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 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 2003–2012, a total of 47 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 2004–2013, 5 of the 52 reporting areas did not provide CDC with data on a consistent annual basis (the five states that did not report continuously for the period 2004–2013 were California, Louisiana, Maryland, New Hampshire, and West Virginia). Because of these limitations, during the period covered by this report the total annual number of abortions recorded by CDC was consistently approximately 70% 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, Ewing A, Mandel MG, Simmons KB, Suchdev DB, Jamieson DJ, Pazol K. Abortion surveillance—United States, 2013. MMWR Surveill Summ 2016;65(SS–12):1–44. Available from: http://www​.cdc.gov/mmwr​/volumes/65/ss/ss6512a1.htm. [PubMed: 27880751]

For More Information

See the NCCDPHP surveillance and research website at: http://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 on an annual basis in ACS were previously collected once a decade through the decennial census long form.

Coverage

ACS covers U.S. residents residing in all 3,141 counties in the 50 states and D.C., 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 over the Internet, followed later 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, or 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 the 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 to each sample person record (both household and group quarters persons) and a weight to 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 U.S. 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 and 2015, it was 97% and 96%, respectively. 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 2005–2015. For year-specific response rates, see: http://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). Washington, DC: U.S. Census Bureau; 2014. Available from: http://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. Washington, D.C.: U.S. Census Bureau, Social, Economic, and Housing Statistics Division; 2014. Available from: http://www​.census.gov​/content/dam/Census​/library/working-papers​/2014/demo/sehsd_wp_2014-29.pdf.

For More Information

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

Overview

BHSUA measures aggregate spending for the treatment of mental health (MH) and/or substance use disorders (SUD) in the United States. Spending for MH and SUD services was based on the principal diagnosis using the International Classification of Diseases, Ninth Revision, Clinical Modification (ICD–9–CM) codes for mental disorders and excluded comorbid health costs resulting from MH and SUD. BHSUA provides expenditures across four dimensions: diagnosis (MH, SUD); providers and products (hospitals, physician services, other professional services including psychologists and clinical social workers, nursing home care, home health care, center-based providers, prescription drugs, insurance administration); setting (inpatient, outpatient, residential); and payment source (private insurance, out of pocket, other private including foundations and charities, Medicare, Medicaid/Children’s Health Insurance Program [CHIP]). A consistent set of definitions is used in the BHSUA allowing for comparisons over time.

Methodology

BHSUA spending estimates were designed to closely mirror the National Health Expenditure Accounts (NHEA) constructed by CMS and to allow for comparisons between MH and SUD spending and overall health expenditures. (See Appendix I, National Health Expenditure Accounts [NHEA]). Estimates for MH and SUD spending for nonspecialty providers were carved out of estimates of total national health consumption expenditures developed by CMS. Estimates for specialty MH and SUD facilities were developed from SAMHSA data. Duplicate expenditures between specialty and nonspecialty providers were removed.

Issues Affecting Interpretation

In the 2009 comprehensive revisions to the NHEA, spending was broadened to encompass residential treatment facilities that included residential SUD and MH facilities. Some residential treatment centers that previously were not included in BHSUA were included starting in 2009, raising the overall level of MH/SUD spending.

Reference

• Substance Abuse and Mental Health Services Administration. Behavioral Health Spending & Use Accounts 1986–2014. Rockville, MD: SAMHSA; 2016. Available from: http://store​.samhsa.gov​/shin/content/SMA16-4975/SMA16-4975​.pdf.

For More Information

See the SAMHSA website at: https://www.samhsa.gov/.

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 D.C. 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, the decedent 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 his or her 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 numbers of fatal occupational injuries were revised once after the initial preliminary release. States had up to eight 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 2010–2014 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 to 2008 were classified based on the 2002 NAICS, while industry data for reference years 2009 to 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.)

References

• Bureau of Labor Statistics. Census of Fatal Occupational Injuries Summary, 2015. Washington, D.C.: U.S. Department of Labor; 2016. Available from: https://www​.bls.gov/news​.release/archives/cfoi_12162016.htm.
• Bureau of Labor Statistics. Revisions to the 2014 Census of Fatal Occupational Injuries (CFOI) counts. Washington, D.C.: U.S. Department of Labor; 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 the 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 D.C. When files from the most recent decennial census become available, the Census Bureau gradually introduces a new sample design for the 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) supplement 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 2015 data from the 2016 CPS ASEC were based on a sample of about 95,000 addresses collected in the 50 states and D.C. In an average month, the nonresponse rate for the basic CPS is about 7%–8%; supplements tend to have higher nonresponse rates.

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, Proctor, and Smith (2012).

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 no 66. Washington, D.C.: U.S. Census Bureau; 2006. Available from: http://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. Washington, D.C.: U.S. Government Printing Office; 2012. Available from: https://www​.census.gov​/prod/2012pubs/p60-243.pdf.
• Proctor BD, Semega JL, Kollar MA. Income and poverty in the United States: 2015. Current Population Reports, P60–256. Washington, D.C.: U.S. Government Printing Office; 2016. Available from: http://www​.census.gov​/content/dam/Census​/library/publications/2016/demo/p60-256​.pdf.

For More Information

See the CPS website at: http://www.census.gov/cps.

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, different VA programs may serve populations with different sociodemographic characteristics in contrast with populations served by other health care systems.

For More Information

See the VA Information Resource Center website at: http://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 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

In 2012, HCUP–NIS was redesigned to improve national estimates. To highlight the design change, beginning with 2012 data, AHRQ renamed HCUP–NIS from the “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 reflect 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. In: Healthcare Cost and Utilization Project—HCUP: A federal-state-industry partnership in health data. Rockville, MD: AHRQ; 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; 2014. HCUP Methods Series Report # 2014–04 ONLINE. April 4, 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: http://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 D.C. 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 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 HCFA–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 adjudicated 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 http://www.medicaid.gov/Medicaid-CHIP-Program-Information/By-Topics/Data-and-Systems/Data-and-Systems.html and the Research Data Assistance Center (ResDAC) website at: http://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 (IC). Data from MEPS–HC and MEPS–MPC are used in Health, United States.

Coverage

The U.S. civilian noninstitutionalized population is the primary population 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 two 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. The 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 the 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 2013 MEPS, there were 13,936 families covered, and 35,068 respondents over the course of the year. For the same year, the overall annual response rate was 52.8%, 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 (2002).

References

• Ezzati-Rice TM, Rohde F, Greenblatt J. Sample design of the Medical Expenditure Panel Survey Household Component, 1998–2007. Methodology report no 22. Rockville, MD: 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 2002;39(1):76–86. [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).

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 (ResDAC) website at: http://www.resdac.org and the CMS website at: http://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 ascertain all types of health insurance coverage and relate coverage to sources of payment; and to trace processes 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 four 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 and Use file and the Access to Care file. Medicare claims are linked to survey-reported events to produce the Cost and Use file, which provides complete expenditure and source-of-payment data on all health care services, including those not covered by Medicare. The Access to Care file contains information on beneficiaries’ access to health care, satisfaction with care, and usual source of care. The sample for this file represents the always-enrolled population—those who participated in the Medicare program for the entire year. In contrast, the Cost and Use file represents the ever-enrolled population, including those who entered Medicare and those who died during the 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 12,000 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 80%; once respondents have completed the first interview, their participation in subsequent rounds is 95% 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 and Use file estimates were created with a new imputation methodology; therefore some utilization estimates may not be comparable with previous years.

