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4
Existing Measures of Child
and Adolescent Health
Health is not bought with a chemist’s pills,
nor saved by the surgeon’s knife.
Health is not only the absence of ills,
but the fight for the fullness of life.
—P. Hein Prologue at the celebration of the 40th anniversary of the
World Health Organization (1988), Copenhagen
(Reprinted with permission by WHO)
Summary of Key Findings
• Multiple data systems capture information on specific health
conditions, but there appears to be overlap in their popula-
tions and content. Moreover, measures are inconsistent across
states, and no current mandate exists for comparability and
standardization.
• Current data collection systems for monitoring health fre-
quently fail to address important social and environmental
factors that influence children’s health outcomes. Likewise,
data collection systems that monitor educational performance
or children’s well-being frequently omit health data.
• Multiple recommendations for improving health measures for
children and adolescents have emerged in recent years. How-
ever, current federal surveys do not yet include a robust set of
measures of positive health, functioning, development, and
health potential within a life-course framework.
• Significant disparities in health status and health care quality
currently exist for a variety of racial, ethnic, and sociodemo-
graphic populations of children.
91
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92 CHILD AND ADOLESCENT HEALTH
• Social and economic conditions influence child health. Such
conditions include not only household income and educational
level, but also such factors as racial and ethnic identity, family
structure, immigrant status, urban/rural location, and health
literacy.
• Multiple environmental factors influence child health, many of
which are outside the purview of the health care system.
• Data on community factors are frequently available in non-
health surveys (e.g., environmental surveys, educational sur-
veys, or child victimization surveys).
• A life-course approach provides a basis for understanding the
relationships among early health conditions, health influences,
and later health status.
• Child health is strongly influenced by family and especially
maternal health (e.g., maternal depression).
The development of conceptually sound and reliable health measures
for children and adolescents is of critical importance for policy makers,
researchers, clinicians, and families, as well as community leaders and the
general public. Child and adolescent health measures can be used to assess
the effects of disease or injury on health; to identify vulnerable children in
clinical practices and vulnerable population subgroups in health plans or
geographic regions; to measure the effects of medical care, policy, and social
programs; and to set targets for improving health care (Szilagyi and Schor,
1998). Health measures also can identify general health trends over time to
highlight areas of progress as well as emerging areas of concern.
Until the middle of the 20th century, data on infant and child mortality
provided a reasonable assessment of child health (Guyer et al., 2000). The
neonatal segment of infant mortality (number of infant deaths at less than
28 days per 1,000 live births) provided a window on conditions related to
fetal development, complications of pregnancy and delivery, and the new-
born period; the postneonatal segment helped in understanding conditions
influencing child health through the preschool years (Black et al., 2003;
Heron et al., 2010).
The middle of the 20th century saw a decrease in the influence of infec-
tious diseases on child health. A different pattern of morbidity emerged,
termed the “new morbidity” (Haggerty et al., 1993; Palfrey, 2006). The
conditions dominating child health today often reflect behavioral and de-
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EXISTING MEASURES OF CHILD AND ADOLESCENT HEALTH
velopmental problems and chronic conditions, as well as associated social
conditions, which are poorly captured in vital statistics systems.
This same period saw the emergence of a wealth of measurement
tools in developmental psychology for assessing normal child development,
including Ages and Stages Questionnaires (ASQ), Bayley Infant Neurode-
velopmental Screens (BINS), Parents’ Evaluations of Developmental Status
(PEDS), and the Wechsler Preschool and Primary Scale of Intelligence
(WPPSI), among others. The application of these measures, however, has
been limited by both conceptual and practical issues. The conceptual issue
is that theories of developmental psychology are still evolving and do not
agree on the selection of appropriate domains for assessment. A comparison
of several well-established child health measures, for example, reveals 14
separate dimensions of child health (Landraf et al., 1996). Moreover, many
of the dimensions, such as learning disabilities, require sophisticated testing
by trained examiners. Practical issues include provider time, reimburse-
ment, and differential skill requirements for administering the instruments.
Early efforts focused specifically on measures of child health status that
would capture issues related to functional abilities were patterned after
more well-established adult measures (Eisen, 1980; Starfield et al., 1993).
For example, many adult health function measures inquire about the impact
of health issues on work and can be adapted to inquire about school for
older children. For preschool children and infants, however, such adapta-
tion is limited, as the activities of younger children are focused more on
attaining developmental skills necessary to attend school and participate
in other activities. Further, data on the validity and reliability of even es-
tablished measures are relatively sparse for pediatric outcomes. Validity is
established most commonly by the ability of the instrument to yield differ-
ent scores when administered to healthy children and those with established
diagnoses. Most instruments have not been used in a longitudinal fashion,
moreover, so that information on predictive validity is lacking, and little has
been done to validate responses against clinical observations. For example,
if a mother reports that her child has difficulty in play activities, does this
indicate a lack of stamina, a lack of coordination, or a lack of social skills?
Alternatively, does it reflect the mother’s lack of understanding of what
developmentally appropriate play looks like at that age?
