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5
Measures of Quality of Child
and Adolescent Health Care
Summary of Key Findings
• T
he prevalence and the aggregate cost of treatment of complex
health conditions are lower for children and adolescents com-
pared with the high cost of hospital care for adults and older
adults.
• M
easurement of health care quality for children and adoles-
cents serves the same purposes as that for adults—account-
ability, quality improvement, and population health. However,
the development of quality measures for child and adolescent
populations has been slow to emerge from the private sector
because enhanced quality is unlikely to produce short-term
reductions in health care costs (in contrast to the results as-
sociated with quality improvement efforts for adults and older
adults).
• T
he Centers for Medicare and Medicaid Services uses only
seven standardized measures to assess care for children and
adolescents enrolled in Medicaid programs, and these measures
apply only to those who are enrolled in Medicaid managed
care plans. These measures involve some of the most com-
mon chronic medical conditions, preventive services, and acute
care. However, they generally measure specific elements of care
rather than serving as comprehensive measures, and they miss
135
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136 CHILD AND ADOLESCENT HEALTH
important areas of health (mental health, oral health, and in-
patient care) and care processes (particularly care coordination
across multiple settings).
• T
he effectiveness of preventive services is particularly difficult
to measure because the outcomes may not be known for many
years, and the impact may vary according to the risk profile of
the patient population. Current preventive measures are largely
process focused, and do not consider the outcomes of screen-
ing efforts or whether recommended treatment services were
actually provided in an effective, evidence-based, equitable,
family-centered, or timely manner. This is the case largely be-
cause the measures are derived from the claims data generated
by a single visit.
• T
he number of children and adolescents who live in poverty or
in low-income families (generally considered to be below 200
percent of the federal poverty level) is higher relative to adults,
a fact that has a significant influence on their health outcomes.
For example, high-quality asthma care may produce marginal
outcomes for children and adolescents whose housing condi-
tions create persistent risk factors for this condition.
• T
he measurement of quality of care for children with special
health care needs requires attention to their functional status
and care transitions as well as their health conditions. Func-
tional status measures for children and adolescents are not
standardized, however, and frequently rely on parental reports
rather than comparison of a child’s behavior or skills with
those of others with similar health conditions.
• V
ariations in the definitions of race, ethnicity, and primary
language in state databases are major obstacles to the develop-
ment and use of heath care quality measures for children and
adolescents. A few states have made efforts to gather demo-
graphic data by linking their Medicaid or CHIP eligibility files
to their claims data sets, but such strategies are not in common
use.
• M
any states and some local districts have demonstrated inter-
est in expanding the number and types of measures used to
assess quality of care, as well as in applying the measures to
children and adolescents enrolled in public and private health
plans. Several states and local districts already collect data that
can identify early antecedents of unhealthy behaviors that may
have lifelong and communitywide consequences.
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137
MEASURES OF QUALITY OF CHILD AND ADOLESCENT HEALTH CARE
In September 2010, the Secretary of Health and Human Services (HHS)
released the first annual report on the quality of care for children in Med-
icaid and the Children’s Health Insurance Program (CHIP), as required by
the Children’s Health Insurance Program Reauthorization Act (CHIPRA)
of 2009 (HHS, 2010c). The report notes that nearly 40 million infants to
young adults are now enrolled in these public health insurance plans, rep-
resenting about half of this population in the United States.1 In addition,
Medicaid pays for nearly half of the annual births nationwide.
Although the Secretary’s report provides an important benchmark for
assessing the current status of quality measurement of child and adolescent
health care services, it also highlights key barriers and challenges that have
yet to be resolved. In summary, the Secretary’s report offers the following
key findings:
Measurement and Reporting
• A lack of uniformity and substantial variation in data reliability
exist in state-based quality metrics, demonstrating a need for stan-
dardized data collection formats.
• Medicaid managed care plans have developed an infrastructure
and processes to support external quality reviews, but these efforts
do not include information on children in fee-for-service payment
arrangements, and they have not yielded statewide information.
• Many state officials welcome the opportunity to create more mean-
ingful and useful measures, and they recognize that current perfor-
mance measures are inadequate.
Quality of and Access to Care
• A report on the seven quality-of-care effectiveness measures in
Medicaid managed care plans from 34 states showed mixed per-
formance: three of the seven measures had relatively high 2008
performance rates, while four of the seven had relatively low per-
formance rates for the same period (see Box 5-1 for a list of the
seven measures).
• Children enrolled in Medicaid/CHIP have much better access to
primary care services than uninsured children and access com-
1 Estimates of the rates of coverage of children in public health insurance plans may vary
according to the source and method of data collection. The 2010 HHS Secretary’s report
draws on administrative data from the Centers for Medicare and Medicaid Services (CMS).