References

• Adler GS. A profile of the Medicare Current Beneficiary Survey. Health Care Financ Rev 1994;15(4):153–63. [PMC free article: PMC4193434] [PubMed: 10138483]
• Lo A, Chu R, Apodaca A. Redesign of the Medicare Current Beneficiary Survey sample. Rockville, MD: Westat, Inc.; 2003. Available from: http://www​.amstat.org​/sections/srms/Proceedings​/y2002/Files/JSM2002-000662.pdf.

For More Information

See the MCBS website at: http://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 sample of 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 the selection of one or more schools in each area, and stage 3 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 on the day of the survey are excluded. Recognizing that the dropout population is at higher risk for drug use, MTF was expanded in 1991 to include similar nationally representative samples of 8th and 10th graders, who have lower dropout rates than seniors and include future high-risk 12th grade dropouts. For more information on MTF adjustments for absentees and dropouts, see Johnston et al. (2014 and preceding); and Miech et al. (2015 onwards).

Sample Size and Response Rate

In 2015, a total of 44,892 students in 382 public and private schools in the coterminous United States participated. The annual senior samples comprised 13,730 12th graders in 121 public and private high schools nationwide. The 10th-grade samples involved 16,147 students in 120 schools, and the 8th-grade samples had 15,015 students in 141 schools. Student response rates were 89% for grade 8, 87% for grade 10, and 83% for grade 12 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 & Health (NSDUH) are not directly comparable with estimates based on MTF and the Youth Risk Behavior Survey (YRBS). 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 YRBS collect data in school classrooms. In addition, NSDUH estimates are tabulated by age, whereas MTF and YRBS estimates are tabulated by grade, representing different ages as well as different populations.

References

• Miech RA, Johnston LD, O’Malley PM, Bachman JG, Schulenberg JE. Monitoring the Future National Survey results on drug use: 1975–2015. Vol I, Secondary school students. Ann Arbor, MI: Institute for Social Research, The University of Michigan; 2016. Available from: http://www​.monitoringthefuture​.org/pubs/monographs​/mtf-vol1_2015.pdf.
• Cowan CD. Coverage, sample design, and weighting in three federal surveys. J Drug Issues 2001;31(3):599–614.
• Johnston LD, O’Malley PM, Bachman JG, Schulenberg JE, Miech, RA. Monitoring the Future National Survey results on drug use, 1975–2013: Vol I, Secondary school students. Ann Arbor, MI: Institute for Social Research, The University of Michigan; 2014. Available from: http:​//monitoringthefuture​.org/pubs/monographs​/mtf-vol1_2013.pdf.

For More Information

See the NIDA website at: http://www.nida.nih.gov/Infofax/HSYouthtrends.html 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 encounters in 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. Patient encounters with physicians engaged in prepaid practices (health maintenance organizations [HMOs], independent practice organizations [IPAs], and other prepaid practices) are included in NAMCS. Excluded are visits to hospital-based physicians; visits to specialists in anesthesiology, pathology, or radiology; and visits to physicians who are principally engaged in teaching, research, or administration. Telephone contacts and nonoffice visits are also excluded. Starting in 2006, NAMCS includes visits to a separate sample of community health centers (CHCs). In 2012, the NAMCS survey sample size was increased to allow for state-level estimates in the 34 most populous states and the U.S. Census Bureau divisions.

Methodology

A multistage probability design is employed. Beginning in 1989–2011, the first-stage sample consisted of 112 primary sampling units (PSUs), which 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. Starting in 1989, the survey included all 50 states and D.C.

Starting in 2006–2011, a dual-sampling procedure was used to select CHC physicians and nonphysician clinicians. 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 were selected, including physicians, physician assistants, nurse practitioners, or nurse midwives. After selection, CHC providers followed traditional NAMCS methods for selecting patient visits. Another major change starting in 2012 was the mode of data collection—from in-person interviews with a paper questionnaire to obtain physician practice information to laptop-assisted data collection using automated survey instruments. Over time, interviewer abstraction from visit records has been increasing. In 2012, medical abstraction by interviewers was the predominant method of data collection.

Since 2008, a supplemental mail survey on EHR systems has been conducted in addition to the core NAMCS. This supplement is known as the National Ambulatory Medical Care Survey–National Electronic Health Records Survey (NEHRS). Starting in 2010, the mail NEHRS sample size was increased five-fold to allow for state-level estimates without needing to combine NEHRS with the core NAMCS. Survey questions have been added since the introduction of NEHRS.

The U.S. Census Bureau acts as the data collection agent for NAMCS. Starting in 2012, Census field representatives have used laptops containing an automated version of each survey instrument to (a) conduct induction interviews with the physician or his or her representative to obtain information about the practice and ensure that it is within the scope of the survey; (b) determine which visits to sample; and (c) abstract and record data from medical charts. Prior to 2012, physicians were asked to perform their own visit sampling and record abstraction using a paper-and-pencil mode of data collection, but Census field representatives were available to perform these tasks if needed. Beginning in 2012, abstraction by field representatives became the preferred mode of data collection, accounting for 98% of 2012 and 99% of 2013 records collected.

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

In 2011, a sample of 3,819 physicians was selected: 2,555 were in-scope and 1,400 participated, for an unweighted response rate of 54% (54% weighted). Data were provided for 30,872 visits. In 2012, a sample of 15,740 physicians was selected: 9,574 were in-scope and 3,010 participated, for an unweighted response rate of 39% (39% weighted). Data were provided for 76,330 visits. The response rates have been modified to accommodate the mixture of one- and two-stage samples of providers. The 2013 NAMCS–NEHRS had a sample of 10,302 physicians. The unweighted response rate was 70% (67% weighted).

Issues Affecting Interpretation

The NAMCS patient record form is modified approximately every 2–4 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 two or more years of data if they wish to examine relatively rare populations or events. Starting with Health, United States, 2005, data for survey years 2001–2002 were revised to be consistent with the weighting scheme introduced in the 2003 NAMCS data. For more information on the new weighting scheme, see Hing et al. (2005). 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 et al. (2016).

References

• Hing E, Cherry DK, Woodwell DA. National Ambulatory Medical Care Survey: 2003 summary. Advance data from vital and health statistics; no 365. Hyattsville, MD: NCHS; 2005. Available from: http://www​.cdc.gov/nchs/data/ad/ad365​.pdf.
• Hing E, Shimizu IM, Talwalkar A. Nonresponse bias in estimates from the 2012 National Ambulatory Medical Care Survey. Vital Health Stat 2(171). Hyattsville, MD: NCHS; 2016. Available from: http://www​.cdc.gov/nchs​/data/series/sr_02/sr02_171.pdf. [PubMed: 27301078]

For More Information

See the National Health Care Surveys website at: http://www.cdc.gov/nchs/dhcs.htm and the Ambulatory Health Care Data website at: http://www.cdc.gov/nchs/ahcd.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 nation, for the nine census divisions, and for 152 smaller geographic areas. NCS includes 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 consists of 152 geographic areas, 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 2016 sample consists of about 6,900 establishments in private industry and about 1,500 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

• Bureau of Labor Statistics. Employer costs for employee compensation—March 2016 [press release USDL–16–1808]. Washington, D.C.: U.S. Department of Labor; 2016 June 09. Available from: http://www​.bls.gov/news​.release/pdf/ecec.pdf.
• Wiatrowski WJ. The National Compensation Survey: Compensation statistics for the 21st century. Washington, D.C.: U.S. Department of Labor, Bureau of Labor Statistics. Compensation and Working Conditions (CWC) Online 2000;Winter:5–14. Available from: http://www​.bls.gov/opub​/mlr/cwc/the-national-compensation-survey-compensation-statistics-for-the-21st-century.pdf.
• U.S. Bureau of Labor Statistics. BLS handbook of methods, Ch. 8: National compensation measures; 2007. Available from: http://www​.bls.gov/opub/hom/pdf/homch8​.pdf.

