparable with those in earlier years. For more information, see: https://www.samhsa.gov/data/sites/default/files/NSDUHTrendBreak-2015.pdf.

Estimates of substance use for youth based on NSDUH are not directly comparable with estimates based on the Monitoring the Future (MTF) Study and the Youth Risk Behavior Surveillance System (YRBSS). In addition to the fact that MTF excludes dropouts and absentees, rates are not directly comparable across these surveys because of differences in the populations covered, sample design, questionnaires, and interview setting. NSDUH collects data in residences, whereas MTF and YRBSS collect data in school classrooms. Furthermore, NSDUH estimates are tabulated by age, whereas MTF and YRBSS estimates are tabulated by grade, representing different ages as well as different populations.

References

• Ahrnsbrak R, Bose J, Hedden SL, Lipari RN, Park-Lee E. Key substance use and mental health indicators in the United States: Results from the 2016 National Survey on Drug Use and Health. 2017. Available from: https://www​.samhsa.gov​/data/sites/default​/files/NSDUH-FFR1-2016/NSDUH-FFR1-2016​.pdf.
• Substance Abuse and Mental Health Services Administration. Results from the 2016 National Survey on Drug Use and Health: Detailed tables. 2017. Available from: https://www​.samhsa.gov​/data/sites/default​/files/NSDUH-DetTabs-2016​/NSDUH-DetTabs-2016.htm.

For More Information

See the NSDUH website at: https://www.samhsa.gov/data/data-we-collect/nsduh-national-survey-drug-use-and-health, and the Center for Behavioral Health Statistics and Quality (the data collection agency) website at: https://www.samhsa.gov/about-us/whowe-are/offices-centers/cbhsq.

Overview

NVSS collects and publishes official national statistics on births, deaths, fetal deaths, and, prior to 1996, marriages and divorces occurring in the United States, based on U.S. Standard Certificates. Fetal deaths are classified and tabulated separately from other deaths. The vital statistics files—Birth, Fetal Death, Mortality Multiple Cause-of-Death, Linked Birth/Infant Death, and Compressed Mortality—are described in detail below.

Coverage

NVSS collects and presents U.S. resident data for the aggregate of 50 states, New York City, and the District of Columbia (D.C.), as well as for each individual state, D.C., and the U.S. dependent areas of Puerto Rico, Virgin Islands, Guam, American Samoa, and Northern Marianas. Vital events occurring in the United States to non-U.S. residents and vital events occurring abroad to U.S. residents are excluded. Starting with Health, United States, 2013, information on vital events for Puerto Rico, Virgin Islands, Guam, American Samoa, and Northern Marianas is shown in selected state tables but is not included in U.S. totals.

Methodology

NCHS’ Division of Vital Statistics obtains information on births and deaths from the registration offices of each of the 50 states, New York City, D.C., Puerto Rico, Virgin Islands, Guam, American Samoa, and Northern Marianas. Until 1972, microfilm copies of all death certificates and a 50% sample of birth certificates were received from all registration areas and processed by NCHS. In 1972, some states began sending their data to NCHS through the Cooperative Health Statistics System (CHSS). States that participated in the CHSS program processed 100% of their death and birth records and sent the entire data file to NCHS on computer tapes. Currently, data are sent to NCHS following procedures similar to those under CHSS. The number of participating states grew from 6 in 1972 to 46 in 1984. Starting in 1985, all 50 states and D.C. participated in the Vital Statistics Cooperative Program.

U.S. Standard Certificates

U.S. Standard Certificates of Live Birth and Death and Fetal Death Reports are revised periodically, allowing evaluation and addition, modification, and deletion of items. Beginning with 1989, revised Standard Certificates replaced the 1978 versions. The 1989 revision of the death certificate included items on educational attainment and Hispanic origin of decedents, as well as changes to improve the medical certification of cause of death. Standard Certificates recommended by NCHS are modified in each registration area to serve the area’s needs. However, most certificates conform closely in content and arrangement to the Standard Certificate, and all certificates contain a minimum data set specified by NCHS. The 2003 revision of vital records went into effect in some states and territories beginning in 2003; full implementation in all states, D.C., and territories (other than American Samoa) was achieved with 2016 data. The 2003 revision of the death certificate included changes in the determination of multiple races, education level, prenatal care, tobacco use, and maternal mortality.

Overview

Vital statistics natality data are a fundamental source of demographic, geographic, and medical and health information on all births occurring in the United States. This is one of the few sources of comparable health-related data for small geographic areas over an extended time period. The data are used to present the characteristics of babies and their mothers, track trends such as birth rates for teenagers, and compare natality trends with those in other countries.

The Birth file includes characteristics of the baby, such as sex, birthweight, and weeks of gestation; demographic information about the parents, such as age, race, Hispanic origin, parity, educational attainment, marital status, and state of residence; medical and health information, such as prenatal care, based on hospital records; and behavioral risk factors for the birth, such as mother’s tobacco use during pregnancy.

Coverage

Birth data presented in Health, United States are based on reporting from all 50 states and D.C. Data for Puerto Rico, Virgin Islands, Guam, American Samoa, and Northern Marianas are shown in selected state tables but are not included in U.S. totals. Beginning with 1970, births to nonresidents of the United States are excluded.

Methodology

In the United States, state laws require birth certificates to be completed for all births. The registration of births is the responsibility of the professional attendant at birth, generally a physician or midwife. The birth certificate must be filed with the local registrar of the district in which the birth occurs. Each birth must be reported promptly; the reporting requirements vary from state to state, ranging from 24 hours to as much as 10 days after the birth.

Federal law mandates national collection and publication of birth and other vital statistics data. NVSS is the result of cooperation between NCHS and the states to provide access to statistical information from birth certificates. Standard forms for the collection of the data, and model procedures for the uniform registration of the events, are developed and recommended for state use through cooperative activities of the states and NCHS. NCHS shares the costs incurred by the states in providing vital statistics data for national use.

Issues Affecting Interpretation

The 2003 revision of the birth certificate was phased in from 2003 to 2016. As of January 1, 2016, all states, territories (except American Samoa), and reporting areas had adopted the 2003 revision of the U.S. Standard Certificate of Live Birth. The 2003 certificate uses revised race and ethnicity sections conforming to the 1997 Revisions to the Standards for the Classification of Federal Data on Race and Ethnicity. However, to provide uniformity and comparability of data for trend comparison, bridged single-race categories are still presented in Health, United States. Interpretation of trend data should take into consideration changes to reporting areas. For methodological and reporting area changes for the following birth certificate items, see Appendix II, Age; Hispanic origin; Marital status; Race.