Since the adoption of quality improvement initiatives under the Chil-
dren’s Health Insurance Program Reauthorization Act (CHIPRA), as well
as new quality efforts authorized under the Patient Protection and Afford-
able Care Act (ACA), the Congress and public and private health agencies
have begun searching for valid, reliable, and accessible health and health
care measures that can support the implementation and evaluation of these
efforts. Ideally, such indicators would provide the capacity at the national,
state, and local levels both to monitor the overall health of children and
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94 CHILD AND ADOLESCENT HEALTH
adolescents and to analyze the quality of health care services offered to both
the general population and vulnerable groups of children and adolescents.
An ideal set of health measures would inform comparisons of the status
of children and adolescents served by different health plans (both public
and private) and the types of health issues associated with different provid-
ers (pediatricians versus nurse practitioners and primary versus specialty
care) and health settings (such as hospitals or ambulatory care settings).
These measures would provide opportunities for states or regions of the
country to monitor the conditions of children and adolescents in areas
relevant to their own circumstances.
Ideally, robust health indicators would reveal significant trends and
changes in health status over time for the general population of children
and adolescents, as well as special groups that are at particular risk for
poor health outcomes and frequently are not identifiable in the major
population-based data sources. Such groups of vulnerable children include
those whose health may require special attention because of particular or
multiple conditions of disadvantage, such as those in certain income cat-
egories; those in certain racial or ethnic groups (such as American Indians
or Alaska Natives); those who live in homes in which English is not the
primary language spoken; those in residential or institutional care (such as
foster care); those who are uninsured or underinsured; and those who reside
in certain geographic areas, such as selected census tracts, rural environ-
ments, or regions with low numbers of health care providers (underserved
communities).
Finally, in an ideal world, child and adolescent health measures would
support analyses of the ways in which economic and social circumstances
influence health status. Such analyses might include the relationships among
children’s insurance status, their access to health providers, and their use
of and the effectiveness of health care, as well as the relationship between
child health status and family income, family stability and preservation,
and children’s school readiness and educational achievement and attain-
ment. The measures would also make it possible to examine relationships
between the health status of children and adolescents and their educational
performance, their social behaviors, and their future health status and pro-
ductivity as adults.
The remainder of this chapter examines the current status of child and
adolescent health measures; measures of health care quality are discussed
in Chapter 5. The first section takes a detailed look at existing measures,
including their strengths and limitations. Issues of the timeliness, qual-
ity, public transparency, and accessibility of currently available data on
child and adolescent health are then addressed. Next, the chapter turns to
the challenges of aggregating, synthesizing, and linking multiple sources
of these data. This is followed by a review of efforts to make the data
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EXISTING MEASURES OF CHILD AND ADOLESCENT HEALTH
more meaningful by linking population health indicators and public health
interventions.
EXISTING MEASURES OF CHILD AND ADOLESCENT HEALTH
In preparing a review of existing measures of child and adolescent
health, the committee identified seven priority areas for measurement, cur-
rent related measures, and the existing sources that provide data on these
measures. The priority areas are based on the committee’s collective judg-
ment and emerged through careful deliberations, a thorough review of the
literature, workshop presentations from a variety of engaged stakeholders
and experts, and an extensive review of existing data sets. The committee
considered the strengths and limitations of measures within each priority
area, as well as the extent to which national and state-based data sources
are available within each area. The seven priority areas are
• c
hildhood morbidity and mortality,
• chronic disease conditions,
• p
reventable common health conditions (especially mental and be-
havioral health and oral health),
• functional status,
• end-of-life conditions,
• health disparities, and
• social determinants of health.
In addition, the committee considered the life-course approach, discussed
in detail in Chapter 2, to be an overarching priority area that is integral to
all seven areas listed above. The committee therefore contends that mea-
surement should be informed by a life-course perspective and includes in
this section a review of the limited number of existing measures and data
collection efforts related to the life course.
Using these priority areas as a starting point for examining the exist-
ing array of measures and data collection efforts differs from previous
approaches. For example, the IOM-NRC report Children’s Health, the
Nation’s Wealth (2004) focuses on the specific measures of child health
included in selected national surveys (e.g., up-to-date immunizations or
nutrition adequacy). Instead, the approach used in this report enables those
who are interested in a particular aspect of child and adolescent health (e.g.,
preventable common health conditions) to readily identify the most relevant
currently available data sources. The sections that follow review child and
adolescent health measures and data sources according to the seven priority
areas, as well as the life-course approach; a more comprehensive review of
the relevant data sets is included in Appendix D.
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96 CHILD AND ADOLESCENT HEALTH
Childhood Morbidity and Mortality
A considerable amount of data related to child and adolescent morbid-
ity and mortality is routinely collected and analyzed. Surveillance of injuries
and fatalities among young people, for example, provides insight into one
aspect of how children are doing and underscores how their epidemiol-
ogy differs from that of adults. While unintentional injuries are a leading
cause of death among Americans of all ages, they are the leading cause of
death among children and adolescents aged 1−19 (Bernard et al., 2007)
(see Box 4-1). Young children (under age 4) are especially vulnerable to
life-threatening injuries (e.g., suffocation, drowning, and injuries related to
motor vehicle crashes) (CDC, 2006).
Three primary sources of data are used nationally to track morbidity
and mortality: the National Vital Statistics System (NVSS), the Medical
Expenditure Panel Survey (MEPS), and the Healthcare Cost and Utilization
Project (HCUP).