For More Information

See the NCS website at: http://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, begun 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. In 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 in 2000–2014, 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. For more information on the sample design for 1999–2006, see: http://www.cdc.gov/nchs/data/series/sr_02/sr02_155.pdf; for 2007–2010, see: http://www.cdc.gov/nchs/data/series/sr_02/sr02_160.pdf; and for 2011–2014, see: http://www.cdc.gov/nchs/data/series/sr_02/sr02_162.pdf.

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 2011–2012, a total of 13,431 persons were eligible, of which 73% (9,756) were interviewed and 70% (9,338) completed the health examination component. 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 more information on unweighted NHANES response rates and response weights using sample size weighted to Current Population Survey population totals, see: http://www.cdc.gov/nchs/nhanes/response_rates_CPS.htm.

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 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, et al. Sample design: Third National Health and Nutrition Examination Survey. NCHS. Vital Health Stat 1992;2(113). Available from: http://www​.cdc.gov/nchs​/data/series/sr_02/sr02_113.pdf. [PubMed: 1413563]
• NCHS. Plan and operation of the Third National Health and Nutrition Examination Survey, 1988–94. Vital Health Stat 1994;1(32). Available from: http://www​.cdc.gov/nchs​/data/series/sr_01/sr01_032.pdf. [PubMed: 7975354]
• Johnson CL, Paulose-Ram R, Ogden CL, et al. National Health and Nutrition Examination Survey: Analytic guidelines, 1999–2010. NCHS. Vital Health Stat 2013;2(161). Available from: http://www​.cdc.gov/nchs​/data/series/sr_02/sr02_161.pdf. [PubMed: 25090154]
• Johnson CL, Dohrmann SM, Burt VL, Mohadjer LK. National Health and Nutrition Examination Survey: Sample design, 2011–2014. Vital Health Stat 2014;2(162). Available from: http://www​.cdc.gov/nchs​/data/series/sr_02/sr02_162.pdf. [PubMed: 25569458]

For More Information

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

Overview

NHEA provide estimates of aggregate health care expenditures in the United States from 1960 onward. NHEA contain 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

The primary data sources used to estimate hospital care spending are the American Hospital Association’s (AHA) Annual Survey and the U.S. Census Bureau’s Services Annual Survey (SAS). These sources are supplemented by data on federal hospital spending. Expenditures for physician and clinical services are estimated using data from SAS and the U.S. Census Bureau’s quinquennial Economic Census. Expenditures for nursing care facilities and continuing care retirement communities, home health care, dentists, and the services of other professionals (e.g., chiropractors, private duty nurses, therapists, and podiatrists) are estimated using data from SAS and the quinquennial Economic Census. The estimate of retail spending for prescription drugs is based on prescription drug data from the U.S. Census Bureau’s Census of Retail Trade and data from IMS Health (Parsippany, NJ), an organization that collects data on retail sales of prescription drugs.

Expenditures for durable and other nondurable medical products purchased in retail outlets are based on input-output and personal consumption expenditure data (Bureau of Economic Analysis), the Economic Census and Annual Retail Trade Survey (ARTS) data (U.S. Census Bureau), Consumer Expenditure Survey data (Bureau of Labor Statistics [BLS]), Medical Expenditure Panel Surveys (MEPS) data (Agency for Healthcare Research and Quality [AHRQ]), and over-the-counter sales data from Kline and Company, Inc. Durable and nondurable products provided to inpatients in hospitals or nursing homes, and those provided by licensed health professionals or through home health care agencies, are excluded from NHEA estimates of durable and nondurable medical products but are included with the expenditure estimates for the provider service category.

The Structures and Equipment component of NHEA includes estimates of the value of new construction put in place and new capital equipment (including software) purchased by the medical sector during the year. These estimates are based on a variety of data from the U.S. Census Bureau and the Bureau of Economic Analysis, including the Annual Capital Expenditures Survey, the C–30 Survey, and data from the National Income and Product Accounts.

Expenditures for noncommercial research are included in the Investment category of NHEA and are developed primarily from information gathered by the National Institutes of Health and the National Science Foundation. The cost of commercial research (such as by drug companies) is assumed to be embedded in the price charged for the product and therefore is not included in the noncommercial research category.

Private health insurance spending for health care goods and services is derived using data from the U.S. Census Bureau, the American Medical Association (AMA), the American Hospital Association (AHA), and IMS Health, as well as household data from surveys such as the National Medical Care Expenditure Survey (National Center for Health Services Research, 1987) and later, MEPS (AHRQ, 1996–2015). The net cost of private health insurance (which includes administrative costs, additions to reserves, rate credits and dividends, premium taxes, and net underwriting gains or losses) is estimated using data from A.M. Best (Oldwick, NJ), the National Association of Insurance Commissioners, BLS surveys on the cost of employer-sponsored health insurance and consumer expenditures, MEPS data for self-insured plans, data from privately funded surveys, and numerous consulting firms and private health insurance trade organizations.

Estimates of federal health care program spending (e.g., Medicare, Medicaid, and Department of Defense) were developed using administrative records maintained by the servicing agencies. Out-of-pocket spending (direct spending by consumers for copayments, coinsurance, deductibles, and payments for goods and services not covered by insurance) was estimated using data from SAS (U.S. Census Bureau), the Consumer Expenditure Survey (BLS), MEPS (AHRQ), the AHA Annual Survey, and IMS Health.

Issues Affecting Interpretation

Every 5 years, NHEA undergo 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

• Martin AB, Hartman M, Benson J, Caitlin A, the National Health Expenditure Accounts Team. National health spending: Faster growth in 2015 as coverage expands and utilization increases. Health Aff (Millwood) 2017;36(1):166–76. [PubMed: 27913569]
• Centers for Medicare & Medicaid Services. National Health Expenditure Accounts: Methodology paper, 2015: Definitions, sources, and methods. Baltimore, MD: CMS; 2016. Available from: https://www​.cms.gov/Research-Statistics-Data-and-Systems​/Statistics-Trends-and-Reports​/NationalHealthExpendData​/downloads/dsm-15.pdf.
• Centers for Medicare & Medicaid Services. Summary of 2014 comprehensive revision to National Health Expenditure Accounts. Baltimore, MD: CMS; 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: http://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 the 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 sampling plan follows a multistage area probability design that permits the representative sampling of households. Traditionally, the sample for NHIS is redesigned and redrawn about every 10 years to better measure the changing U.S. population and to meet new survey objectives. A new sample design was implemented in the 2006 survey and will be used through the 2015 survey year. A new sample design will be used in 2016. The fundamental structure of the 2006 design is very similar to the previous design for the 1995–2005 surveys. Only the current sampling plan covering design years 2006–2015 is addressed here. The first stage of the current sampling plan consists of a sample of 428 primary sampling units (PSUs) drawn from approximately 1,900 geographically defined PSUs that cover the 50 states and D.C. A PSU consists of a county, a small group of contiguous counties, or a metropolitan statistical area.