For More Information

See the NVSS Birth Data website at: https://www.cdc.gov/nchs/nvss/births.htm, and Vitalstats at: https://www.cdc.gov/nchs/data_access/Vitalstatsonline.htm.

Overview

Fetal mortality refers to the intrauterine death of a fetus at any gestational age. In Health, United States, data are presented for fetal deaths at 20 weeks or more. The Fetal Death data set includes characteristics of the fetus, such as sex, birthweight, and weeks of gestation; demographic information about the mother, such as age, race, Hispanic origin, and live-birth order; and medical and health information, such as maternal diabetes and hypertension.

Coverage

Data presented in Health, United States are based on reporting from all 50 states and D.C. Data for Puerto Rico, Virgin Islands, Guam, American Samoa, and Northern Marianas are not included in U.S. totals but are included in the fetal death user’s guides, available from the NCHS website at: https://www.cdc.gov/nchs/data_access/VitalStatsOnline.htm, and in periodic reports.

Methodology

Fetal death means the death of a fetus prior to delivery from the mother, irrespective of the duration of pregnancy. Fetal deaths do not include induced terminations of pregnancy This definition of fetal death, adopted by NCHS as the nationally recommended standard, is based on the definition published by the World Health Organization (WHO) in 1950 and revised in 1988. The term fetal death encompasses other commonly used terms, including stillbirth, spontaneous abortion, and miscarriage. All U.S. states and registration areas have definitions similar to the standard definition, except for Puerto Rico and Wisconsin, which have no formal definition.

State laws require the reporting of fetal deaths, and federal law mandates national collection and publication of fetal death data. States and reporting areas submit fetal mortality data to NCHS as part of a cooperative agreement. Standard forms and procedures for the collection of the data are developed and recommended for state use through cooperative activities of the states and NCHS. NCHS shares the costs incurred by the states in providing vital statistics data for national use.

In addition to fetal mortality rates, perinatal mortality rates are also presented in Health, United States. Perinatal mortality includes both late fetal deaths (of at least 28 weeks of gestation) and early infant (neonatal) deaths (within 7 days of birth). Data on early infant deaths come from the Linked Birth/Infant Death data set.

Issues Affecting Interpretation

Reporting requirements for fetal deaths vary by state, and these differences have important implications for comparisons of fetal mortality rates by state. The majority of states require reporting of fetal deaths at 20 weeks of gestation or more, or a minimum of 350 grams birthweight (roughly equivalent to 20 weeks), or some combination of the two. In 2015, six states required reporting of fetal deaths at all periods of gestation, and one state required reporting beginning at 16 weeks of gestation. Further, one state required the reporting of fetal deaths with birthweights of 500 grams or more (roughly equivalent to 22 weeks of gestation).

Starting with 2014 data, the obstetric estimate of gestation at delivery (OE) is used to determine gestational age, instead of the last normal menses (LMP), which was used for earlier years. The adoption of OE for gestational age had no or negligible impact on total fetal mortality rates. However, late fetal mortality rates based on the OE were lower than those based on the LMP. For more information, see “User Guide to the 2014 Fetal Death Public Use File.”

There is substantial evidence that not all fetal deaths for which reporting is required are, in fact, reported. Underreporting of fetal deaths is most likely to occur in the earlier part of the required reporting period for each state. For example, in 2013, for those states requiring reporting of fetal deaths at all periods of gestation, 56.4% of fetal deaths at 20 weeks of gestation or more were at 20-27 weeks, whereas for states requiring reporting of fetal deaths of 500 grams or more, only 33.8% were at 20-27 weeks, thus indicating substantial underreporting of early fetal deaths in some states.

References

• National Center for Health Statistics. User guide to the 2015 fetal death public use file. Available from: ftp://ftp​.cdc.gov/pub​/Health_Statistics/NCHS​/Dataset_Documentation​/DVS/fetaldeath​/2015FetalUserGuide.pdf
• MacDorman MF, Gregory ECW. Fetal and perinatal mortality: United States, 2013. National Vital Statistics Reports; vol 64 no 8. Hyattsville, MD: National Center for Health Statistics. 2015. Available from: https://www​.cdc.gov/nchs​/data/nvsr/nvsr64/nvsr64_08.pdf. [PubMed: 26222771]
• Gregory ECW, MacDorman MF, Martin JA. Trends in fetal and perinatal mortality in the United States, 2006-2012. NCHS Data Brief, no 169. Hyattsville, MD: National Center for Health Statistics. 2014. Available from: https://www​.cdc.gov/nchs​/data/databriefs/db169.pdf.

For More Information

See the NCHS Fetal Deaths data website at: http://www.cdc.gov/nchs/fetal_death.htm.

Overview

Vital statistics mortality data are a fundamental source of demographic, geographic, and underlying and multiple cause-of-death information. Multiple cause-of-death data reflect all medical information reported on death certificates and complement traditional underlying cause-of-death data. Multiple-cause data give information on diseases that are a factor in death, whether or not they are the underlying cause of death; on associations among diseases; and on injuries leading to death.

The Mortality multiple cause-of-death file includes demographic information on age, sex, race, Hispanic origin, state of residence, and educational attainment, as well as medical information on causes of death. This data set is one of the few sources of comparable health-related data for small geographic areas over an extended time period. The data are used to present the characteristics of those dying in the United States, to determine life expectancy, and to compare mortality trends with those in other countries.

Coverage

Mortality data presented in Health, United States are based on reporting from all 50 states and D.C. Data for Puerto Rico, Virgin Islands, Guam, American Samoa, and Northern Marianas are shown in selected state tables, but are not included in U.S. totals. Beginning with 1970, mortality statistics for the United States exclude deaths of U.S. nonresidents. Mortality statistics for Puerto Rico, Virgin Islands, American Samoa, and Northern Marianas excluded deaths of nonresidents for each area. For Guam, mortality statistics exclude deaths that occurred to a resident of any place other than Guam or the United States (50 states and D.C.).

Methodology

By law, the registration of deaths is the responsibility of the funeral director. The funeral director obtains demographic data for the death certificate from an informant. The physician in attendance at the death is required to certify the cause of death. Where cause of death is from other than natural causes, a coroner or medical examiner may be required to examine the body and certify the cause of death.