BOX 4-1
Leading Causes of Death Among Children and Adolescents
Accidents* are by far the leading cause of death among children and adoles-
cents. The top three causes of death by age group are listed below.
Ages 0−1:
• Developmental and genetic conditions present at birth
• Sudden infant death syndrome
• All conditions associated with prematurity and low birth weight
Ages 1–4:
• Accidents/injuries
• Developmental and genetic conditions present at birth
• Cancer
Ages 5−14:
• Accidents/injuries
• Cancer
• Homicide
Ages 15−24:
• Accidents/injuries
• Homicide
• Suicide
* The preferred term for “accidents” is “unintentional injuries.”
SOURCE: NIH, 2010b.
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EXISTING MEASURES OF CHILD AND ADOLESCENT HEALTH
The NVSS is maintained by the National Center for Health Statistics
(NCHS) within the Centers for Disease Control and Prevention (CDC).
Federal reports frequently use data from the NVSS to monitor trends in
child and adolescent mortality on a regional, national, and international
basis. NVSS data are collected through ongoing reports from vital statistics
officers in 50 states and the District of Columbia and reflect the cause of
death that is recorded on individual death certificates, providing the basis
for analyses of the leading causes of childhood morbidity and mortality.
The data are organized by age and gender, as well as selected racial and
ethnic groups. The NVSS relies on International Classification of Diseases
(ICD) codes to describe health conditions, disorders, diseases, and injuries.
For the most part, the ICD codes are organized by disease or injury catego-
ries, such as different types of cancers or congenital conditions, infectious
and parasitic diseases, endocrine conditions, mental disorders, disorders of
pregnancy and childbirth, poisonings, drowning, and so forth.
Hospitalization data for children and adolescents are collected through
such data sources as the MEPS, as well as such syntheses of public−private
data collection efforts as the HCUP. MEPS data are collected through a na-
tionally representative survey of U.S. civilian households. The data provide
information on the utilization and cost of health services, as well as on the
cost, scope, and breadth of private health insurance held by and available
to the U.S. population. HCUP data include a census of hospital discharge
billing records collected from 40 states. The data provide information on
reasons for hospitalization, length of hospital stays, procedures during
hospitalization, and treatments received for specific conditions while in the
hospital.
As a part of HCUP, the Agency for Healthcare Quality and Research
(AHRQ) developed a database specifically designed to allow in-depth stud-
ies of children’s hospitalizations—the Kids’ Inpatient Database (KID). The
KID is a stratified probability sample of pediatric discharges from 2,500–
4,000 community hospitals in the United States (defined as short-term,
nonfederal general and specialty hospitals, excluding hospital units of other
institutions). The purpose of KID data, which are drawn from an all-payer
(Medicaid, private insurance, and uninsured) inpatient care database for
children, is to identify, track, and analyze national trends in utilization, ac-
cess, charges, quality, and outcomes for inpatient hospital services.
Large claims-based data sets available from insurers and vendors also
are commonly used in research on health care utilization and on preva-
lence of disease. Examples include the Medstat Marketscan data set and
the data sets of Blue Cross Blue Shield, Wellpoint/HealthCore, and Kaiser
Permanente.
Data collected by the HCUP and the KID reveal the most common
reasons for admission to the hospital among children aged 17 and younger.
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98 CHILD AND ADOLESCENT HEALTH
The overwhelming majority—approximately 95 percent—of these admis-
sions are for the birth of infants (Owens et al., 2003). Newborns, or chil-
dren 30 days of age or less, account for approximately 4.8 million hospital
stays or 73 percent of all childhood admissions (Elixhauser, 2008). Affective
disorders, including depression and bipolar disorders, are the sixth most
common reason for hospital admissions among children, accounting for
82,500 discharges. Adolescent pregnancy is one of the leading causes of
hospitalization for females younger than 17. For adolescent boys, hospi-
talization occurs primarily as a result of unintentional injuries (Owens et
al., 2003).
Strengths
NVSS data provide a rigorous classification scheme for deaths associ-
ated with an array of health conditions, including pregnancy, abortions, and
various types of injuries that are common among children and adolescents.
The data can be pooled and analyses conducted over multiple years by
gender, race and ethnicity, and geographic location (state and county level)
to highlight trends that may not be apparent within a single time period.
The NVSS E-codes provide supplemental information about the cause of
injury (such as motor vehicle crash or child maltreatment). The rigor of
the data classification and the ongoing data collection support analyses
of trends among racial and ethnic minority groups that are often difficult
to detect in studies that rely on household surveys or other data sources.
For example, one CDC study of fatal injuries among children by race and
ethnicity (1999−2002) highlighted disproportionate rates of deaths due to
motor vehicle injuries among American Indian/Alaska Native children, as
well as higher rates of drowning deaths among black infants and American
Indians/Alaska Natives aged 1−19 (Bernard et al., 2007). Linked death and
birth records permit the examination of infant deaths by characteristics of
the parents and can be used to compare the mortality experience of dif-
ferent subpopulations (IOM, 1993). Linked records also provide insight
into access to prenatal and delivery care and some outcomes of pregnancy
(Marquis and Long, 2002; Schoendorf and Branum, 2006).