Within a PSU, two types of second-stage units are used: area segments and permit segments. Area segments are defined geographically and contain an expected 8, 12, or 16 addresses. Permit segments cover housing units built after the 2000 census. The permit segments are defined using updated lists of building permits issued in the PSU since 2000 and contain an expected four addresses. Within each segment, all occupied households at the sample addresses are targeted for interview.

The total NHIS sample of PSUs is subdivided into four separate panels, or subdesigns, such that each panel is a representative sample of the U.S. population. This design feature has a number of advantages, including flexibility for the total sample size. The households selected for interview each week in NHIS are a probability sample representative of the target population.

Oversampling of the black and Hispanic populations was retained in the 2006–2015 design to allow for more precise estimation of health characteristics in these populations. The current sample design also oversamples the Asian population. In addition, the sample adult selection process was revised so that when black, Hispanic, or Asian persons aged 65 and over are present, they have an increased chance of being selected as the sample adult.

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 one 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 in NHIS, one sample adult is randomly selected to participate in the Sample Adult questionnaire. For families with children under age 18, one sample 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.

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. Between 1997 and 2005, the sample numbered about 100,000 persons annually, with about 30,000–36,000 persons participating in the Sample Adult and about 12,000–14,000 in the Sample Child questionnaires. In the 2006–2015 redesign, the NHIS sample was reduced by 13% compared with the 1995–2005 design. With four sample panels and no sample cuts or augmentations, the expected annual NHIS sample size (completed interviews) during survey years 2006–2010 was on average 37,000 households containing about 81,000 persons.

In 2011–2015, the NHIS sample size was augmented in 32 states and D.C. The main goal of the augmentation was to increase the number of states for which reliable state-level estimates can be made. In 2011, the sample size was augmented by approximately 13%; in 2012, by approximately 21%; in 2013, by approximately 18%; in 2014, by approximately 28%; and in 2015, by approximately 19%. In 2015, the sample numbered 103,789 persons, with 33,672 persons participating in the Sample Adult and 12,291 in the Sample Child questionnaires. In 2015 the total household response rate was 70%. The final response rate in 2015 was 55% for the Sample Adult file and 63% for the Sample Child file.

Issues Affecting Interpretation

In 1997, the questionnaire was redesigned: 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 (CAPI). Because of the major redesign of the questionnaire in 1997, most NHIS trend tables in Health, United States begin with 1997 data. 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 on 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 (2009).

References

• Moriarity C 2009 National Health Interview Survey sample adult and sample child nonresponse bias analysis. Hyattsville, MD: NCHS; 2010. Available from: http://www​.cdc.gov/nchs​/data/nhis/nr_bias​_analysis_report_2009_NHIS.pdf.
• Parsons VL, Moriarity C, Jonas K, et al. Design and estimation for the National Health Interview Survey, 2006–2015. NCHS. Vital Health Stat 2; (165)2014. [PubMed: 24775908]

For More Information

See the NHIS website at: http://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 diagnosed with HIV infection include age, sex, race, ethnicity, mode of exposure, and geographic region.

Coverage

All 50 states, D.C., and six 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 six dependent areas. Using a standard confidential case report form, the health departments collect information that is then transmitted electronically, without personal identifiers, to CDC.

The 2015 HIV Surveillance Report marks the transition to presenting diagnosis, death, and prevalence data without statistical adjustments for delays in reporting of cases to CDC.

Because a substantial proportion of cases of HIV infection are reported to CDC without an identified risk factor, multiple imputation is used to assign a transmission category. Multiple imputation is a statistical approach in which each missing transmission category is replaced with a set of plausible values that represent the uncertainty about the true, but missing, value. The plausible values are analyzed by using standard procedures, and the results from these analyses are then combined to produce the final results. In tables displaying transmission categories, multiple imputation was used for adults and adolescents, but not for children (because the number of cases in children is small, missing transmission categories were not imputed). For more information, see Harrison KM, Kajese T, Hall HI, Song R. Risk factor redistribution of the national HIV/AIDS surveillance data: an alternative approach. Public Health Rep 2008;123(5):618–627; and see: Rubin DB. Multiple Imputation for Nonresponse in Surveys. New York: John Wiley & Sons Inc.; 1987.

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.

Reference

• CDC. HIV surveillance report. Atlanta, GA; [published annually]. Available from: http://www​.cdc.gov/hiv​/library/reports/hiv-surveillance.html.

For More Information

See the NCHHSTP website at: http://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. 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.

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. Within PSUs, 600 general and short-stay hospitals were sampled and assigned to 1 of 16 panels. In any given year, 13 panels are included. Each panel is assigned to a 4-week reporting period during the survey year.

In the NHAMCS OPD, a clinic is defined as an administrative unit of the OPD in which ambulatory medical care is provided under the supervision of a physician. Clinics where only ancillary services (e.g., radiology, laboratory services, physical rehabilitation, renal dialysis, and pharmacy) are provided, or other settings in which physician services are not typically provided, are considered out of scope. If a hospital OPD has five or fewer in-scope clinics, all are included in the sample. If an OPD has more than five clinics, the clinics are assigned to one of six specialty groups: general medicine, surgery, pediatrics, obstetrics and gynecology, substance abuse, and other. Within these specialty groups, clinics are grouped into clinic sampling units (SUs). A clinic SU is generally one clinic, except when a clinic expects fewer than 30 visits. In that case, it is grouped with one or more other clinics to form a clinic SU. If the grouped SU is selected, all clinics included in that SU are included in the sample. Prior to 2001, generally a sample of five clinic SUs was selected per hospital, based on probability proportional to the total expected number of patient visits to the clinic during the assigned 4-week reporting period. Starting in 2001, clinic sampling within each hospital was stratified. If an OPD had more than five clinics, two clinic SUs were selected from each of the six specialty groups with a probability proportional to the total expected number of visits to the clinic. The change was made to ensure that at least two SUs were sampled from each of the specialty group strata.

The U.S. Census Bureau acts as the data collection agent for NHAMCS. Census field representatives contact sample hospitals to determine whether they have a 24-hour ED or an OPD that offers physician services. Visits to eligible EDs and OPDs are systematically sampled over the 4-week reporting period such that about 100 ED encounters and about 150–200 OPD encounters are selected. Hospital staff are asked to complete patient record forms (PRFs) for each sampled visit, but census field representatives typically abstract data for approximately two-thirds of these visits.

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, the hospital sample consists of approximately 500 hospitals, of which 80% have EDs and about one-half have eligible OPDs. Typically, about 1,000 clinics are selected from participating hospital OPDs.