Other data sources, such as those collected by the Census Bureau and those based on parental
reports, estimate that about 30–35 percent of children and adolescents are covered by public
health insurance plans (HHS, 2010a).
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138 CHILD AND ADOLESCENT HEALTH
BOX 5-1
Quality-of-Care Effectiveness Measures
(Reported by the National Committee for Quality Assurance
for Children in Medicaid Managed Care Plans)
• U
se of appropriate medication for asthma
• A
ppropriate treatment for upper respiratory infection
• C
hildhood immunizations
• L
ead screening
• C
hlamydia screening in 16- to 20-year-olds
• F
ollow-up care for children prescribed medication for attention-deficit/hyperac-
tivity disorder
• ppropriate testing for children with pharyngitis
A
SOURCE: NCQA, 2009.
parable to that of privately insured children. However, access to
specialty care services (e.g., dental, mental health) needs substantial
improvement.
• Once enrolled in Medicaid or CHIP, racial/ethnic minority children
and children with special health care needs experience improved
access to care, but disparities in access to and quality of care persist
despite these gains.
This chapter reviews how efforts to improve the measurement of health
care quality for children and adolescents have evolved in public and pri-
vate health care settings. The analysis considers how these efforts compare
against a vision of an optimal system of health care quality measurement
for younger populations. The review highlights how the findings from the
2010 HHS Secretary’s report might be considered in light of persistent
areas of need and emerging opportunities for improving the measurement
of health care quality, particularly for children and adolescents enrolled in
Medicaid and CHIP health plans. The focus is on five key questions:
• What is the purpose of health care quality measurement for chil-
dren and adolescents?
• What are the critical features of an optimal health care quality
measurement system for children and adolescents?
• What steps have been taken to develop such a high-quality mea-
surement system?
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MEASURES OF QUALITY OF CHILD AND ADOLESCENT HEALTH CARE
• What are examples of current efforts to improve the system?
• Are these efforts sufficient to achieve the vision of an optimal
system?
The chapter also highlights promising state and local initiatives.
PURPOSE OF QUALITY MEASUREMENT
Measuring the quality of health care services overall fulfills three ma-
jor purposes: accountability, quality improvement, and population health
(IOM, 2006b):
• Accountability—Quality measures provide a basis for assessing and
comparing the performance of selected components of the health
care system, including individual professionals, provider groups,
hospitals, health plans, and states. Quality measures can identify
differences in health care practices or processes, service delivery
settings, health plans, and state programs and policies, as well
as the outcomes associated with these differences. They provide
a basis for determining whether the care patients receive from
specific providers is consistent with evidence and professional stan-
dards. Such information can assist multiple stakeholders in making
choices about providers, about plans, and about state policies and
programs. These stakeholders include, among others, patients de-
ciding on a clinician, hospital, or other provider from which to seek
services and a health plan from which to obtain coverage; purchas-
ers and health plans selecting providers to include in their health
insurance networks; and quality oversight organizations making
accreditation and certification decisions. Quality measures facilitate
assessment and monitoring of the overall functioning of the health
insurance and care delivery system over time, demonstrating who
is being reached and who is not. Thus they provide the ability to
hold health care state systems and health plans accountable for
their performance.
• Quality improvement—Quality measures can be useful for provid-
ers and others who are seeking to improve the quality of care. Such
measures can identify gaps in performance that merit attention and
can also be used to track progress as individuals and organizations
undertake changes to improve care. Key users of such data for
improvement include clinicians, quality improvement staff, and
managers and members of health care organizations.
• Population health—Quality measures must be able to identify gaps
in population health, as well as in the clinical care of individuals,
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140 CHILD AND ADOLESCENT HEALTH
and to track progress in addressing these gaps. Stakeholders in-
clude those with specific responsibility for broad population health,
as well as those involved in the delivery of health and public health
services, such as communitywide programs and efforts to address
racial and ethnic disparities and promote healthy behaviors.
The creation, selection, and certification of quality measures are driven
by multiple public- and private-sector efforts aimed at accomplishing one
or more of the above three objectives. Providers have tended to focus on
opportunities for clinical improvement, while employers and other private
payers have tended to place more emphasis on improving the effectiveness
and efficiency of clinical services for prevalent, high-cost conditions that
often require interactions with multiple health care providers and health
care settings. As a result, many quality measures include an emphasis on
procedures or settings associated with effective and timely clinical care,
such as the use of specific treatments or the performance of specific tests
and monitoring procedures. Public payers have placed more emphasis on
broader population-level measurement, such as rates of hospitalization for
preventable conditions or rates of rehospitalization.