Data collected through the MEPS and HCUP may be more accurate
and reliable than survey data. For example, data obtained directly from
providers, such as specific diagnoses and treatment, are less likely to be
affected by recall bias than comparable data obtained from surveys based
on self-reports (Cohen, 2004). Hospital discharge data can often be linked
to other data sets, including data from the social services, criminal justice,
education, housing, and other sectors (Schoenman et al., 2005).
The KID’s large sample size enables analyses of both common and rare
conditions. The database comprises more than 100 clinical and nonclinical
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EXISTING MEASURES OF CHILD AND ADOLESCENT HEALTH
variables for each hospital stay, including primary and secondary diagnoses
and procedures, admission and discharge status, patient demographics (e.g.,
gender, age, race, median income for ZIP code), expected payment source,
total charges, length of stay, and hospital characteristics (e.g., ownership,
size, teaching status). The KID contains clinical and resource use data
included in a typical discharge abstract, but excludes data elements that
could identify individuals directly or indirectly. Analyses of HCUP and
KID data on rates of hospital admissions for specific conditions per popula-
tion or rates of specific events per procedure can provide the hospital and
reimbursement perspective on health care quality in terms of effectiveness
and patient safety (Berdahl et al., 2010). Children can be identified by age
in the Household Component of the MEPS, allowing most MEPS analyses
to be performed for children. In 2001, a Child Health and Preventive Care
section was added to the survey. It contains questions previously included
in the 2000 Parent Administered Questionnaire, selected questions related
to children that had been asked in previous years, and additional questions
related to child preventive care.
Limitations
Morbidity and mortality data provide information for only the most
severe health consequences, which involve a relatively small number of
children and adolescents. Those who are concerned with children’s health
status often want to know more than just the presence or absence of specific
health problems in the general child population at a given point in time.
They want to know the sequence of health conditions that may contribute
to morbidity and mortality events, as well as the relationship between
selected health conditions and certain social characteristics. They want to
know whether children who have access to certain family resources, certain
types of health care providers, or certain environmental and social condi-
tions fare better than those who do not. And increasingly, they want to
know whether children are on track to become healthy adults, especially
those young people who display early signs of poor health conditions that
are associated with adverse health outcomes and chronic disease in older
populations.
While NCHS can link vital statistics data with other data sources (in-
cluding census data, Supplemental Nutrition Program for Women, Infants,
and Children [WIC] program data, and hospital discharge data), NVSS data
alone are limited in the information they can provide. For example, NVSS
data do not capture fetal mortality experience by special populations (e.g.,
populations that are relatively small in number). Furthermore, challenges
to data collection, including frequent item nonresponse, variation in state
reporting requirements, and racial misclassification, may limit the overall
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100 CHILD AND ADOLESCENT HEALTH
quality and utility of NVSS data (Hoyert and Martin, 2002). The NVSS
also does not collect information about family or other household charac-
teristics (e.g., socioeconomic status), nor does it collect data on the types of
health plans associated with selected health conditions or injuries. Hospital
discharge data, of course, are limited in that they capture only those events
that occur in a hospital. Moreover, the HCUP does not include data from
all states, and less populous states are underrepresented. Further, the HCUP
is not designed specifically for pediatric issues and does not allow for longi-
tudinal studies of individuals. It is unclear whether the KID has the capacity
to capture a representative sample of uncommon and rare diagnoses.
Chronic Disease Conditions
The number of children and youth in the United States identified as
having chronic health conditions has increased considerably in the past four
decades. Data from the 2009 National Health Interview Survey (NHIS), for
example, indicate that 14 percent (more than 10 million) of children in the
United States aged 17 and under have ever been diagnosed with asthma and
that 10 percent (7.1 million) of children still have asthma. The 2009 survey
also found that 9 percent (5 million) of children aged 3−17 had attention-
deficit/hyperactivity disorder (ADHD) (Bloom et al., 2010). More than 12
million U.S. children meet the definition of children and youth with special
health care needs—those at “increased risk for chronic physical, develop-
mental, behavioral, or emotional conditions that require health and related
services of a type or amount beyond that required of children generally”
(McCormick et al., 2011; McPherson et al., 1998, p. 138). This group
accounts for roughly 15−20 percent of the childhood population and for
80 percent of annual health care expenditures for all children (Newacheck
et al., 1998b). Whether the increase in the number of children and adoles-
cents with chronic health conditions is the result of environmental changes,
better survival rates for once-fatal conditions, or increased access to care
through Medicaid expansions and the Children’s Health Insurance Program
(CHIP), it represents a significant trend (Van Cleave et al., 2010).
The NHIS is conducted annually and collects data on health indicators,
health care utilization and access (including current health insurance cover-
age), and health-related behaviors for the U.S. civilian noninstitutionalized
population. As a household survey, the NHIS collects data on all members
of the household, including children, adolescents, and adults. Data collected
through the NHIS are used to monitor trends in illness and disability and
to track progress toward the achievement of national health objectives
(Bloom et al., 2010).