In 2011, the number of PRFs completed for EDs was 31,084 and for OPDs was 32,233, and the hospital response rate was 80% for EDs and 67% for OPDs. In 2012, the number of PRFs completed for EDs was 29,453 and the hospital response rate was 64% for EDs. In 2013, the number of PRFs completed for EDs was 24,777 and the hospital response rate was 66% for EDs. OPD data for years after 2011 are not currently available and at present there is no timeline for their release.

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.

Reference

• McCaig LF, McLemore T. Plan and operation of the National Hospital Ambulatory Medical Care Survey. NCHS. Vital Health Stat 1994;1(34). Available from: http://www​.cdc.gov/nchs​/data/series/sr_01/sr01_034acc.pdf. [PubMed: 7975355]

For More Information

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

Overview

NIS is a continuing nationwide telephone sample survey to monitor vaccination coverage rates among children aged 19–35 months and among teenagers (NIS–Teen) aged 13–17. 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 nation, the 50 states, and selected local areas and 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 2015, the overall Council of American Survey Research Organizations (CASRO) response rate for NIS was 34.9%. Response rates for the landline and cellular telephone samples were 59.2% and 32.2%, respectively. Of the 4,522 age-eligible children with completed household interviews from the landline sample, 2,700 (59.7%) had adequate provider data. From the cellular telephone sample, 12,467 (55.5%) of the 22,453 eligible children with completed household interviews had adequate provider data.

The overall CASRO response rate for the 2015 NIS–Teen was 33.0%. Response rates for the landline and cellular telephone samples were 56.4% and 29.8%, respectively. Of the 8,961 age-eligible adolescents with completed household interviews from the landline sample, 4,784 (53.4%) had adequate provider data. From the cellular telephone sample, 17,091 (48.9%) of the 34,965 eligible adolescents with completed household interviews had adequate provider data.

Issues Affecting Interpretation

Starting with Health, United States, 2015, estimates are from the NIS website and may differ slightly from estimates published previously in Morbidity and Mortality Weekly Report (MMWR) articles.

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 three doses of a vaccine product that requires four doses were misclassified as fully vaccinated. For more information, see “Changes in measurement of Haemophilus influenzae serotype b (Hib) vaccination coverage—National Immunization Survey, United States, 2009. MMWR 2010;59:1069–72.”

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: http://www.cdc.gov/vaccines/imz-managers/coverage/nis/teen/apd-report.html, and for revised 2013 estimates based on the 2014 criteria, see: CDC. National, regional, state, and selected local area vaccination coverage among adolescents aged 13–17 years—United States, 2014. MMWR 2015;64(29):784–92. Available from: http://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

• CDC. Vaccination coverage among children aged 19–35 months—United States, 2015. MMWR 2016;65(39):1065–71. Available from: http://www​.cdc.gov/mmwr​/volumes/65/wr/pdfs/mm6539a4.pdf. [PubMed: 27711036]
• CDC. National, regional, state, and selected local area vaccination coverage among adolescents aged 13–17 years—United States, 2015. MMWR 2016;65(33):850–58. Available from: http://www​.cdc.gov/mmwr​/volumes/65/wr/pdfs/mm6533a4.pdf. [PubMed: 27561081]
• Smith PJ, Hoaglin DC, Battaglia MP, et al. Statistical methodology of the National Immunization Survey, 1994–2002. NCHS. Vital Health Stat 2005;2(138). Available from: http://www​.cdc.gov/nchs​/data/series/sr_02/sr02_138.pdf. [PubMed: 15789691]
• CDC. Announcement: Addition of households with only cellular telephone service to the National Immunization Survey, 2011. Available from: http://www​.cdc.gov/mmwr​/preview/mmwrhtml/mm6134a5​.htm?s_cid=mm6134a5_e%0d%0a.
• CDC. Changes in measurement of Haemophilus influenzae serotype b (Hib) vaccination coverage—National Immunization Survey, United States, 2009. MMWR 2010;59(33):1069–72. Available from: http://www​.cdc.gov/mmwr​/preview/mmwrhtml/mm5933a3​.htm?s_cid=mm5933a3_e%0d%0a. [PubMed: 20798669]

For More Information

See the NIS website at: http://www.cdc.gov/vaccines/nis.

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 provide a detailed snapshot of the myriad transactions that make up the economy—buying and selling goods and services, hiring of labor, investing, renting property, paying taxes, and the like. 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 and services produced by labor and property located in the United States. NIPA calculate GDP as the sum of familiar final expenditure components: personal consumption expenditures, private investment, government spending (consumption and investment), and net exports. 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 D.C. 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 on a quarterly, annual, and quinquennial basis. 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 three 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 use 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 occasionally be adjusted to account for special circumstances that affect the accuracy of the data. For example, quarterly and monthly NIPA estimates are seasonally adjusted 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: http://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: http://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: http://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. Washington, D.C.: BEA; 2006. Available from: http://www​.bea.gov/national​/pdf/nipaguid.pdf.

For More Information

See the BEA (NIPA) website at: http://www.bea.gov/national/index.htm.

Overview

The CDC National Notifiable Diseases Surveillance System (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 reportable diseases, which are nationally notifiable using uniform surveillance case definitions.

Coverage

Notifiable disease reports are received from health departments in the 50 states, five territories, D.C., 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 without personal identifiers. The system also provides annual summaries of the finalized data. CSTE and CDC annually review the status of national infectious 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, Q fever and tularemia became nationally notifiable in 2000. 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 cyclosporiasis 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 Report (MMWR) and in Summary of Notifiable Diseases, United States (before 1985, titled Annual Summary).

Issues Affecting Interpretation

NNDSS data must be interpreted in light of reporting practices. Some diseases that cause severe clinical illness (for example, 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.

Reference

• CDC. Summary of notifiable diseases—United States, 2014. MMWR 2016;63(54):1–152. Available from: http://www​.cdc.gov/mmwr/mmwr_nd/index​.html. [PubMed: 27736829]

For More Information

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

Overview

NNHS collected data from a nationally representative sample of nursing homes and provided national estimates on the characteristics of nursing homes and their residents and staff. Data about the facilities include characteristics such as bed size, ownership, Medicare/Medicaid certification, services offered, staff characteristics, expenses, and charges. Data about the current residents and discharges include demographic characteristics, health status, services received, and sources of payment.

Coverage

The initial NNHS, conducted in 1973–1974, included the universe of nursing homes that provided some level of nursing care and excluded homes providing only personal or domiciliary care. The 1977 NNHS encompassed all types of nursing homes, including personal care and domiciliary care homes. The 1985, 1995, 1997, 1999, and 2004 NNHS included only nursing homes that provided some level of nursing care and excluded homes providing only personal or domiciliary care, similar to the 1973–1974 survey.

Methodology

The survey used a stratified two-stage probability design. The first stage was the selection of facilities, and the second stage was the selection of residents and discharges. Prior to the 2004 NNHS, up to six current residents and/or six discharges were selected for each facility. The 2004 survey was designed to select only current residents, 12 from each facility, to participate in the survey. Information on the facility was collected through a personal interview with the administrator or with staff designated by the administrator. Resident data were provided by staff familiar with the care provided to the resident. Staff relied on the medical record and personal knowledge of the resident. Both live and deceased discharges were included. Residents were counted more than once if they were discharged more than once during the reference period. Resident rates are calculated using estimates of the civilian population of the United States, including institutionalized persons.

