tem, the opportunities far outweigh the challenges. In addition to an ethical mandate to know what is happening to children (e.g., when they are at risk, whether their health is changing for the better or worse), a solid data foundation to monitor risks and changes in health is crucial to evidence-based policy making and accountability, particularly in an environment in which states are being given more decision-making responsibilities. There is also a clear need to better understand and act on disparities in health to ensure the long-term productivity of the nation and the health of its citizens.

The chapter begins with definitions and then provides descriptions of data systems, including examples of state and local efforts to build children’s health data systems and federal efforts to encourage such systems. It then outlines the needed steps that would facilitate all states and communities using available data to monitor their children’s health and the influences on it.


For purposes of this report, data are tools to measure health, influences, and their indicators. A data element is a specific component of data with a clear, standardized definition to ensure that the numbers collected accurately represent the component. Age, birthweight, income, source of insurance, educational level completed, and race are examples of data elements. A dataset refers to observations and measurements collected through a single mechanism, effort, or type of scientific investigation. For example, data from a range of questions asked by a survey, such as the census or the National Health Interview Survey, is a dataset. Other examples of datasets are law enforcement records (e.g., incidence of domestic violence, juvenile arrests, and homicides), vital records (e.g., birth, death, marriage, and divorce records), immunization registries, newborn metabolic screening results, program encounter data, results of school readiness assessments, reports of childhood abuse, and health data for children in foster care. A data system is an integrated system of multiple datasets, including the combination of software and hardware that makes possible the manipulation or interpretation of data and datasets.

Data integration refers to the combination of data from more than one dataset into a data system. Data integration facilitates maximal use of data and improves surveillance of children’s health and the factors that affect it. Single datasets allow an assessment of only a narrow set of aspects of health. Data integration can involve either aggregation of data from multiple datasets or linkage of multiple datasets at the individual level.


Good integrated data systems increase knowledge that can be used by states, communities, and policy makers who design policies and fund interventions that

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