NCHS is responsible for compiling and publishing annual national statistics on causes of death. In carrying out this responsibility, NCHS adheres to WHO Nomenclature Regulations. These regulations require (a) that cause of death be coded in accordance with the applicable revision of the International Classification of Diseases (ICD) (see Appendix II, International Classification of Diseases [ICD]; Table III); and (b) that underlying cause of death be selected in accordance with international rules. Traditionally, national mortality statistics have been based on a count of deaths, with one underlying cause assigned for each death.

Prior to 1968, mortality medical data were based on manual coding of an underlying cause of death for each certificate in accordance with WHO rules. Starting with 1968, NCHS converted to computerized coding of the underlying cause and manual coding of all causes (multiple causes) on the death certificate. In this system, called Automated Classification of Medical Entities (ACME), multiple-cause codes serve as inputs to the computer software, which employs WHO rules to select the underlying cause. ACME is used to select the underlying cause of death for all death certificates in the United States, and cause-of-death data in Health, United States are coded using ACME.

In addition, NCHS has developed two computer systems as inputs to ACME. Beginning with 1990 data, the Mortality Medical Indexing, Classification, and Retrieval system (MICAR) was introduced to automate coding of multiple causes of death. MICAR provides more detailed information on the conditions reported on death certificates than is available through the ICD code structure. Then, beginning with data year 1993, SuperMICAR, an enhancement of MICAR, was introduced. SuperMICAR allows for literal entry of the multiple cause-of-death text as reported by the certifier. This information is then processed automatically by the MICAR and ACME computer systems. Records that cannot be processed automatically by MICAR or SuperMICAR are multiple-cause-coded manually and then further processed through ACME. Starting in 2003, SuperMICAR was used to process all of the country’s death records.

Data for the entire United States refer to events occurring within the 50 states and D.C.; data for geographic areas are by place of residence. For methodological and reporting area changes for the following death certificate items, see Appendix II, Hispanic origin; Race.

Issues Affecting Interpretation

ICD, by which cause of death is coded and classified, is revised approximately every 10 to 20 years. Because revisions of ICD may cause discontinuities in trend data by cause of death, comparison of death rates by cause of death across ICD revisions should be done with caution and with reference to the comparability ratio (see Appendix II, Comparability ratio). Prior to 1999, modifications to ICD were made only when a new revision of ICD was implemented. A process for updating ICD was introduced with the 10th revision (ICD-10) that allows for midrevision changes. These changes, however, may affect comparability of data between years for select causes of death. Minor changes may be implemented every year, whereas major changes may be implemented every 3 years (e.g., 2003 data year). In data year 2006, major changes were implemented, including the addition and deletion of several ICD codes. For more information, see Heron et al.

Multiple-cause data were obtained from all certificates for 1968-1971, 1973-1980, and 1983-present. Data were obtained from a 50% sample of certificates for 1972. Multiple-cause data for 1981 and 1982 were obtained from a 50% sample of certificates from 19 registration areas. For the other states, data were obtained from all certificates.

The death certificate has been revised periodically. A revised U.S. Standard Certificate of Death was recommended for state use beginning January 1, 1989. Among the changes were the addition of a new item on educational attainment and Hispanic origin of the decedent and changes to improve the medical certification of cause of death. The U.S. Standard Certificate of Death was revised again in 2003; states are adopting this new certificate on a rolling basis.

The 2003 revision permits reporting of more than one race (multiple races). This change was implemented to reflect the increasing diversity of the U.S. population and to be consistent with the decennial census. Some states, however, are still using the 1989 revision of the U.S. Standard Certificate of Death, which allows only a single race to be reported. Until all states adopt the new death certificate, the race data reported using the 2003 revision are “bridged” for those for whom more than one race was reported (multiple race) to one single race, to provide comparability with race data reported on the 1989 revision. For more information on the impact of the 2003 certificate revisions on mortality data presented in Health, United States, see Appendix II, Race.

References

• Murphy SL, Xu JQ, Kochanek KD, Curtin SC, Arias E. Deaths: Final data for 2015. National Vital Statistics Reports; vol 66 no 6. Hyattsville, MD: National Center for Health Statistics. 2017. Available from: https://www​.cdc.gov/nchs​/data/nvsr/nvsr66/nvsr66_06.pdf.
• Kochanek KD, Murphy SL, Xu JQ, Tejada-Vera B. Deaths: Final data for 2014. National Vital Statistics Reports; vol 65 no 4. Hyattsville, MD: National Center for Health Statistics. 2016. Available from: https://www​.cdc.gov/nchs​/data/nvsr/nvsr65/nvsr65_04.pdf.
• Heron MP, Hoyert DL, Murphy SL, Xu JQ, Kochanek KD, Tejada-Vera B. Deaths: Final data for 2006. National Vital Statistics Reports; vol 57 no 14. Hyattsville, MD: National Center for Health Statistics. 2009. Available from: https://www​.cdc.gov/nchs​/data/nvsr/nvsr57/nvsr57_14.pdf.
• National Center for Health Statistics. Multiple causes of death in the United States. Monthly Vital Statistics Report; vol 32 no 10 supplement 2. Hyattsville, MD: National Center for Health Statistics. 1984. Available from: https://www​.cdc.gov/nchs​/data/mvsr/supp/mv32_10s2.pdf.

For More Information

See the NCHS Mortality Data website at: https://www.cdc.gov/nchs/deaths.htm.

Overview

National linked files of live births and infant deaths are used for research on infant mortality. The Linked Birth/Infant Death data set links information from the birth certificate to information from the death certificate for each infant death in the United States. The purpose of the linkage is to use the many additional variables from the birth certificate, including the more accurate racial and ethnic data, for more detailed analyses of infant mortality patterns. The Linked Birth/Infant Death data set includes all variables on the natality (Birth) file, including racial and ethnic information, birthweight, and maternal smoking, as well as variables on the Mortality file, including cause of death and age at death.

Coverage

To be included in the U.S. linked file, both the birth and death must have occurred in the 50 states, D.C., Puerto Rico, Virgin Islands, or Guam. Data for Puerto Rico, Virgin Islands, and Guam are shown in selected state tables but are not included in U.S. totals. Linked birth/infant death data are not available for American Samoa and Northern Marianas.