As noted in earlier chapters, younger populations tend to be relatively
healthy, and the frequency of high-cost conditions is much lower among
children compared with adults. Given these characteristics and the increas-
ing numbers of children insured through public payers, the public sector
has demonstrated far greater interest to date, relative to the private sector,
in the development and use of health care quality measures for children
and adolescents.
Solid reasons exist for the lag in development and use of measures of
health care quality for children and adolescents:
• The relatively low cost of child health care and the rarity of many
child health conditions have impeded clinical research into many
of these conditions, limiting the quality of evidence underlying the
effectiveness of treatment for younger populations. Without strong
evidence linking care processes and outcomes, performance mea-
surement (at least in the domain of effectiveness) is difficult.
• Prevention is particularly important for children, but proving the
effectiveness of many clinical preventive services in children is dif-
ficult. There is a long lag time between many of these preventive
interventions and potential outcomes, and the determinants of
these outcomes are complex—health care may be but one of many
inputs. Consensus guidelines for preventive services in childhood
are now available and widely used (e.g., Bright Futures or the Pro-
moting Healthy Development Survey [PHDS]) but the effectiveness
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MEASURES OF QUALITY OF CHILD AND ADOLESCENT HEALTH CARE
of these services in improving health outcomes for children has not
yet been demonstrated (Bethell et al., 2001).
• The processes of care associated with many health services for
children and adolescents involve detailed clinical information that
may be included in medical records but is not easily accessible from
claims-based or other administrative databases. The time and costs
associated with abstracting clinical data (such as the results of rou-
tine clinical exams and screening tools associated with well-child
care) impede the use of these data in large data collection efforts.
• Because many important services and conditions other than health
care, such as educational services and community nutrition pro-
grams, contribute to child health outcomes, a framework that
explicitly acknowledges this shared accountability is especially im-
portant for child health. Measures that reflect this shared account-
ability, such as school readiness, can be constructed and used for
quality improvement programs, but they are more difficult to apply
within the narrow context of health care accountability. A more
popular approach has been the use of a process measure, such as
access to a medical home (or health home) for children and ado-
lescents, especially those who have a complex or chronic health
condition.
CRITICAL FEATURES OF AN OPTIMAL HEALTH CARE QUALITY
MEASUREMENT SYSTEM FOR CHILDREN AND ADOLESCENTS
In considering the features of an optimal health care quality measure-
ment system for children and adolescents, the committee took into account
the charge for this study from the Congress; the principles underlying
performance measurement as articulated in earlier Institute of Medicine
(IOM) studies on performance measures (IOM, 2006b); the family/patient
focus expressed in the IOM report Crossing the Quality Chasm: A New
Health System for the 21st Century (IOM, 2001a); and the committee’s
own deliberations, which were strongly influenced by another earlier IOM
study, Children’s Health, the Nation’s Wealth (IOM and NRC, 2004). The
optimal features thus identified are as follows:
• Measures should address those topics that (1) are associated with
the greatest burden of mortality and morbidity during childhood,
(2) have the greatest potential impact over the life span, (3) address
the drivers of high child health care costs, (4) are most sensitive to
the quality and safety of services, and (5) are of greatest concern
to patients/families.
• Measures should be based on the best available evidence.
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142 CHILD AND ADOLESCENT HEALTH
• Measures should recognize the unique characteristics of the child
and adolescent population, often termed “the four D’s” (differ-
ential epidemiology, developmental focus, dependent status, and
different demography) (Forrest et al., 1997).
• Measures should apply to the whole population of children and
adolescents, not just those in specific health plans or states.
• Measures should be capable of aggregation at multiple levels (pro-
vider, organization, community, state, nation).
• Measures should take account of the social environment in which
children live to allow assessment of how health care services inter-
act with conditions of adversity to influence health outcomes.
• Measures should be broader than the presence or absence of
disease.
• Measures should minimize the burden and cost of collection.
• Measures should be able to generate data to drive action and qual-
ity improvement at the program (provider) and policy levels.
• Measures should be readily available to all (transparent).
• Measures should be available in a timely manner.
• Measures should reflect patient, family, and community perspec-
tives on quality.
The contrast between these features and the quality measures that are
cited in the 2010 HHS Secretary’s report is remarkable. Only seven qual-
ity measures for children and adolescents are reviewed in that report, and
those measures are used in only 30 states and only for those enrolled in
Medicaid managed care programs. As a result, the nation is far from having
a performance measurement system that can foster the incorporation of the
above features into the development and use of quality measures for child
and adolescent health care.
