Diane Wagener, PhD
Director, Data Monitoring and Analysis Branch, Division of Health Promotion Statistics, National Center for Health Statistics, CDC

Mary Ann Freedman, MA.
Director, Division of Vital Statistics, National Center for Health Statistics, CDC

Three critical data issues:

1. Implementation of ICD-10 (International Statistical Classification of Diseases and Related Health Problems) for mortality.
   
• Change in code categories for diseases and other health problems.
2. Implementation of a new population standard for age-adjusted death rates from 1940 to the projected 2000 standard.
   
• New policy of DHHS changes the population weights from 1940 to projected 2000
• This is in response to 1) the need to update, 2) recognizing that the 1940 population does not reflect that of today, and 2) elimination of the current use of multiple standards.
• Because of the different characteristics between the 1940 population and projected 2000 population, there will be changes in statistical rates simply because of the change to the projected 2000 standard (e.g. starting in 1999, there will be an "apparent" doubling of deaths related to heart disease). This highlights the critical need to clearly communicate the effects of switching to a new standard.
• This also has implications for race/ethnicity differentials - need to be prepared to communicate the effects of this change (e.g. numerical disparities between races may change because of the change in population standard)
• Would have to readjust Healthy People goals
• This is concurrent with the implementation of ICD-10.
3. Implementation of new guideline for collecting and tabulating race statistics
   
• Allows for the selection of more than one race and Hispanic origin for the 2000 Census.
• New guideline may affect comparability among races.
• Important for revised birth and death certificates: How and when to collect information on vital records according to OMB Directive 15? Quality and completeness of information?

Ron Bialek, MPA
Executive Director, Public Health Foundation

From: Measuring Health Objectives and Indicators: 1997 State and Local Capacity Survey

1. What we have:
   
• Consensus set of 18 health status indicators (developed from Objective 22.1 of Healthy People 2000).
• Usefulness of health status indicators for Healthy People 2000?
• Found that data are important in driving objectives; availability of baseline data influenced the selection of objectives.
• Vital statistics most frequently used for measuring objectives.
• Turnaround time to get mortality data to localities is around 2 years.
2. What we know:
   
• Gaps in Healthy People 2010 Objectives.
• Baseline data were generally not available at local level.
• Timeliness of tracking data improved over baseline data.
• Lack of data systems and staff perceived as leading barriers to tracking state objectives.
• Staffing needs, data sharing/linking, and new data collection systems dominated states’ wish lists.
• Private sector data were a significant source of data for some states.
3. What we need:
   
• Refine and promote consensus set of health status indicators.
• Enhance existing information systems to provide valid and reliable data to local jurisdictions.
• Identify and communicate current efforts so that models will be identified.
• Training of staff.
• Enhance sharing of data across agencies.

In summary:

• Consensus set of indicators make a big difference.
• Need to improve behavioral, chronic disease, access, and environmental health data.
• Need to better use what already exist.

Ron Wilson
Consultant, National Center for Health Statistics, CDC

Theme: Do changes in indicators of health indicate changes in health?

• Quality of small area data for tracking objectives: 1) are local data comparable to national data? 2) are sample sizes large enough to measure change?
• Will measures change in the right direction (e.g., domestic abuse reports could increase with greater emphasis and better reporting)?
• Purpose of local data: identify problems and track progress.
• Need data to evaluate programs (need highest quality data).
• Local data cannot afford to have big sample sizes, so it is crucial to have good quality data at the local level.
• Are local data comparable to national data?
• With regards to developmental objectives in Healthy People 2010, it is difficult to collect quality data when the outcome is not clear.
• Data leadership is needed to educate the public of the potential and limitations of data.
• More evaluation is needed; funding for programs need to be sustained so that long-term impact studies can be conducted.

Olivia Carter-Pokras, PhD
Director, Division of Policy and Data, Office of Minority Health

• Racial data presented for many but not all people-specific objectives.
• Racial data only shown for those with greatest disparities.
• If data were missing, not clear whether data 1) were not available or 2) did not show a disparity.
• Latest data show many widening gaps.
• For Healthy People 2010, recommended that baseline and monitored data be presented for each people-specific objective for at least 5 major race groups; when possible, SES data would be presented but not broken out by race.
• 2 approaches: 1) For 3 types of objectives, targets will be set that reported improvements for all segments of the population (better than the best); 2) For one type of objective, targets will be selected that represent improvements for the majority of the population.
• 2 policy decisions: 1) attack poverty itself? or 2) Target all poor persons? Universal insurance cannot eliminate disparity because of effects of poverty.
• Unexplained health disparities could reflect 1) inadequacies in controlling for changes in social class, 2) failure to consider the effects of social class in earlier life, and 3) intergenerational effects of social class.

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