Methodology

Infant deaths are defined as a death before the infant’s first birthday. About 98%-99% of infant death records can be linked to their corresponding birth certificates. The linkage makes available extensive information from the birth certificate about the pregnancy, maternal risk factors, infant characteristics, and health items at birth that can be used for more detailed analyses of infant mortality. The linked file is used for calculating infant mortality rates by race and ethnicity, which are more accurately measured from the birth certificate.

Starting with 1995 data, linked birth/infant death data files are available in two different formats: period data and birth cohort data. The numerator for the period linked file consists of all infant deaths occurring in a given data year linked to their corresponding birth certificates, whether the birth occurred in that year or the previous year. The numerator for the birth cohort linked file consists of deaths to infants born in a given year. In both cases, the denominator is all births occurring in the year. For example, the 2013 period linked file contains a numerator file that consists of all infant deaths occurring in 2013 that have been linked to their corresponding birth certificates, whether the birth occurred in 2012 or 2013. In contrast, the 2013 birth cohort linked file will contain a numerator file that consists of all infant deaths to babies born in 2013, whether the death occurred in 2013 or 2014. Although the birth cohort format has methodological advantages, it creates substantial delays in data availability because it is necessary to wait until the close of the following data year to include all infant deaths in the birth cohort. Starting with 1995 data, period linked files are used for infant mortality rate tables in Health, United States

Other changes to the data set starting with 1995 include the addition of record weights to compensate for the 1%-2% of infant death records that could not be linked to their corresponding birth records. In addition, not-stated birthweight was imputed if the period of gestation was known. This imputation was done to improve the accuracy of birthweight-specific infant mortality rates because the percentage of records with not-stated birthweight is generally higher for infant deaths (4. 08% in 2015) than for live births (0.09% in 2015). In 2015, not-stated birthweight was imputed for 0.07% of births.

Issues Affecting Interpretation

Period linked file data starting with 1995 are not strictly comparable with birth cohort data for 1983-1991. A new revision of the birth certificate was introduced in 2003, and as of 2016 data, all states and reporting areas (except for American Samoa) had adopted the 2003 version of the birth certificate.

References

• Mathews TJ, Driscoll AK. Trends in infant mortality in the United States, 2005-2014. NCHS Data Brief, no 279. Hyattsville, MD: National Center for Health Statistics. 2017. Available from: https://www​.cdc.gov/nchs​/data/databriefs/db279.pdf. [PubMed: 28437240]
• Mathews TJ, MacDorman MF, Thoma ME. Infant mortality statistics from the 2013 period linked birth/infant death data set. National Vital Statistics Reports; vol 64 no 9. Hyattsville, MD: National Center for Health Statistics. 2015. Available from: https://www​.cdc.gov/nchs​/data/nvsr/nvsr64/nvsr64_09.pdf. [PubMed: 26270610]

For More Information

See the NCHS Linked Birth and Infant Death Data website at: http://www.cdc.gov/nchs/linked.htm.

Overview

NYTS is an annual school-based survey of U.S. middle and high school students that collects data on tobacco use and tobacco-related attitudes, beliefs, and influences. Data collected include use of cigarettes, cigars, smokeless tobacco, e-cigarettes, hookahs, pipe tobacco, and bidis within the past 30 days.

Coverage

Data are nationally representative of 6th through 12th graders in public and private high schools in the United States.

Methodology

Prior to 2011, the survey was biennial. The survey uses a three-stage cluster sampling design to generate a nationally representative sample of U.S. students attending public and private schools in grades 6 through 12. Data are collected using a voluntary, school-based, self-administered, pencil-and-paper questionnaire. Dropouts and students who are absent from school or class at the time of data collection are excluded. Data were weighted to account for the complex survey design and adjusted for nonresponse.

Sample Size and Response Rate

In 2016, a total of 20,675 students in 202 public and private schools in the United States participated, with a response rate of 72%. The 20,675 participants were broken down by grade as follows: 2,692 12th graders, 2,698 11th graders, 2,831 10th graders, 2,751 9th graders, 3,192 8th graders, 3,272 7th graders, and 3,239 6th graders. From 2011 to 2016, sample sizes ranged from 18,866 to 20,675 students, and response rates were 63% to 74%

Issues Affecting Interpretation

Estimates of substance use among youth based on NYTS are not directly comparable with estimates based on the National Survey on Drug Use and Health (NSDUH), the Monitoring the Future (MTF) Study, and the Youth Risk Behavior Surveillance System (YRBSS). This is because of differences in populations covered, sample design, questionnaires, interview settings, and data cleaning procedures NSDUH collects data in residences, whereas NYTS, MTF, and YRBSS collect data in school classrooms. In addition, NSDUH estimates are tabulated by age, whereas NYTS, MTF, and YRBSS estimates are tabulated by school level or grade, representing different ages as well as different populations.

For More Information

See the NYTS website at: https://www.cdc.gov/tobacco/data_statistics/surveys/nyts/index.htm.

Overview

The OES program conducts a semiannual survey designed to produce estimates of employment and wages for specific occupations. The program collects data on wage and salary workers in nonfarm establishments, producing employment and wage estimates for over 800 occupations. The OES program produces these occupational estimates for all industries combined at different geographic levels: for the country; the 50 states and the District of Columbia (D.C.); metropolitan and nonmetropolitan areas; and Guam, Puerto Rico, and the U.S. Virgin Islands. National occupational employment and wage estimates are also available by industry for more than 430 industry aggregations and by public or private ownership across all industries and for schools and hospitals.

Coverage

The OES survey covers all full-time and part-time wage and salary workers in nonfarm establishments. The survey does not cover the self-employed, owners and partners in unincorporated firms, household workers, or unpaid family workers.

Methodology

The OES program surveys approximately 200,000 establishments per panel (every 6 months), taking 3 years to fully collect the sample of 1.2 million establishments. The estimates for occupations in nonfarm establishments are based on OES data collected for the reference months of May and November. May 2016 employment and wage estimates are based on all data collected from establishments sampled in the May 2016, May 2015, November 2015, May 2014, November 2014, and November 2013 semiannual panels. The overall national response rate for the six panels, based on the 50 states and D.C., is 73% based on establishments and 69% based on weighted sampled employment.

The OES survey is a federal-state cooperative program between BLS and state workforce agencies (SWAs). BLS provides the procedures and technical support, draws the sample, and produces the survey materials, while SWAs collect most of the data. SWAs from all 50 states and D.C., Puerto Rico, Guam, and the U.S. Virgin Islands participate in the survey. Occupational employment and wage rate estimates at the national level are produced by BLS using data from the 50 states and D.C. Employers who respond to states’ requests to participate in the OES survey make these estimates possible.