Sample Size and Response Rates

In 1973–1974, the sample of 2,118 homes was selected from nursing homes open for business in 1972. The 1977 NNHS sampled 1,698 homes. The sample for the 1985 survey consisted of 1,220 facilities. The 1995 sample was 1,500 nursing homes. For the 1997 survey, data were obtained from 1,488 nursing homes. The 1999 sample consisted of 1,496 nursing homes. In 1995, 1997, and 1999, facility-level response rates were over 93%. For the final NNHS in 2004, 1,500 nursing homes were selected and a facility response rate of 81% was achieved.

Issues Affecting Interpretation

Samples of discharges and residents contain different populations with different characteristics. The resident sample is more likely to contain long-term nursing home residents and, conversely, to underestimate short nursing home stays. Because short-term residents are less likely to be on the nursing home rolls on a given night, they are less likely to be sampled. Estimates of discharges underestimate long nursing home stays. The last NNHS was conducted in 2004; nursing home data is now available from the National Study of Long-Term Care Providers (NSLTCP).

References

• Van Nostrand JF, Zappolo A, Hing E, Bloom B, Hirsch B, Foley DJ. The National Nursing Home Survey: 1977 summary for the United States. Vital Health Stat 13(43). Hyattsville, MD: NCHS; 1979. Available from: http://www​.cdc.gov/nchs​/data/series/sr_13/sr13_043.pdf. [PubMed: 506073]
• Hing E, Sekscenski E, Strahan G. The National Nursing Home Survey: 1985 summary for the United States. Vital Health Stat 13(97). Hyattsville, MD: NCHS; 1989. Available from: http://www​.cdc.gov/nchs​/data/series/sr_13/sr13_097.pdf. [PubMed: 2929143]
• Strahan GW. An overview of nursing homes and their current residents: Data from the 1995 National Nursing Home Survey. Advance data from vital and health statistics; no 280. Hyattsville, MD: NCHS; 1997. Available from: http://www​.cdc.gov/nchs/data/ad/ad280​.pdf. [PubMed: 10164984]
• Jones AL, Dwyer LL, Bercovitz AR, Strahan GW. The National Nursing Home Survey: 2004 overview. Vital Health Stat 13(167). Hyattsville, MD: NCHS; 2009. Available from: http://www​.cdc.gov/nchs​/data/series/sr_13/sr13_167.pdf. [PubMed: 19655659]

For More Information

See the NNHS website at: http://www.cdc.gov/nchs/nnhs.htm.

Overview

NSLTCP is a biennial study to monitor the major sectors of paid, regulated long-term care services. NSLTCP uses administrative data from the Centers for Medicare & Medicaid Services (CMS) about the home health, nursing home, and hospice sectors and collects survey data on the residential care community and adult day services sectors. Information includes the supply, organizational characteristics, staffing, and services offered by providers of long-term care services and the demographic, health, and functional status of users of these services. NSLTCP replaces NCHS’ periodic National Nursing Home Survey and National Home and Hospice Care Survey, and the one-time National Survey of Residential Care Facilities.

Coverage

The initial NSLTCP, conducted in 2012, included providers that were licensed, registered, listed, certified, or otherwise regulated by the federal or state governments.

Methodology

Data on adult day services centers and residential care communities were obtained through surveys. Information on nursing homes, home health agencies, or hospices was obtained from CMS administrative records.

Survey data were collected through three modes: self-administered, hard copy mail questionnaires; self-administered web questionnaires; and computer-assisted telephone interview (CATI) interviews. To the extent possible, the questionnaires included topics comparable across all five LTC sectors, as well as topics specific to the particular sector.

The sampling frame from the National Adult Day Services Association (NADSA) contained 5,678 self-identified adult day services centers; duplicates were removed from the frame, leaving 5,443 centers. Centers were eligible if they: 1) were licensed or certified by the state or Medicaid; 2) had average daily attendance of at least one participant based on a typical week; and 3) had at least one participant enrolled at the center at the time of the survey.

Data from residential care communities included a mix of sampled communities from states that had enough residential care communities to produce reliable state estimates and a census of residential care communities in states that did not have enough communities to produce reliable state estimates. The sampling frame of 40,583 residential care communities was constructed from lists of licensed residential care communities obtained from the state licensing agencies in each of the 50 states and the District of Columbia. Sampling weights were used only for residential care communities where a sample was drawn. To be eligible for the survey, residential communities had to be state-licensed with four or more licensed beds; provide room and board of at least two meals a day, around-the-clock supervision, and offer assistance with personal care (like dressing) or health-related services (such as medication management); have at least one resident; and serve primarily an adult population.

Every nursing home, home health agency, or hospice in the United States that was certified to provide services under Medicare, Medicaid, or both, and had user data, was included in the data. Facility data was obtained from the CMS’ administrative records in Certification and Survey Provider Enhanced Reporting ([CASPER], formerly known as Online Survey Certification and Reporting); the third quarter file of the data year was used. User data were obtained from the assessment and beneficiary files that CMS has for each of the three provider types and aggregated to the provider level.

Sample Size and Response Rates

Every certified nursing home, home health agency, and hospice with user information, and all users during the data time frame, was included. Of the 4,751 in-scope and presumed in-scope adult day services centers in 2014, 2,763 completed the questionnaire, for a response rate of 58.0%. Although a census of all adult day services centers was attempted, estimates were subject to variability due to the amount of nonresponse; this variability associated with the nonresponse was treated as if it were from a stratified (by state) sample without replacement. From 40,583 residential communities in the sampling frame, 11,618 residential care communities were sampled of which 10,415 were deemed eligible; 5,380 communities could not be contacted by the end of data collection. This yielded a weighted response rate of 49.6%.

Issues Affecting Interpretation

The estimates for adult day services center participants, nursing home residents, and residential care community residents are for current service users on any given day, rather than all users in a year. The estimate for home health patients includes only those who ended care in the prior year (discharges). The same person may be included in this sum more than once, if a person received care in more than one sector in a similar time period (e.g., a residential care resident receiving care from a home health agency). While every effort was made to match question wording in the NSLTCP surveys to the administrative data available through CMS, some differences remained and may affect comparisons between these two data sources. For example, because not all LTC providers are residential, information on capacity is not comparable across provider types. In addition, different data sources used different reference periods. For instance, user-level data used for home health agencies and hospices were from patients who received home health or hospice care services at any time in calendar year prior to the survey. In contrast, survey data on residential care community residents and adult day services center participants, and CMS data on nursing home residents, were from current users on any given day or active residents on the last day of the third quarter of the data year.

References

• Harris-Kojetin L, Sengupta M, Park-Lee E, Valverde R, Caffrey C, Rome V, Lendon J. Long-term care providers and services users in the United States: Data from the National Study of Long-Term Care Providers, 2013–2014. National Center for Health Statistics. Vital Health Stat 3. (38)2016. Available from: http://www​.cdc.gov/nchs​/data/series/sr_03/sr03_038.pdf. [PubMed: 27023287]
• Harris-Kojetin L, Sengupta M, Park-Lee E, Valverde R. Long-term care services in the United States: 2013 overview. National Center for Health Statistics. Vital Health Stat 3. (37)2013. Available from: http://www​.cdc.gov/nchs​/data/series/sr_03/sr03_037.pdf. [PubMed: 26158640]
• Sengupta M, Valverde R, Lendon JP, Rome V, Caffrey C, Harris-Kojetin L. Long-term care providers and services users in the United States—State estimates supplement: National Study of Long-Term Care Providers, 2013–2014. Hyattsville, MD: National Center for Health Statistics. 2016. Available from: http://www​.cdc.gov/nchs​/data/nsltcp/2014​_nsltcp_state_tables.pdf. [PubMed: 27023287]

For More Information

See the NSLTCP website at: http://www.cdc.gov/nchs/nsltcp/index.htm.