The National Survey of Children’s Health (NSCH), first introduced in
2003 and subsequently fielded in 2007, is one of the most comprehensive
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EXISTING MEASURES OF CHILD AND ADOLESCENT HEALTH
surveys of child and adolescent health that offers national as well as state-
level data (NCHS, 2010b). Data collected through the NSCH support
analyses of physical, emotional, and behavioral child health indicators, as
well as contextual factors. The next NSCH survey, planned for 2011, will
expand the measurement of insurance adequacy beyond “having coverage”
to include items regarding the actual providers and services covered by the
child’s insurance policy, the costs of services not covered by the deductable,
and the overall adequacy of benefits (Bethell and Newacheck, 2010).
The NSCH is complemented by two other national surveys—the Na-
tional Survey of Children with Special Health Care Needs (NS-CSHCN)
and the National Survey of Early Child Health (NSECH). The NS-CSHCN
was first conducted in 2001 and again in 2005−2006 to monitor states’
provision of services to children with special health care needs through
federal programs, such as Title V and Supplemental Security Income (SSI)
(Blumberg et al., 2003; van Dyck et al., 2002). The NS-CSHCN measures
more than 100 indicators of children’s health and well-being for children
enrolled in these programs in six key areas: health status, health care,
school and activities, family and neighborhood, young children (aged 0–5),
and school-aged children (aged 6−17). The NS-CSHCN was developed to
measure the prevalence among children of both chronic conditions (e.g.,
asthma; attention-deficit disorder [ADD]/ADHD; depression, anxiety, or
other emotional problems; mental retardation; and seizure disorders) and
functional difficulties (e.g., respiratory problems, behavioral problems,
chronic pain, and self-care), as well as services received and satisfaction
with care (Blumberg et al., 2003; CAHMI, 2006; van Dyck et al., 2002).
The NSECH is a nationally representative household survey of children
aged 4−35 months that produces national and regional estimates. It was
administered once, in 2000. Planning for a possible NSECH-II has been un-
der way for several years, but no plan for its readministration has yet been
developed. Survey questions include child developmental status, provision
of recommended preventive services for which parents are valid reporters
(e.g., anticipatory guidance, some screenings, and family-centered care),
parenting behaviors and home safety, health insurance status, early child-
hood program enrollment, and utilization of services (Halfon et al., 2002).
The above three national surveys obtain national and state-based sam-
ples that are weighted to represent the general population of noninstitu-
tionalized children and adolescents. They all rely on a household survey
platform known as the State and Local Area Integrated Telephone Survey
(SLAITS), which is conducted by NCHS to support the design and sampling
frame for the ongoing National Immunization Survey. The SLAITS operates
by calling household telephone numbers at random to identify households
with one or more children under 18. In each household, one child is ran-
domly selected to be the subject of the interview.
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124 CHILD AND ADOLESCENT HEALTH
records, hospital discharge records) to follow their health outcomes and use
of health care services (CDC, 2010c).
Limitations
The retrospective reporting of childhood experiences is a potential
limitation of the ACE. Respondents may find it difficult to recall specific
events. In cases in which childhood abuse has been documented, for
example, adult respondents are likely to underestimate the actual occur-
rence of the abuse upon follow-up (Femina et al., 1990; Williams, 1995).
Another limitation relates to the sample included in the ACE. The major-
ity of ACE participants are white (74.8 percent), middle-class adults, the
overwhelming majority of whom have completed high school, attended
college, or completed college and/or beyond (92.8 percent) (CDC, 2010a).
These demographic characteristics limit the extent to which the findings of
the study can be generalized.
TIMELINESS, QUALITY, PUBLIC TRANSPARENCY, AND
ACCESSIBILITY OF DATA ON CHILD AND ADOLESCENT HEALTH
In its charge, the committee was asked to focus particular attention
on the timeliness, quality, public transparency, and accessibility of data on
child and adolescent health. Timeliness is a critical element in the assess-
ment and development of measures, as more rapidly released public-use
files provide a far more accurate picture of existing conditions than those
released long after data collection (NRC, 2010). Public transparency de-
pends on the timely availability and accessibility of quality data to reinforce
accountability on the part of responsible agencies (Beal et al., 2004; IOM,
2001a).
A number of online sources are designed to advance the timely and
effective use of public data on children, youth, and families in the United
States. Box 4-2 includes examples of accessible data sets across the seven
priority areas for child and adolescent health that can be used by families,
researchers, insurers, policy makers, and advocates to assess the health and
mortality experiences of children and adolescents. These include public data
sets, aggregations and syntheses of public data (see the next section), and
sources that integrate public and private data.
AGGREGATING, SYNTHESIZING, AND LINKING
MULTIPLE DATA SOURCES
Title V of the Social Security Act requires annual reporting of state
performance and health outcome measurement data, fiscal data and num-
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EXISTING MEASURES OF CHILD AND ADOLESCENT HEALTH
bers of clients served (individual, source, and service type), screening and
treatment data, state priority needs, state Title V initiatives, maternal and
child health (MCH) toll-free hotline data, and CSHCN service system data
(MCHB, 2010). Although these data are posted in a timely fashion to the
Title V Information System website, the data collected on child and adoles-
cent health exist largely in individual silos and are not readily translatable
to the seven priority areas discussed above.