Issues Affecting Interpretation

Over time, OES data have had changes in the occupational, industrial, and geographical classification systems; data collection methods; survey reference period; and mean wage estimation methodology. Because of these changes as well as permanent features of the OES methodology, caution should be used in trend analysis.

OES occupational estimates are based on the Office of Management and Budget’s Standard Occupational Classification (SOC) system. The OES survey classifies workers into more than 800 detailed occupations; these detailed occupations are aggregated into 23 SOC major groups. Only 22 SOC major groups are included in OES; major group 55, Military Specific Occupations, is not included. Data on selected health care occupations are presented in Health, United States.

OES estimates for 1999 to 2009 classified occupations according to the 2000 SOC system. OES estimates for 2010 and 2011 were based on a hybrid structure using both the 2000 and 2010 SOC systems. For more information about the hybrid structure, see https://www.bls.gov/oes/oes_ques.htm OES estimates for 2012 to 2016 classified occupations according to the 2010 SOC system.

For More Information

See the OES website at: https://www.bls.gov/OES.

Decennial Census

The census of population (decennial census) has been held in the United States every 10 years since 1790. Since 1930, it has enumerated the resident population as of April 1 of the census year. Data on sex, race, Hispanic origin, age, and marital status are collected from 100% of the enumerated population.

Race Data on the 1990 Census

The question on race on the 1990 Census was based on the Office of Management and Budget’s (OMB) 1977 Race and Ethnic Standards for Federal Statistics and Administrative Reporting (Statistical Policy Directive 15). This document specified rules for the collection, tabulation, and reporting of racial and ethnic data within the federal statistical system. The 1977 Standards required federal agencies to report race-specific tabulations using four single-race categories: American Indian or Alaska Native, Asian or Pacific Islander, black, and white. Under the 1977 Standards, race and ethnicity were considered to be two separate and distinct concepts. Thus, persons of Hispanic origin may be of any race.

Race Data on the 2000 Census

The question on race on the 2000 Census was based on OMB’s 1997 Revisions to the Standards for the Classification of Federal Data on Race and Ethnicity (see: Federal Register 62(210):58782-90. 1997.). (Also see Appendix II, Race.) The 1997 Standards incorporated two major changes in the collection, tabulation, and presentation of race data. First, the 1997 Standards increased the minimum set of categories to be used by federal agencies for identification of race from four to five: American Indian or Alaska Native, Asian, black or African American, Native Hawaiian or Other Pacific Islander, and white. Second, the 1997 Standards included the requirement that federal data collection programs allow respondents to select one or more race categories when responding to a query on their racial identity. This provision means that there are potentially 31 race groups, depending on whether an individual selects one, two, three, four, or all five of the race categories. The 1997 Standards continue to call for use, when possible, of a separate question on Hispanic or Latino ethnicity and specify that the ethnicity question should appear before the question on race. Thus, under the 1997 Standards, as under the 1977 Standards, persons of Hispanic origin may be of any race.

Race Data on the 2010 Census

Similar to race data on the 2000 Census, the question on race on the 2010 Census was based on OMB’s 1997 Revisions to the Standards for the Classification of Federal Data on Race and Ethnicity (see: Federal Register 62(210):58782-90. 1997.). (Also see Appendix II, Race.) The 1997 Standards required a minimum set of categories to be used by federal agencies for identification of race: American Indian or Alaska Native, Asian, black or African American, Native Hawaiian or Other Pacific Islander, and white, and require that federal data collection programs allow respondents to select one or more race categories when responding to a query on their racial identity. The 1997 Standards continue to call for use, when possible, of a separate question on Hispanic or Latino ethnicity and specify that the ethnicity question should appear before the question on race. Thus, under the 1997 Standards, as under the 1977 Standards, persons of Hispanic origin may be of any race.

Modified Decennial Census Files

For several decades, the U.S. Census Bureau has produced Modified Decennial Census files. These modified files incorporate adjustments to the 100% April 1 count data for (a) errors in the census data discovered subsequent to publication, (b) misreported age data, and (c) nonspecified race.

For the 1990 Census, the U.S. Census Bureau modified the age, race, and sex data on the census and produced the Modified Age-Race-Sex (MARS) file. The differences between the population counts in the original census file and the MARS file are primarily due to modification of the race data. Of the 248.7 million persons enumerated in 1990, 9.8 million did not specify their race (more than 95% were of Hispanic origin). For the 1990 MARS file, these persons were assigned the race reported by a nearby person with an identical response to the Hispanic-origin question.

For the 2000 and 2010 Censuses, the U.S. Census Bureau modified the race data and produced the Modified Race Data Summary files. For these files, persons who did not report a race (reported only the category “Some other race”) as part of their race response were assigned by imputation to one of the 31 race groups, which are the single- and multiple-race combinations of the five race categories specified in the 1997 OMB race and ethnicity standards. For the 2000 Census, 97% of the 15.4 million persons who did not report a race were of Hispanic origin. Because a large proportion of those identifying their race as “Some other race” are Hispanic, for the 2010 Census, a new instruction was added that, for the census, Hispanic origins are not races. For the 2010 Census, 97% of the 19.1 million persons who did not report a race (reported only the category “Some other race”) were of Hispanic origin.

Postcensal Population Estimates

Postcensal population estimates are estimates made for the years following a census, before the next census is taken. Postcensal population estimates are derived annually by updating the resident population enumerated in the decennial census using a components-of-population-change approach. Each annual series includes estimates for the current data year and revised estimates for the earlier years in the decade. The following formula is used to derive national estimates for a given year from those for the previous year, starting with the decennial census enumerated resident population as the base:

Resident population estimate

+ births to U.S. resident women

- deaths to U.S. residents

+ net international migration

The postcensal estimates are consistent with official decennial census figures and do not reflect estimated decennial census under-enumeration.

Estimates for the earlier years in a given series are revised to reflect changes in the components-of-change data sets (for example, births to U.S. resident women from a preliminary natality file are replaced with counts from a final natality file). To help users keep track of which postcensal estimate is being used, each annual series is referred to as “vintage,” and the last year in the series is used to name the series. For example, both the vintage 2011 and the vintage 2012 postcensal series have revised estimates for July 1, 2011, but the estimates for July 1, 2011, from the vintage 2011 and vintage 2012 postcensal series differ.

