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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

Healthy People 2010 Criteria for Data Suppression

Suzanne E. Proctor, M.S.P.H.

National Center for Health Statistics

introduction
Introduction
  • Presentation of data for Healthy People

2010 is complex

- Many data sources

- Many data sources

- Data are shown for numerous population groups

slide3

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%)

introduction4
Introduction
  • Presentation of data for Healthy People

2010 is complex

- Many data sources

- Data are shown for numerous population groups

slide5

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

data not available
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

data are suppressed dsu
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

slide10

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

major reasons for dsu
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
major reasons for dsu12
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
national health and nutrition examination survey
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

major reasons for dsu14
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
national hospital discharge survey
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)

major reasons for dsu16
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
national health interview survey
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

major reasons for dsu18
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

criteria for dsu
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

slide21

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

major reason for dsu
Major reason for DSU
  • Number of events is small

- random error is of concern

- confidentiality is of concern

major reason for dsu23
Major reason for DSU
  • Number of events is small

- random error is of concern

- confidentiality is of concern

national vital statistics system
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%

major reason for dsu26
Major reason for DSU
  • Number of events is small

- random error is of concern

- confidentiality is of concern

std surveillance system
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.

criteria for dsu28
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

reliability of compound statistics
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

race ethnicity classification
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
slide34

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