In the absence of population or administrative data sources that can
link specific experiences or events to selected health behaviors in individual
children, many researchers rely on linking selected data sources at the
geographic level—for example, census tracts, counties, or states. Typically
they link one of the individual-level data sources discussed above with an-
other data source describing the social contexts of children and youth as
proxy measures for adverse or supportive environments in a child’s census
tract, county, or state. Such data include measures describing education,
employment, income, and community crime trends for national or regional
populations of children and youth.
Box 4-3 provides examples of efforts to aggregate, synthesize, and link
data from multiple sources. These include state, local, and national efforts
using both publicly and privately collected data. Key sources of data for
these efforts include the Current Population Survey (CPS), the Ameri-
can Community Survey (ACS), the National Survey of American Families
(NSAF), the National Center for Education Statistics (NCES) surveys, the
NVSS, and the BRFSS, among others.
Strengths
Aggregating, synthesizing, and linking data from multiple data sources
allows agencies and organizations to convey trends in child and adolescent
health to policy makers and the general public. These efforts often generate
easy-to-understand reports, fact books, and online tools.
Limitations
Unfortunately, linking multiple data sources cannot capture the dy-
namics of child and adolescent health and does not provide insight into
the interactions among various influences on child and adolescent health.
The data sets are frequently based on cross-sectional data, a disadvantage
for any effort to link multiple data sources. At present, moreover, financial
barriers hinder the ability to access deidentified Medicaid files for purposes
of cross-state quality measurement. As a result, current efforts to aggregate,
synthesize, and link data result in something more akin to a mosaic than a
snapshot of child and adolescent health, falling short of the goal of provid-
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126 CHILD AND ADOLESCENT HEALTH
BOX 4-2
Selected Online Sources of Data on
Child and Adolescent Health
• ehavioral Risk Factor Surveillance System (BRFSS) Interactive Data-
B
bases provide online access to the state-based system of health surveys that
collects information on health risk behaviors, preventive health practices, and
health care access primarily related to chronic disease and injury (http://www.
cdc.gov/brfss/).
• PONDER is a web-based query system created to access data collected
C
through Pregnancy Risk Assessment Monitoring System (PRAMS) surveys.
Users have the ability to design their own analysis by choosing from an in-
dexed list of available categorical variables. Descriptive statistics in the form
of proportions are included in the resulting report and corresponding graph.
CPONDER contains PRAMS data from 2000 through 2006 for state/year
combinations that achieve at least a 70 percent response rate. CPONDER
contains 2007 data for PRAMS state/year combinations that achieve at least
a 65 percent response rate. As additional years of data are weighted, they will
be added to the system (http://www.cdc.gov/prams/cponder.htm).
• ATA2010 is an interactive database system developed by staff of the Division
D
of Health Promotion Statistics at the National Center for Health Statistics, and
contains the most recent monitoring data for tracking Healthy People 2010.
Data are included for all the objectives and subgroups identified in the Healthy
People 2010: Objectives for Improving Health. DATA2010 contains primarily
national data. However, state-based data are provided as available (http://
wonder.cdc.gov/data2010/).
• he Data Resource Center for Child and Adolescent Health (DRC) pro-
T
vides online access to the survey data that allows users to compare state,
regional, and nationwide results for every state and HRSA region as well as
resources and personalized assistance for interpreting and reporting findings.
DRC includes data from the National Survey of Children’s Health (NCHS) and
the National Survey of Children with Special Health Care Needs (NS-CSHCN)
(http://www.childhealthdata.org/content/Default.aspx).
• CUPnet is a web-based interactive service for identifying, tracking, analyzing,
H
and comparing statistics on hospital care. HCUPnet was created with the inten-
tion to make health care data available to the public. HCUPnet allows anyone
to access aggregate statistics from these data sets to generate descriptive
statistics on many topics of interest, including, for example, the percentage
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EXISTING MEASURES OF CHILD AND ADOLESCENT HEALTH
of hospitalizations for children who are uninsured by state, trends in hospital
admissions for specific conditions, quality indicators and information on the
expenses of conditions treated in hospitals (http://hcupnet.ahrq.gov/).
• H
ealth Data Interactive presents tables with national health statistics for
infants, children, adolescents, adults, and older adults. Tables can be custom-
ized by age, gender, race/ethnicity, and geographic location to explore different
trends and patterns (includes the following data sources: Current Population
Survey [CPS], National Ambulatory Medical Care Survey [NAMCS], National
Health and Nutrition Examination Survey [NHANES], National Health Care
Survey [NHCS], National Health Interview Survey [NHIS], National Home and
Hospice Care Survey [NHHCS], National Hospital Ambulatory Medical Care
Survey (NHAMCS), National Hospital Discharge Survey [NHDS], National Vital
Statistics System [NVSS] [mortality and natality], and population estimates)
(http://www.cdc.gov/nchs/hdi.htm).
• M
EPSnet/HC is an interactive query tool that generates statistics of health
care use, expenditures, sources of payment, and insurance coverage for the
U.S. civilian noninstitutionalized population. However, none of the Child Health
and Preventive Care section variables are available on MEPSnet/HC (http://
www.meps.ahrq.gov/mepsweb/data_stats/MEPSnetHC.jsp).
• N
ational Center for Health Statistics. Data files for the National Survey of
CSHCN can be downloaded in SAS file format at no cost from the National
Center for Health Statistics website (http://www.cshcndata.org).