The U.S. Census Bureau also produces postcensal estimates of the resident population of states and counties, using the components-of-population-change method. An additional component of population change—net internal migration—is involved.

Intercensal Population Estimates

Intercensal population estimates are estimates made for the years between two decennial censuses and are produced once the census at the end of the decade has been completed. They replace the postcensal estimates produced prior to the completion of the census at the end of the decade. Intercensal estimates are more accurate than postcensal estimates because they are based on both the census at the beginning and the census at the end of the decade. They are derived by adjusting the final postcensal estimates for the decade to correct for the error of closure (the difference between the estimated population at the end of the decade and the census count for that date). The patterns of population change observed over the decade are preserved. The intercensal estimates for the 1990s were produced using the same methodology used to generate the intercensal estimates for the 1980s. The revised intercensal population estimates for 2000-2009 were produced using a modified version of the methodology used previously Vital rates calculated using postcensal population estimates are routinely revised when intercensal estimates become available.

Bridged-race Population Estimates

Race data on the 2000 and 2010 Censuses are not comparable with race data on other data systems that are continuing to collect data using the 1977 OMB Standards on race and ethnicity during the transition to full implementation of the 1997 OMB Standards. For example, states are implementing the revised birth and death certificates—which have race and ethnicity items that are compliant with the 1997 OMB Standards—at different times, and to date, some states are still using the 1989 death certificates that collect race and ethnicity data in accordance with the 1977 OMB Standards. Thus, population estimates for 1990 and beyond with race categories comparable with the 1977 OMB categories are needed so that race-specific birth and death rates can be calculated. To meet this need, the National Center for Health Statistics (NCHS), in collaboration with the U.S. Census Bureau, developed methodology to bridge the 31 race groups in Census 2000 and Census 2010 to the four single-race categories specified under the 1977 OMB Standards. As of January 1, 2016, all states and D.C., in addition to Puerto Rico, the U.S. Virgin Islands, Guam, and Northern Marianas, use the 2003 revision of the U.S. Standard Certificate of Live Birth and report race according to the 1997 revised OMB standards. However, to provide uniformity and comparability of data for trend comparison, bridged single-race categories are still presented in Health, United States.

The bridging methodology was developed using information from the 1997-2000 National Health Interview Survey (NHIS). NHIS provides a unique opportunity to investigate multiple-race groups because, since 1982, it has allowed respondents to choose more than one race but has also asked respondents reporting multiple races to choose a primary race. The bridging methodology developed by NCHS involved the application of regression models relating person-level and county-level covariates to the selection of a particular primary race by the multiple-race respondents. The bridging proportions derived from these models have been applied by the U.S. Census Bureau to various unbridged resident population files. These applications have resulted in bridged-race population estimates for each of the four single-race categories: American Indian or Alaska Native, Asian or Pacific Islander, black, and white.

In Health, United States, vital rates for 1991-1999 were calculated using the July 1, 1991-July 1, 1999, bridged-race intercensal estimates Vital rates for 2000 were calculated using the bridged-race April 1, 2000, census counts, and those for 2010 were calculated using the bridged-race April 1, 2010, census counts. Starting with Health, United States, 2012, vital rates for 2001-2009 have been recalculated using the July 1, 2001-July 1, 2009, revised intercensal bridged-race population estimates. Vital rates for 2011 and beyond are calculated using bridged-race estimates of the July 1 population from the corresponding postcensal vintage.

For More Information

See the U.S. Census Bureau website at: https://www.census.gov, and the NCHS website for U.S. census populations with bridged-race categories at: https://www.cdc.gov/nchs/nvss/bridged_race.htm.

Overview

This administrative database, referred to in Health, United States as QIES, is created from the Certification and Survey Provider Enhanced Reporting (CASPER) and QIES systems. QIES is a CMS database that contains information from the standard annual facility survey data submitted by state survey agencies to CMS for certification to participate in the Medicare and Medicaid programs in the United States and territories. (Data for the territories are not shown in Health, United States.) The purpose of the facility survey certification process is to ensure that facilities meet current CMS care requirements and thus can be paid for services furnished to Medicare and Medicaid beneficiaries. In 2012, QIES replaced the Online Survey Certification and Reporting Database (OSCAR). QIES (and OSCAR) contain information on facility and patient characteristics and health deficiencies issued by the government during the survey process.

Coverage

Facilities in the United States that are certified to receive Medicare or Medicaid payments are included.

Methodology

QIES data are compiled by the state survey agency and a facility representative. The data are reviewed during the survey process and then submitted electronically to CMS. The information provided can be audited at any time.

All certified facilities are inspected periodically by representatives of the state survey agency (generally the department of health). Some facilities are inspected twice, or more often, during any given reporting cycle. To avoid overcounting, the data must be edited, and duplicates removed. Data editing and compilation of nursing home data were performed by Cowles Research Group and published in its Nursing Home Statistical Yearbook series.

References

• Cowles CM, editor. Nursing home statistical yearbooks for 2003-2016. Anacortes, WA: Cowles Research Group. 2004-2017, respectively. Available from: http://www​.longtermcareinfo​.com/publications​/nursing-home-statistical-yearbook​.php.
• Centers for Medicare & Medicaid Services. Quality, safety, and oversight: Certification and compliance. 2005. Available from: https://www​.cms.gov/Medicare​/Provider-Enrollment-and-Certification​/CertificationandComplianc/index​.html.

For More Information

See the CMS website at: https://www.cms.gov/Research-Statistics-Data-and-Systems/Files-for-Order/NonIdentifiableDataFiles/index.html, and the Cowles Research Group website at: http://www.longtermcareinfo.com/index.html.

Overview

Surveillance information on the incidence and prevalence of STDs is used to inform public and private health efforts to control these diseases. Case reporting data are available for nationally notifiable diseases, including chancroid, chlamydia, gonorrhea, and syphilis. Enhanced surveillance of these conditions and surveillance of other STDs, such as genital herpes simplex virus, genital warts and other human papillomavirus infections, and trichomoniasis use data collected from other sources, including data from sentinel surveillance and national surveys.

