Moderator:
Christopher G. Atchison, MPA
Director, Iowa Department of Public Health

Panelists:
Harry Rosenberg, PhD
Chief of Mortality Statistics Branch, Division of Vital Statistics, National Center for Health Statistics, Centers for Disease Control and Prevention

Three critical data issues:

1. Implementation of ICD-10 (International Statistical Classification of Diseases and Related Health Problems) for mortality.
2. Implementation of a new population standard for age-adjusted death rates from 1940 to the projected 2000 standard.
• New policy of DHHS chances 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.
3. Implementation of new guideline for collecting and tabulating race statistics.

• Allows for the selection of more than one race and Hispanic origin.
• 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?

Tom Doremus, MS
Information and Communications Specialist, 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 is 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 was 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 exists

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.

• "Better than the best" is a good method because we should improve the overall health of every person.
• With regards to data on disability, there is no consensus on "disability" and the status of the data is poor.
• Technical assistance for GIS systems is needed as well as understanding and interpreting data for communities, localities and states.
• How prepared is the workforce to explain data issues? It is crucial that they can interpret and use the data.
• Race/ethnicity should not be viewed using a biomedical model but as a social construct
• With regards to birth and death records:
• They are both a legal and statistical document.
• They cannot overburden with questions of health/statistical nature.
• They should limit on type of information that can be collected.
• Race versus identity: if race is X, but culture is Y, what do you mark? If race is not genetic, then what is the importance of race?

Chicago Transcripts and Summaries