• N
ational Immunization Survey Public Use Data Files are available for sta-
tistical analysis or reporting purposes through the National Center for Health
Statistics (http://www.cdc.gov/nis/data_files.htm).
• W
ISQARS™ (Web-based Injury Statistics Query and Reporting System) is an
interactive database system that provides customized reports of injury-related
data (http://www.cdc.gov/injury/wisqars/index.html).
• Y
outh Online is an online database allows users to analyze national, state,
and local Youth Risk Behavior Surveillance System (YRBSS) data from 1991-
2009. Data from high school and middle school surveys are included. Users
can filter and sort on the basis of race/ethnicity, sex, grade, or site, create
customized tables and graphs, and perform statistical tests by site and health
topic (http://apps.nccd.cdc.gov/youthonline/App/Default.aspx?SID=HS).
NOTE: Descriptions are verbatim from source websites.
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128 CHILD AND ADOLESCENT HEALTH
BOX 4-3
Examples of Efforts to Aggregate, Synthesize,
and Link Multiple Data Sources
State and Local Governments/Health Departments
California Report Card (Children Now)
The Children’s Agenda (Montgomery County, Maryland)
Children’s Score Card (Los Angeles County)
Delaware Children’s Health Chartbook (Nemours)
MassCHIP (Massachusetts Department of Public Health)
North Carolina Child Health Report Card (Action for Children North Carolina,
NC IOM)
National
America’s Children: Key National Indicators of Well-Being (Federal
Interagency Forum on Child and Family Statistics)
America’s Health Starts with Healthy Children: How Do States Compare?
(Robert Wood Johnson Foundation)
The Child and Youth Well-Being Index (The Foundation for Child
Development)
Child Health USA (Health Resources and Services Administration/
Maternal and Child Health Bureau)
Child Trends DataBank (Child Trends)
The Child Well-Being Index (The Foundation for Child Development)
Indicators of Youth Health and Well-Being: Taking the Long View
(Stagner and Zweigl, 2007)
Key Indicators of Health and Safety: Infancy, Preschool, and Middle
Childhood (Hogan and Msall, 2008)
Kids Count (Annie E. Casey Foundation)
Appendix A: Datasets for Measuring Children’s Health and Influences on
Children’s Health, in Children’s Health, the Nation’s Wealth (IOM and NRC,
2004)
Appendix B: Gaps Analysis of Measures of Children’s Health and Influences
on Children’s Health in Select National Surveys, in Children’s Health, the
Nation’s Wealth (IOM and NRC, 2004)
Appendix C: Selected Indicators from National Children’s Data Syntheses,
in Children’s Health, the Nation’s Wealth (IOM and NRC, 2004)
ing a complete and accurate picture. Technology may make it possible to
achieve this goal in the near future. Chapter 2 provides a brief overview
of the implications of health information technology (HIT) for child and
adolescent health. A more in-depth analysis of future implications of HIT
for health and health care services is provided in Chapter 6.
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EXISTING MEASURES OF CHILD AND ADOLESCENT HEALTH
EFFORTS TO MAKE DATA MEANINGFUL BY
LINKING POPULATION HEALTH INDICATORS
AND PUBLIC HEALTH INTERVENTIONS
During the past three decades, efforts have been undertaken within
public health and child advocacy centers to link population health data
with national, state, and local initiatives designed to ameliorate those fac-
tors that contribute to adverse health outcomes for children and youth.
These efforts have emphasized identifying health conditions and behaviors
that would benefit from public health interventions, as well as changes in
social and economic settings, as opposed to medical treatments. Three such
efforts are the Healthy People program, administered by CDC; County
Health Rankings, developed within several states and published by The
Robert Wood Johnson Foundation; and the Kids Count initiative, funded
through the Annie E. Casey Foundation.
The Healthy People 2010 and forthcoming Healthy People 2020 objec-
tives provide a comprehensive agenda for nationwide health promotion and
prevention of disease, disability, and premature death; they serve as a road
map for improving the health of all Americans during the first decade of
the 21st century. CDC relies extensively on health measures drawn from the
NHIS and other data sources in the implementation of the Healthy People
initiatives (HHS, 2000a).
Healthy People 2010 includes 28 focus areas with 467 specific objec-
tives. One of the 28 focus areas is maternal, infant, and child health, and
107 of the objectives pertain to adolescents and young adults. The two
overarching goals of Healthy People, which are applicable across the life
course, are to increase quality of life and years of healthy life and eliminate
health disparities. A recent report on progress toward the Healthy People
2010 objectives describes mixed results for child and adolescent health. On
the one hand, between 1996 and 2008, exposure of children to tobacco
smoke at home and exposure to environmental tobacco smoke showed
significant progress (reductions of 69.2 percent), and immunization of
children aged 19–35 months increased by 10.9 percent. On the other hand,
overweight in children and adolescents increased by 58.7 percent (Sondik
et al., 2010).
Efforts to finalize the Healthy People 2020 objectives have been under
way since December 2010. Early indications point to a continued com-
mitment to eliminating health disparities and a greater focus on the social
determinants of health that have a disproportionate impact on specific
racial/ethnic populations (Sondik et al., 2010). Two new overarching goals
will be added: “promoting quality of life, healthy development, and healthy
behaviors across life stages; and creating social and physical environments
that promote good health” (Koh, 2010, p. 1656).