Coverage

Case reports of STDs are reported to CDC by STD surveillance systems operated by state and local STD control programs and health departments in 50 states, the District of Columbia, selected cities, all U.S. counties, and outlying areas consisting of U.S. dependencies, possessions, and independent countries in free association with the United States. Data from outlying areas are not included in Health, United States

Methodology

Information is obtained from the following data sources: (a) notifiable disease reporting from state and local STD programs; (b) projects that monitor STD positivity and prevalence in various settings, including the National Job Training Program, the National Notifiable Disease Surveillance System, and the Gonococcal Isolate Surveillance Project; and (c) national sample surveys implemented by federal and private organizations. STD data are submitted to CDC on a variety of hard-copy summary reporting forms (monthly, quarterly, and annually) and in electronic summary or individual case-specific (line-listed) formats through the National Electronic Telecommunications System for Surveillance.

Issues Affecting Interpretation

Because of incomplete diagnosis and reporting, the number of STD cases reported to CDC undercounts the actual number of infections occurring among the U.S. population.

For More Information

See the CDC website on STD data and statistics at: https://www.cdc.gov/std/stats, and the CDC website on STD diseases and related conditions: https://www.cdc.gov/std/general/default.htm.

Overview

SEER tracks the incidence of new cancers each year and collects follow-up information on all previously diagnosed patients until their death. For each cancer, SEER registries routinely collect data on patient demographics, primary tumor site, morphology, stage at diagnosis, first course of treatment, and follow-up for vital status.

Coverage

The SEER 9 registries (Atlanta, Connecticut, Detroit, Hawaii, Iowa, New Mexico, San Francisco-Oakland, Seattle-Puget Sound, and Utah) have been part of the program continuously since 1975. The SEER 13 registries (the SEER 9 registries plus Los Angeles, San Jose-Monterey, rural Georgia, and the Alaska Native Tumor Registry) have been part of the program continuously since 1992. The SEER 18 registries (the SEER 13 plus Greater Georgia, Kentucky, Greater California, New Jersey, and Louisiana) have been part of the program continuously since 2000. SEER currently collects and publishes cancer incidence and survival data from 18 population-based cancer registries covering approximately 30% of the U.S. population.

Methodology

A cancer registry collects and stores data on cancers diagnosed in a specific hospital or medical facility (hospital-based registry) or in a defined geographic area (population-based registry). A population-based registry includes, but is not limited to, a number of hospital-based registries. In SEER registry areas, trained coders abstract medical records using the International Classification of Diseases for Oncology, 3rd edition (ICD-O-3) to classify site and tumor morphology. The ICD-O-3 coding also includes updates for hematopoietic codes based on the World Health Organization Classification of Tumours of Haematopoietic and Lymphoid Tissues. All SEER data in this report were collected with or converted to ICD-O-3

NCI obtains population counts from the U.S. Census Bureau and uses them to calculate incidence rates. It also uses estimation procedures as needed to obtain estimates for years and races not included in data provided by the U.S. Census Bureau. Life tables used to determine general population life expectancy when calculating relative survival rates were obtained from the National Center for Health Statistics and in-house calculations. Separate life tables are used for each race-sex-specific group included in SEER.

Issues Affecting Interpretation

Because of the addition of registries over time, analysis of long-term incidence and survival trends is limited to those registries that have been in SEER for similar lengths of time. Analysis of Hispanic and American Indian or Alaska Native data is limited to shorter trends. Starting with Health, United States, 2006, the North American Association of Central Cancer Registries Hispanic Identification Algorithm was used on a combination of variables to classify cases as Hispanic for analytic purposes. Starting with Health, United States, 2007, Hispanic incidence data exclude data for Alaska. Earlier editions of Health, United States also excluded Hispanic data for Hawaii and Seattle. Starting with Health, United States, 2007, incidence estimates for the American Indian or Alaska Native population are limited to contract health service delivery area counties within SEER reporting areas. This change is believed to produce estimates that more accurately reflect the incidence rates for this population group. For more information on SEER estimates by race and ethnicity, see: https://seer.cancer.gov/seerstat/variables/seer/race_ethnicity/index.html. Rates presented in this report may differ somewhat from those reported previously due to changes in population estimates and the addition and deletion of small numbers of incidence cases.

References

• Howlader N, Noone AM, Krapcho M, Miller D, Bishop K, Kosary CL, et al., editors. SEER cancer statistics review (CSR), 1975-2014. Based on November 2016 SEER data submission, posted to the SEER website, April 2017. Available from: https://seer​.cancer.gov/csr/1975_2014/.
• Jim MA, Arias E, Seneca DS, Hoopes MJ, Jim CC, Johnson NJ, Wiggins CL. Racial misclassification of American Indians and Alaska Natives by Indian Health Service Contract Health Service Delivery Area. Am J Public Health 104(Suppl 3):S295–302. [PMC free article: PMC4035863] [PubMed: 24754617]

For More Information

See the SEER website at: https://seer.cancer.gov.

Overview

YRBSS monitors health risk behaviors among students in grades 9 to 12 that contribute to morbidity and mortality in both adolescence and adulthood. The six areas monitored are behaviors that contribute to unintentional injuries and violence; tobacco use; alcohol and other drug use; sexual behaviors that contribute to unintended pregnancy and sexually transmitted diseases (STDs), including human immunodeficiency virus (HIV) infection; unhealthy dietary behaviors; and physical inactivity. In addition, YRBSS monitors the prevalence of obesity, asthma, and sleep behaviors.

Coverage

National data are representative of high school students in public and private schools in the United States.

Methodology

The national YRBSS school-based surveys have been conducted biennially since 1991. A three-stage cluster sample design is used to produce a nationally representative sample of students in grades 9 to 12 attending public and private schools. In 2013 and 2015, the first-stage sampling frame comprised primary sampling units (PSUs) consisting of counties, subareas of large counties, or groups of smaller, adjacent counties. PSUs were categorized into strata according to their metropolitan statistical area (MSA) status (e.g., urban city) and the percentages of non-Hispanic black and Hispanic students in the PSUs. PSUs were sampled with probability proportional to overall school enrollment size for the PSU. In the second stage of sampling, schools with any of grades 9 to 12 were sampled with probability proportional to school enrollment size The third stage of sampling consisted of random sampling in each of grades 9 to 12, one or two classrooms from either a required subject (e.g., English or Social Studies) or a required period (e.g., Homeroom or second period.)

