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Healthy People 2010 Criteria for Data Suppression

Healthy People 2010 Criteria for Data Suppression. Suzanne E. Proctor, M.S.P.H. National Center for Health Statistics. Introduction. Presentation of data for Healthy People 2010 is complex . - Many data sources. - Many data sources. - Data are shown for numerous population groups.

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Healthy People 2010 Criteria for Data Suppression

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  1. Healthy People 2010 Criteria for Data Suppression Suzanne E. Proctor, M.S.P.H. National Center for Health Statistics

  2. Introduction • Presentation of data for Healthy People 2010 is complex - Many data sources - Many data sources - Data are shown for numerous population groups

  3. Major data systemsNo. objectives tracked* National Health Interview Survey (NHIS) 67 National Health and Nutrition Examination Survey (NHANES) 35 National Vital Statistics System – Mortality (NVSS-M) 32 National Survey on Family Growth (NSFG) 14 National Hospital Discharge Survey (NHDS) 11 Youth Risk Behavior Surveillance System (YRBSS) 11 HIV/AIDS Surveillance System 10 Behavioral Risk Factor Surveillance System (BRFSS) 9 National Household Survey on Drug Abuse (NHSDA) 8 School Health Policies and Programs Study (SHPPS) 8 National Vital Statistics System – Natality (NVSS-N) 8 National Profile of Local Health Departments (NPLHD) 8 National Ambulatory Medical Care Survey (NAMCS) 7 United States Renal Data System (USRDS) 7 STD Surveillance System (STDSS) 7 Medical Expenditure Panel Survey (MEPS) 6 National Hospital Ambulatory Medical Care Survey (NHAMCS) 6 Continuing Survey of Food Intake by Individuals (CSFII) 6 National Crime Victimization Survey (NCVS) 6 1999 National Worksite Health Promotion Survey (NWHPS) 5 State Tobacco Activities Tracking and Evaluation System (STATES) 5 National Notifiable Disease Surveillance System (NNDSS) 5 Monitoring the Future (MTF) 5 * At the national level 286 (60%)

  4. Introduction • Presentation of data for Healthy People 2010 is complex - Many data sources - Data are shown for numerous population groups

  5. Population group, year Condition Measure Total Race and Ethnicity American Indian or Alaska Native Asian or Pacific Islander Asian Native Hawaiian or Other Pacific Islander Black or African American White Hispanic or Latino Not Hispanic or Latino Black or African American White Gender Female Male Education level or Family Income level Less than high school Poor High school graduate Near poor At least some college Middle or high income

  6. Data not available DNC: Data are not collected DNA: Data are collected but are not yet analyzed DSU: Data are suppressed – data do not meet criteria for statistical reliability data quality, or confidentiality

  7. Data are suppressed (DSU) • Each data system has its own criteria for data suppression • HP2010 uses the criteria specified by each data system • Criteria are affected by the type of data system - Sample surveys - Population-count systems

  8. Sample surveys

  9. No. Objectives Survey Tracked Major Sample Surveys National Health Interview Survey (NHIS) 67 National Health and Nutrition Examination Survey (NHANES) 35 National Survey on Family Growth (NSFG) 14 National Hospital Discharge Survey (NHDS) 11 Youth Risk Behavior Surveillance System (YRBSS) 11 Behavioral Risk Factor Surveillance System (BRFSS) 09 National Household Survey on Drug Abuse (NHSDA) 08 School Health Policies and Programs Study (SHPPS) 08 National Ambulatory Medical Care Survey (NAMCS) 07 Medical Expenditure Panel Survey (MEPS) 06 National Hospital Ambulatory Medical Care Survey (NHAMCS) 06 Continuing Survey of Food Intake by Individuals (CSFII) 06 National Crime Victimization Survey (NCVS) 06 1999 National Worksite Health Promotion Survey (NWHPS) 05 Monitoring the Future (MTF) 05

  10. Major reasons for DSU • Sample design does not produce representative estimates • High item non-response • Number of events is too small to produce reliable estimates

  11. Major reasons for DSU • Sample design does not produce representative estimates • High item non-response • Number of events is too small to produce reliable estimates