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130 CHILD AND ADOLESCENT HEALTH
The Robert Wood Johnson Foundation’s County Health Rankings ranks
the overall health of every county in all 50 states. The rankings are based
on a model of population health that includes health outcomes (based on
equal weighting of length and quality of life) and health factors (weighted
scores for health behaviors, clinical care, social and economic factors, and
the physical environment) (see Figure 4-1) (Booske and UWPHI, 2010). The
rankings are based on data from multiple sources, including
• t
he BRFSS;
• t
he NCHS;
• t
he National Center for Chronic Disease Prevention and Health
Promotion (Division of Diabetes Translation);
• t
he National Center for Hepatitis, HIV, STD, and TB Prevention;
• t
he Environmental Protection Agency (EPA) Collaboration;
• t
he Health Resources and Services Administration;
• t
he CPS;
• t
he Federal Bureau of Investigation;
• M
edicare claims; and
• t
he National Center for Education Statistics.
Bethell (2010) has identified four key questions to be considered in
aligning population health indicators with efforts to improve the quality of
health care services for children and youth:
• S
hould the emphasis be on leading causes of death and most com-
mon reasons for using medical care or on the prevalence of ongo-
ing health conditions (also described as the low-volume/high-cost
versus high-volume/low-cost trade-off)?
• S
hould the population health measures be condition-specific (e.g.,
reflect the ICD categories), or should the broad-based, conse-
quences-focused definition used in the survey of children with
special health care needs (NS-CSHCN) be adopted?
• W
hat effort should be directed toward indicators of risk versus
established conditions (e.g., overweight and obesity, or risks for
developmental delay or substance use)?
• S
hould population health indicators aim to address categories
of conditions (e.g., mental and behavioral health, oral health,
injuries)?
SUMMARY
This chapter has reviewed the relative strengths and limitations of
measures of the health of children and adolescents based on population
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EXISTING MEASURES OF CHILD AND ADOLESCENT HEALTH
FIGURE 4-1 County Health Rankings model.
SOURCE: Booske and UWPHI, 2010.
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132 CHILD AND ADOLESCENT HEALTH
health and administrative data sources. This review has highlighted the
diversity and complexity of existing measures while calling attention to
areas in which existing data systems are insufficient to address key topics
of interest. For example:
• A
lack of standardization in the measurement of disparities in
health limits the ability to identify, monitor, and address persistent
health disparities among children and adolescents.
• C
urrent child health measures lack the capacity to capture impor-
tant functional data and developmental stages; valid measures in
these areas that have been tested across diverse populations do not
yet exist.
• M
ost child and adolescent health data sets lack the capacity to
support efforts to track the life-course implications of child health
events, especially those that occur in early stages of development.
The committee has identified seven priority areas for future measures
that could provide relevant information on the health of children and ado-
lescents for policy makers, service providers, and the general public and also
inform quality improvement efforts within public and private health plans.
The committee also has emphasized the importance of using a life-course
approach, which may require changes to current public- and private-sector
criteria and methods for the selection of existing and the development of
new health quality measures. Indicators generated from data acquired with
a life-course perspective in the seven priority areas should make it possible
to examine specific conditions and issues of particular importance to vul-
nerable and underserved children and adolescents, especially those served
by Medicaid and CHIP programs. Such conditions and issues might include
• g
estational and perinatal issues that impact child health, such as
prenatal care;
• u
nique neonatal issues, such as prematurity and low birth weight;
• h
ealth issues in the transition of those with chronic illnesses from
adolescence to young adulthood (particularly in light of health re-
form changes that include coverage of children under their parents’
health insurance until age 26);
• c
hronic childhood conditions that impact adult health, such as
Down syndrome, cystic fibrosis, childhood cancer, and congenital
heart defects; and
• o
pportunities presented by the NCS, which will follow subjects
from preconception to age 21.
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EXISTING MEASURES OF CHILD AND ADOLESCENT HEALTH
Ideally, child and adolescent health quality measures should support
analyses that can demonstrate how changes in funding levels for public
insurance programs (such as Medicaid or CHIP) or changes in eligibility
requirements, enrollment levels, or service procedures would affect child
health outcomes, school achievement, and health care costs. Such measures
should also be useful in assessing whether and how the organization and de-
livery of health care achieve public goals of effectiveness, efficiency, safety,
timeliness, equity, and patient satisfaction. Realizing these goals will require
capacity for state-level analyses because Medicaid and CHIP are executed
and managed at the state level, and there has historically been significant
state-level variation in eligibility, coverage, and access to providers.
Additional themes that deserve attention include the following:
• t
he distinction between low-incidence/high-cost conditions and
those that reflect the most common child and adolescent health
disorders;
• s
ignificant trends in child health, health care access and quality, and
outcomes (e.g., immunization coverage rates);
• i
ndicators of resilience and protective factors/effects; and
• c
omorbidities (because of their potential multiplier effects).
Finally, the seven priority areas, as well as a life-course perspective,
should be used to direct analysis toward possible emerging threats to child
health as a test of how comprehensive and useful this taxonomy can be in
generating priority indicators for child and adolescent health.
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