All students in sampled classes were eligible to participate. Schools, classes, and students that refused to participate were not replaced. To enable a separate analysis of data for black and Hispanic students, two classes per grade, rather than one, were sampled in schools with a high enrollment of black and Hispanic students. Prior to 2013, three strategies were used to oversample black and Hispanic students: (a) larger sampling rates were used to select PSUs that were in high-black and high-Hispanic strata; (b) a modified measure of size was used to increase the probability of sampling schools with a disproportionately high minority enrollment; and (c) two classes per grade, rather than one, were sampled in schools with a high enrollment of black and Hispanic students. A weighting factor is applied to each student record to adjust for nonresponse and for the varying probabilities of selection, including those resulting from the oversampling of black and Hispanic students.

Sample Size and Response Rate

The sample size for the 2015 YRBSS was 15,624 students in 180 schools. The school response rate was 69%, and the student response rate was 86%, for an overall response rate of 60%.

Issues Affecting Interpretation

National YRBSS data are subject to at least two limitations. First, these data apply only to adolescents who attend regular high school, including some charter, public alternative, special education, and vocational schools. These students may not be representative of all persons in this age group because those who have dropped out of high school are not surveyed. Second, the extent of underreporting or overreporting cannot be determined, although the survey questions demonstrate good test-retest reliability.

Estimates of substance use for youth based on YRBSS differ from the National Survey on Drug Use and Health (NSDUH) and the Monitoring the Future (MTF) Study. Rates are not directly comparable across these surveys because of differences in populations covered, sample designs, questionnaires, and interview settings. NSDUH collects data in residences, whereas MTF and YRBSS collect data in school classrooms. In addition, NSDUH estimates are tabulated by age, whereas MTF and YRBSS estimates are tabulated by grade, representing different ages as well as different populations. All YRBSS data collection is anonymous.

References

• Centers for Disease Control and Prevention, Brener ND, Kann L, Shanklin S, Kinchen S, Eaton DK, et al. Methodology of the Youth Risk Behavior Surveillance System-2013. MMWR Recomm Rep 62(RR-1):1–23. 2013. Available from: http://www​.cdc.gov/mmwr​/preview/mmwrhtml/rr6201a1.htm. [PubMed: 23446553]
• Kann L, Kinchen S, Shanklin SL, Flint KH, Hawkins J, Harris WA, et al. Youth risk behavior surveillance-United States, 2013. MMWR Suppl 63(4):1–168. 2014. Available from: http://www​.cdc.gov/mmwr/pdf/ss/ss6304​.pdf. [PubMed: 24918634]
• Kann L, McManus T, Harris WA, Shanklin SL, Flint KH, Hawkins J, et al. Youth risk behavior surveillance-United States, 2015. MMWR Surveill Summ 65(6):1–174. 2016. Available from: https://www​.cdc.gov/healthyyouth​/data/yrbs​/pdf/2015/ss6506_updated.pdf. [PubMed: 27280474]
• Cowan CD. Coverage, sample design, and weighting in three federal surveys. J Drug Issues 31(3):599–614. 2001.

For More Information

See the YRBSS website at: https://www.cdc.gov/healthyyouth/data/yrbs/index.htm.

For More Information

See the AACOM website at: http://www.aacom.org.

Reference

• American Association of Colleges of Pharmacy Fall 2015 Profile of Pharmacy Students, Fall 2016 Profile of Pharmacy Students. Available from: https://www​.aacp.org​/research/student-applications-enrollments-and-degrees-conferred.

For More Information

See the AACP website at: https://www.aacp.org.

Reference

• American Association of Colleges of Podiatric Medicine Applicant, matriculant, and graduate statistics. Available from: http://www​.aacpm.org/statistics/.

For More Information

See the AACPM website at: http://www.aacpm.org.

References

• American Dental Association, Health Policy Institute. Tables 1 and 3. In: Supply of dentists in the U.S.: 2001-2017. Available from: https://www​.ada.org/en​/science-research/health-policy-institute​/data-center/supply-and-profile-of-dentists.
• American Dental Association, Health Policy Institute. Survey of Dental Education series. Report 1: Academic programs, enrollment and graduates. 2015-2016 report 1. 2016. Available from: https://www​.ada.org/~​/media/ADA/Science%20and%20Research​/HPI​/Files/2015-16_SDE1_final.xlsx?la=en.

For More Information

See the ADA website at: https://www.ada.org.

Reference

• American Hospital Association. AHA hospital statistics, 2017 edition. Chicago, IL: AHA. 2017.

For More Information

See the AHA website at: http://www.aha.org.

Reference

• American Medical Association. Physician characteristics and distribution in the U.S., 2015. Chicago, IL: AMA Division of Survey and Data Resources. 2015.

For More Information

See the AMA website at: https://www.ama-assn.org.

Reference

• American Osteopathic Association. 2015 osteopathic medical profession report. 2015. Available from: https://osteopathic​.org​/wp-content/uploads​/2018/02/2015-OMP-report.pdf.

For More Information

See the AOA website at: http://www.osteopathic.org.

References

• Association of American Medical Colleges. AAMC data book: Medical schools and teaching hospitals by the numbers, 2017. Washington, D.C.: AAMC. 2017.
• Association of American Medical Colleges. AAMC FACTS: Tables. 2017.

For More Information

See the AAMC website at: https://www.aamc.org.

References

• Association of Schools and Colleges of Optometry. Annual student data report: Academic year 2015-2016. 2016 (updated 2017). Available from: https:​//optometriceducation​.org/wp-content​/uploads/2017/05/ASG?-StuData-Report-15-16-5-9-17-2.pdf.
• Association of Schools and Colleges of Optometry. Association of Schools and Colleges of Optometry Annual student data report: Academic year 2016-2017. 2017. Available from: https:​//optometriceducation​.org/wp-content​/uploads/2018/05/ASCO-Student-Data-Report-2016-17-updated-May-2018.pdf.

For More Information

See the ASCO website at: https://www.optometriceducation.org.

Reference

• Association of Schools and Programs of Public Health. 2017 [unpublished data]

For More Information

See the ASPPH website at: https://www.aspph.org/connect/data-center.

Reference

• Jones RK, Jerman J. Abortion incidence and service availability in the United States, 2014. Perspect Sex Reprod Health 49(1):17–27. 2017. Available from: https://www​.guttmacher​.org/sites/default​/files/article_files​/abortion-incidence-us.pdf. [PMC free article: PMC5487028] [PubMed: 28094905]

For More Information

See The Guttmacher Institute website at: https://www.guttmacher.org.

For More Information

See the OECD website at: http://www.oecd.org/health.