  12. National Health and Nutrition Examination Survey • National interview and examination survey assessing health and nutrition status - Annual sample size ~ 5,000 - Stratified, multi-stage sampling scheme - Over sampling of Mexican Americans • Data are suppressed for Hispanics (total) - Geographic selection procedures - Reliable estimates can be made for Mexican Americans

  13. Major reasons for DSU • Sample design does not produce representative estimates • High item non-response • Number of events is too small to produce reliable estimates

  14. National Hospital Discharge Survey • Annual survey collecting information on hospital visits and discharges - Three-stage probability sampling scheme - Annual sample size ~ 300,000 medical records • Data are suppressed for Hispanics - Hispanic origin missing for ~ 75% of the NHDS records in 1992 (Kozak 1995)

  15. Major reasons for DSU • Sample design does not produce representative estimates • High item non-response • Number of events is too small to produce reliable estimates

  16. National Health Interview Survey • Annual personal interview survey assessing health behaviors, outcomes, and resources - National sample size ~ 43,000 households - Stratified, multi-stage sampling scheme • In some cases, data are suppressed for AI/AN and API groups - Too few cases in a single data year - May be possible to combine data for several years

  17. Major reasons for DSU • Sample design does not produce representative estimates • High item non-response • Number of events is too small to produce reliable estimates Data Quality Statistical Reliability

  18. Criteria for DSU Example Measure(s)Data systemCriteria Reason Relative standard error NHSDA > 17.5% Reliability Numerator count NCVS < 10 Reliability Denominator count BRFSS < 50 Reliability Coefficient of variation CSFII > 30% or Variance inflation factor n < 30*VIF Reliability Denominator count NHANES < 30 or Relative standard error > 30% Reliability

  19. Population-count systems

  20. Major Population-Count Systems No. Objectives Tracked Data System National Vital Statistics System – Mortality (NVSS-M) 32 HIV/AIDS Surveillance System 10 National Vital Statistics System – Natality (NVSS-N) 8 National Profile of Local Health Departments (NPLHD) 8 United States Renal Data System (USRDS) 7 STD Surveillance System (STDSS) 7 National Notifiable Disease Surveillance System (NNDSS) 5

  21. Major reason for DSU • Number of events is small - random error is of concern - confidentiality is of concern

  22. Major reason for DSU • Number of events is small - random error is of concern - confidentiality is of concern

  23. National Vital Statistics System • NCHS system that compiles data from birth and death certificates provided by the States - Data for HP2010 are based on resident deaths/births filed in the 50 States and DC • Rates, proportions, and ratios are suppressed if they are based on < 20 events - < 20 events corresponds to a RSE of > 23%

  24. Source: National Vital Statistics System, CDC, NCHS.

  25. Major reason for DSU • Number of events is small - random error is of concern - confidentiality is of concern

  26. STD Surveillance System • CDC system that compiles State data on new STD cases - 50 States and DC report cases on a monthly basis - Disease-specific and demographic information • Data release policies differ by geographic level - National: No restrictions - State: Demographic-specific frequencies based on < 3 cases reported as “< 3” - County: Frequencies based on < 5 cases reported as “< 5 ”. No rates reported.

  27. Criteria for DSU Measure Data system Criteria Reason Numerator count NVSS-M < 20 Reliability Numerator count HIV-AIDS < 4 Confidentiality Numerator count STDSS < 6 (county) Confidentiality < 4 (state) - - - (national) Example

  28. Other Issues

  29. Reliability of compound statistics • Compound statistic - produced from two or more statistics e.g. ratio with numerator and denominator derived from different data systems • 4 HP2010 measures are compound statistics • Reliability of a compound statistic requires consideration of its component parts

  30. Race/ethnicity classification • 1997 OMB directive: Revised standards for collecting and presenting data on race and ethnicity • Federal data systems must implement by 2003 • May affect the ability of data systems to report estimates for newly-defined groups

  31. For more information

  32. Resources available on-line Data suppression Healthy People Statistical Note No. 24 Major data systems Tracking Healthy People 2010 (Part C) Healthy People 2010 www.cdc.gov/nchs/hphome.htm

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