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 household population of the United States (50 states and D.C.). 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.

Methodology

The 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 multi-stage probability-based, nationally representative sample of the household population aged 15–44. Black and Hispanic adults, as well as all 15- to 19-year-olds are oversampled. Interviews are administered in person by trained female interviewers using a laptop or notebook computer with computer-assisted personal interviewing (CAPI) or audio computer-assisted self-interview (ACASI) 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 (for example, if there was a 1 in 5,000 chance that a woman would be selected for the sample, her sampling weight was 5,000); (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

• Public Use Data File Documentation: 2011–2013 National Survey of Family Growth User’s Guide. Hyattsville, MD: NCHS; 2014. Available from: https://www​.cdc.gov/nchs​/data/nsfg/nsfg_2011-2013​_userguide_maintext.pdf.
• Public Use Data File Documentation: 2013–2015 National Survey of Family Growth User’s Guide. Hyattsville, MD: NCHS; 2016. Available from: https://www​.cdc.gov/nchs​/data/nsfg/nsfg_2013​_2015_userguide_maintext.pdf.

For More Information

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

Overview

NSDUH reports on the prevalence, incidence, and patterns of drug and alcohol use and abuse in the general U.S. civilian noninstitutionalized population aged 12 and over. NSDUH also reports on substance use disorders, substance use treatment, health care, mental disorders, and mental health service utilization.

Coverage

NSDUH is representative of persons aged 12 and over in the civilian noninstitutionalized population of the United States, and in each state and 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 and hospitals.

Methodology

The data collection method is in-person interviews conducted with a sample of individuals at their place of residence. Computer-assisted interviewing (CAI) methods, including audio computer-assisted self-interviewing (ACASI), 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. Each state was stratified into approximately equally populated state sampling regions (SSRs), and then census tracts within each SSR were selected, 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.

In addition, 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 and many state estimates as well as 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 or older. 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

Nationally, 132,210 household addresses were successfully screened for the 2015 survey, conducted from January to December 2015. In 2015, screening was completed at 132,210 addresses, and 68,073 completed interviews were obtained, including 16,955 interviews from adolescents aged 12–17 and 51,118 interviews from adults aged 18 or over. Weighted response rates were 79.7% for household screening and 69.3% for interviewing.

Issues Affecting Interpretation

Several improvements to the 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: http://www.samhsa.gov/data/NSDUH/NSDUHCensusEffects/Index.aspx.

The NSDUH questionnaire underwent a partial redesign in 2015 to improve the quality of NSDUH 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 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/NSDUH-TrendBreak-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 Survey (YRBS). 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 YRBS collect data in school classrooms. Further, NSDUH estimates are tabulated by age, whereas MTF and YRBS estimates are tabulated by grade, representing different ages as well as different populations.

References

• Substance Abuse and Mental Health Services Administration. 2014 National Survey on Drug Use and Health: Methodological summary and definitions. Rockville, MD: SAMHSA; 2015. Available from: http://www​.samhsa.gov​/data/sites/default​/files/NSDUH-MethodSummDefs2014​/NSDUH-MethodSummDefs2014.pdf.
• Substance Abuse and Mental Health Services Administration. Results from the 2014 National Survey on Drug Use and Health: Detailed tables. Rockville, MD: SAMHSA; 2015. Available from: http://www​.samhsa.gov​/data/sites/default​/files/NSDUH-DetTabs2014​/NSDUH-DetTabs2014.htm.
• Substance Abuse and Mental Health Services Administration. Key substance use and mental health indicators in the United States: Results from the 2015 National Survey on Drug Use and Health. Rockville, MD: SAMHSA; 2016. Available from: https://www​.samhsa.gov​/data/sites/default​/files/NSDUH-FFR1-2015​/NSDUH-FFR1-2015/NSDUH-FFR1-2015.pdf.
• Substance Abuse and Mental Health Services Administration. Results from the 2015 National Survey on Drug Use and Health: Detailed tables. Rockville, MD: SAMHSA; 2016. Available from: https://www​.samhsa.gov​/data/sites/default​/files/NSDUH-DetTabs-2015​/NSDUH-DetTabs-2015​/NSDUH-DetTabs-2015.htm.

For More Information

See the NSDUH website at: http://www.samhsa.gov/data/population-data-nsduh and the Center for Behavioral Health Statistics and Quality (the data collection agency) website at: http://www.samhsa.gov/about-us/who-we-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 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 through the Vital Statistics Cooperative Program (VSCP) 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 VSCP.

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 birth certificate included items to identify the Hispanic parentage of newborns and to expand information about maternal and infant health characteristics. 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, but full implementation in all states and territories will be phased in over several years. The 2003 revision of the birth certificate included changes in ascertainment of education level, prenatal care, and tobacco use during pregnancy. The 2003 revision of the death certificate included changes in the ascertainment of multiple races, education level, 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

Two-thirds (66%) of all births in 2009, 76% in 2010, 83% in 2011, 86% in 2012, 90% in 2013, 96% in 2014, and 97% in 2015 were reported using the 2003 revision of the U.S. Standard Certificate of Live Birth. 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.

Reference

• Martin JA, Hamilton BE, Osterman MJK, Driscoll AK, Mathews TJ. Births: Final data for 2015. National vital statistics report, vol 66, no 1. Hyattsville, MD: NCHS. 2017. Available from: https://www​.cdc.gov/nchs​/data/nvsr/nvsr66/nvsr66_01.pdf. [PubMed: 28135188]

For More Information

See the Birth Data website at: http://www.cdc.gov/nchs/births.htm, and Vitalstats at: http://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 Guide available from the NCHS website at: http://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 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 2014, seven 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

• NCHS. User guide to the 2014 Fetal Death public use file. Hyattsville, MD. Available from: ftp://ftp​.cdc.gov/pub​/Health_Statistics/NCHS​/Dataset_Documentation​/DVS/fetaldeath​/2014FetalUserGuide.pdf.
• MacDorman MF, Gregory ECW. Fetal and perinatal mortality: United States, 2013. National vital statistics reports; vol 64 no 8. Hyattsville, MD: NCHS; 2015. Available from: http://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: NCHS; 2014. Available from: http://www​.cdc.gov/nchs​/data/databriefs/db169.htm. [PubMed: 25408960]
• MacDorman MF, Kirmeyer SE, Wilson EC. Fetal and perinatal mortality, United States, 2006. National vital statistics report; vol 60 no 8. Hyattsville, MD: NCHS; 2012. Available from: http://www​.cdc.gov/nchs​/data/nvsr/nvsr60/nvsr60_08.pdf. [PubMed: 24979970]

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 U.S. exclude deaths of nonresidents of the U.S. 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 U.S. (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 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 the World Health Organization (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 nation’s death records.

