Establishing measurable national health objectives focused on disease and injury prevention and reduction of premature mortality has been a critical strategy for improving and protecting public health in the U.S. since the 1970s.7
The Healthy People in Every Stage of Life component of CDC's new Health Protection Goals measures improvements in health and quality of life using broad positive measures.2
The overall goals framework reflects the Institute of Medicine's recommendation that a short list of health status and risk-reduction measures, along with appropriate performance measures, will lead to a clearer focus on national health.32,33
CDC's short list of goals and associated outcome measures will track improvements in health status and healthy behaviors, guiding the agency's activities, its work with partners, and the allocation of its resources.
CDC is constructing the goals framework to be compatible with Healthy People 2010 and the Office of Management and Budget's performance assessment rating tool so that the agency will have one cohesive approach for targeting its resources and monitoring its progress.34,35
Efforts are also underway to retain consistency with past initiatives. While the Healthy People 2010 Leading Health Indicators (LHI) continue to be relevant in monitoring overall population health, the current Healthy People goals provide a complementary approach for monitoring health by life stage.36
To ensure historical continuity and compatibility across these two approaches, the LHI objectives are being used to help develop underlying objectives for the Healthy People goals. Creating a set of health outcome measures for the life-stage goals is one step toward establishing a goals-based performance system. Further research is needed to make all goals measurable by developing measures for the places, preparedness, and global goals.37
While the forecasting approach presented in this article can guide the development of attainable but ambitious targets, target-setting will require extensive programmatic and stakeholder input as well. Analytic support is needed to develop links between the measures of burden and program areas (e.g., healthy life expectancy and cancer prevention and control) for which objectives and performance measures are being developed. For example, CDC's immunization programs set specific immunization objectives that are critical for continued progress toward eliminating vaccine-preventable childhood diseases, which will eventually lead to improved health outcomes for children.
CDC goal teams, comprising experts from inside the agency, are working with external partners to develop objectives, measures, and recommendations for aligning CDC programs with the goals.1
Eventually, this will provide a cohesive framework that maps all program activities to the agency's overarching goals and broad mission. However, it is important to acknowledge that the health-status measures described in this article are not in themselves measures of CDC's performance; improving trends toward goal attainment might certainly reflect CDC's contribution, but captures the effect of other factors including the contribution of other key players and partners.
Although this is the first article to present a broad, unified framework for monitoring the Healthy People goals, multiple approaches are necessary for developing measurable goals and evaluating activities in support of the overall process. Developing this set of health outcome measures within the framework of the five life stages presented numerous methodological challenges. Because certain life stages have broad age ranges, substantial variation might exist in health risks by age within such age groups. Likewise, in defining the healthy weight indicator, multiple BMI categories with possible variations in health risks were grouped together. For particular programmatic needs, subgroup outcome measures (e.g., infant mortality or premature mortality for people aged 50 to 64 years) and behavioral indicators (e.g., physical activity or diet) will be used for measuring progress toward specific life-stage objectives. In addition, age-adjusted estimates will be monitored by goal action teams to assess the impact of targeted programs and activities.
Crude estimates, not adjusted for age, were used for the majority of measures (except HLE, which is an age-standardized measure independent of the age distribution) to maintain consistency in measures across life stages, as well as to retain the impact of aging. The implication of this approach must be highlighted for Older Adults and Seniors (≥50 years) because it masks considerable variation in health status that exists within this age group as well as the rapid impact of the changing age distribution over time. In addition, the growing share of minorities (e.g., Hispanic people) in the overall population is likely to affect the sentinel outcomes. Assessing the extent and impact of aging as well as other demographic (e.g., race/ethnicity) changes on risk factors and disease burden is critically important, but for appropriate policy relevance, they merit a separate, more comprehensive analysis.38,39
Availability of data systems and historical data were among the criteria for selection of health outcome measures; thus, outcomes supported by data that did not meet these criteria were not included. For example, available data systems do not provide optimal general measures of morbidity for Children and Adolescents. Recognition of major data gaps should emphasize the need for investment in measures development, including data systems to track them at the national, state, and local levels. Continued investment in surveys that can provide timely public-use data for comparable state- and county-level estimates is critical for ensuring participation of state and local public health agencies in tracking progress toward these goals.
Because of limited historical data for certain health outcome measures, forecasting was restricted to univariate time-series analyses. This restriction limits interpretation of the underlying associations among variables and assumes that both the variation in and the effect of exogenous variables is expressed in the past behavior of the series. The implication of this assumption is pertinent, particularly for mortality forecasts, because the life expectancy gains experienced from 1982 through 2004 are expected to exhibit diminishing returns in the future. Consequently, mortality targets that are challenging but attainable are likely to be below the projected forecasts. Thus, if conditions under which the past data were generated remain the same, this method will provide reasonably accurate short- and medium-term forecasts. Forecasts should be updated periodically to incorporate the impact of systemic changes (e.g., new technologies, epidemics, or wars) and other temporal changes (e.g., aging and increasing racial/ethnic diversity) in underlying conditions.
Further research is needed for improved summary measures of population health. The simple measure of respondent-assessed health status was chosen because of its validated reliability and its utility as a valid predictor of future health events, including death.40
In contrast, identifying the best construct for measuring healthy life expectancy is complex, but supported by active research that explores development of new multidimensional summary measures. The HLE measure was chosen because of its ability to continually monitor healthy life expectancy in the U.S., but it might be supplanted by improved measures of healthy life expectancy developed in this evolving field.