Data for the entire United States refer to events occurring within the United States; 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

The ICD, by which cause of death is coded and classified, is revised approximately every 10–20 years. Because revisions of the 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 the ICD were made only when a new revision of the ICD was implemented. A process for updating the ICD was introduced with the 10th revision (ICD–10) that allows for mid-revision 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. (2009).

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, Kochanek KD, Xu JQ, Curtin SC. Deaths: Final data for 2015. Hyattsville, MD: NCHS; 2017. Available from: http://www​.cdc.gov/nchs/products/nvsr​.htm. [PubMed: 29235985]
• Kochanek KD, Murphy SL, Xu JQ, Tejada-Vera B. Deaths: Final data for 2014. National vital statistics reports; vol 65 no 4. Hyattsville, MD: NCHS; 2016. Available from: https://www​.cdc.gov/nchs​/data/nvsr/nvsr65/nvsr65_04.pdf. [PubMed: 27378572]
• Heron M, Hoyert DL, Murphy SL, et al. Deaths: Final data for 2006. National vital statistics reports; vol 57 no 14. Hyattsville, MD: NCHS; 2009. Available from: http://www​.cdc.gov/nchs​/data/nvsr/nvsr57/nvsr57_14.pdf. [PubMed: 19788058]
• NCHS. Multiple causes of death in the United States. Monthly vital statistics report; vol 32 no 10 suppl 2. Hyattsville, MD: NCHS; 1984. Available from: http://www​.cdc.gov/nchs​/data/mvsr/supp/mv32_10s2.pdf.

For More Information

See the Mortality Data website at: http://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 race and ethnicity 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 (4.0% in 2014) than for live births (0.1% in 2014). In 2014, not-stated birthweight was imputed for 0.10% 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 is being adopted by states on a voluntary, rolling basis.

Reference

• Mathews TJ, Driscoll AK. Trends in infant mortality in the United States, 2005–2014. NCHS data brief, no 279. Hyattsville, MD: NCHS; 2017. Available from: https://www​.cdc.gov/nchs​/products/databriefs.htm. [PubMed: 28437240]
• Mathews TJ, MacDorman MF, Thoma ME. Infant mortality statistics from the 2013 period Linked Birth/Infant Death data set. National vital statistics report; vol 64 no 9. Hyattsville, MD: NCHS; 2015. Available from: http://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

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 nation; the 50 states and 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/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 2015 employment and wage estimates are based on all data collected from establishments sampled in the May 2015, November 2014, May 2014, November 2013, May 2013, and November 2012 semiannual panels. The overall national response rate for the six panels is 73.5% based on establishments and 69.6% based on weighted sampled employment in the 50 states and D.C.

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 plus 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 healthcare occupations are presented in Health, United States.

OES estimates for 1999 through 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 http://www.bls.gov/oes/oes_ques.htm. OES estimates for 2012 to 2015 classified occupations according to the 2010 SOC system.

Reference

• Bureau of Labor Statistics. Occupational employment and wages, May 2015. Washington, DC: U.S. Department of Labor; 2016. Available from: http://www​.bls.gov/OES/.

For More Information

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

Reference

• Ingram DD, Parker JD, Schenker N, et al. United States Census 2000 population with bridged race categories. NCHS. Vital Health Stat 2003;2(135). Available from: http://www​.cdc.gov/nchs​/data/series/sr_02/sr02_135.pdf. [PubMed: 14556588]

For More Information

See the U.S. Census Bureau website at: http://www.census.gov and the NCHS website for U.S. Census populations with bridged race categories at: http://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 its predecessor 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 (CRG; Anacortes, WA) and published in the group’s Nursing Home Statistical Yearbook series.

References

• Cowles CM, ed. Nursing home statistical yearbooks for 2003–2015. Anacortes, WA: CRG; published 2004–2016, respectively. Available from: http://www​.longtermcareinfo​.com/publications​/nursing-home-statistical-yearbook​.php.
• Centers for Medicare & Medicaid Services. Certification and compliance. Baltimore, MD: CMS; 2005. Available from: http://www​.cms.gov/CertificationandComplianc/01_overview.asp.

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 CRG 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 chancroid, chlamydia, gonorrhea, and syphilis. Enhanced surveillance of these conditions and surveillance of other STDs, such as genital herpes simplex virus, genital warts or 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, D.C., selected cities, 3,142 U.S. counties, and outlying areas consisting of U.S. dependencies, possessions, and independent nations 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 (NNDSS), 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.

Reference

• CDC. Sexually transmitted disease surveillance 2015. Atlanta, GA: CDC; 2016. Available from: http://www​.cdc.gov/std/stats15/default​.htm.

For More Information

See the STD Data and Statistics website at: http://www.cdc.gov/std/stats and the STD Diseases & Related Conditions website at: http://www.cdc.gov/std/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 28% 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 WHO Classification of Tumours of Haematopoietic and Lymphoid Tissues (2008). 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 Census Bureau. Life tables used to determine general population life expectancy when calculating relative survival rates were obtained from NCHS 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 (NAACCR) 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 (CHSDA) counties within SEER reporting areas. This change is believed to produce estimates that more accurately reflect the incidence rates for this population group. More information on CHSDA is available from: http://www.ihs.gov/chs/index.cfm?module=chs_requirements_chsda. For more information on SEER estimates by race and ethnicity, see: http://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.

Reference

• Howlader N, Noone AM, Krapcho M, Miller D, Bishop K, Altekruse SF, et al. (eds). SEER Cancer Statistics Review, 1975–2013, National Cancer Institute. Bethesda, MD, based on November 2015 SEER data submission, posted to the SEER website, April 2016. Available from: http://seer​.cancer.gov/csr/1975_2013/.

For More Information

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

Overview

YRBS monitors health risk behaviors among students in grades 9–12 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, YRBS 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 YRBS 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 9–12 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 9–12 were sampled with probability proportional to school enrollment size. The third stage of sampling consisted of random sampling in each of grades 9–12, 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 YRBS 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 YRBS 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 YRBS differ from the National Survey on Drug Use & 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 YRBS collect data in school classrooms. In addition, NSDUH estimates are tabulated by age, whereas MTF and YRBS estimates are tabulated by grade, representing different ages as well as different populations. All YRBS data collection is anonymous.

References

• Brener ND, Kann L, Shanklin SL, et al. Methodology of the Youth Risk Behavior Surveillance System—2013. MMWR 2013;62(RR01):1–23. Available from: http://www​.cdc.gov/mmwr​/preview/mmwrhtml/rr6201a1.htm. [PubMed: 23446553]
• Kann L, Kinchen S, Shanklin SL, et al. Youth Risk Behavior Surveillance—United States, 2013. MMWR Surveill Summ 2014;63(SS–4):1–172. Available from: http://www​.cdc.gov/mmwr/pdf/ss/ss6304​.pdf. [PubMed: 22673000]
• Kann L, McManus T, Harris WA, et al. Youth Risk Behavior Surveillance—United States, 2015. MMWR Surveill Summ 2016;65(SS–6):1–174. 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 2001;31(3):599–614.

For More Information

See the YRBS website at: http://www.cdc.gov/yrbs.