INITIAL EFFORTS TO DEVELOP A MEASUREMENT SYSTEM
FOR QUALITY OF CARE FOR CHILDREN AND ADOLESCENTS
Initial efforts to improve the measurement of health care quality for
the general population include reports by the IOM and initiatives by such
groups as the National Committee for Quality Assurance (NCQA) and the
National Quality Forum (NQF) (see Appendix C). More recently, the Na-
tional Initiative for Children’s Healthcare Quality (NICHQ) and the Child
and Adolescent Health Measurement Initiative (CAHMI) have sought to
emphasize the need for consumer-driven measures of health care quality for
children and adolescents, as well as to develop approaches for encouraging
the use of available measures. These various efforts were encouraged and
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MEASURES OF QUALITY OF CHILD AND ADOLESCENT HEALTH CARE
supported through congressional guidance in the CHIP (1997) and CHIPRA
(2009) legislation, which stimulated national leadership and research sup-
port by the Agency for Healthcare Research and Quality (AHRQ), as well
as demonstration and state-based coordination efforts within the Centers
for Medicaid and Medicare Services (CMS).
Initial Congressional Guidance and Federal Leadership
In 1997, Congress created the State Children’s Health Insurance Pro-
gram (SCHIP), one success resulting from the earlier, intense, but ultimately
unsuccessful battle over health care reform (Iglehart, 2007). The legislation
proved to be a major advance for children and families in terms of expand-
ing health plan coverage and access to services and reducing disparities
in these two areas. In addition, the 1997 SCHIP legislation required that
state annual reports include for the first time information on quality—a
requirement that did not exist in Medicaid. HHS developed a standardized
template for these state reports emphasizing the use of Healthcare Effective-
ness Data and Information Set (HEDIS©) measures that had been developed
as part of quality improvement efforts among private health plans—efforts
focused largely on adult health care quality.
During the past two decades, CMS worked with multiple partners to
develop quality measures that could be used to assess and improve health
care services for children and adolescents enrolled in Medicaid and CHIP
health plans. These efforts focused initially on use of the HEDIS measures
and collaboration with NCQA. In 1996, for example, prior to passage of
the CHIP legislation, Medicaid HEDIS was developed, incorporating stan-
dards specific to Medicaid populations (MacTaggart, 2010). Although the
use of such measures was voluntary, more than 30 state Medicaid agencies
were using at least portions of Medicaid HEDIS within a year. Further col-
laboration with NCQA, the American Public Human Services Association,
and the Commonwealth Fund led to a 2002 report that covered 13 HEDIS
measures, 5 of which were child-specific, from 176 managed care organiza-
tions in 33 states plus the District of Columbia and the Commonwealth of
Puerto Rico (MacTaggart, 2010). One year later, HEDIS 2003 contained
23 measures designed for or applicable to children and adolescents, in-
cluding child and adolescent immunization status, chlamydia screening
for women, use of appropriate medications and follow-up care for people
with asthma, and experience of care (based on responses to the Consumer
Assessment of Healthcare Providers and Systems [CAHPS] 3.0H Child
Survey, which included a screener for children with chronic conditions)
(MacTaggart, 2010).
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144 CHILD AND ADOLESCENT HEALTH
Early Attributes of Quality Measures for Children and Adolescents
In 2004, the Commonwealth Fund examined existing child health care
quality measures within 19 different data sources or measurement sets (Beal
et al., 2004; Leatherman and McCarthy, 2004). This analysis identified 396
quality measures for children within the 19 data sources, 10 of which relied
on administrative or medical record data and 9 of which used survey data.
In categorizing these measures according to the six aspects of qual-
ity care identified in Crossing the Quality Chasm (IOM, 2001a)—safety,
timeliness, effectiveness, equity, efficiency, and patient-centeredness—the
authors found that more than half (59 percent) of the measures involve
indicators of effectiveness, while about one-sixth (14 percent) are relevant
to the safety domain (Beal et al., 2004). The safety measures involve pri-
marily serious errors in health care delivery, especially medical and surgi-
cal errors during hospitalization. The authors also examined how existing
health care quality measures are distributed across the different purposes of
health care—acute care (getting better), preventive care (staying healthy),
and chronic care management (living with illness). They found that a large
proportion of the measures (40 percent) could be categorized under getting
better, about 24 percent under staying healthy, and 17 percent under liv-
ing with illness. There were no measures related to end-of-life care. Nearly
one-fourth of all measures were not classifiable by the six aspects of quality
care (Beal et al., 2004).
In addition, some efforts have focused on developing quality measures
that would apply to children of all ages, as well as measures that would
have specific application to selected age groups—infants, toddlers, children,
and adolescents. Analyses of these efforts have shown that the majority of
measures they produced can be applied to children across all age groups;
however, there are no unique measures for school-aged children (aged
5−18) (Beal et al., 2004).
Despite the advances achieved through the above efforts, studies have
revealed many areas in which quality measures fall short (Landon et al.,
2007; Leatherman and McCarthy, 1999; Mangione-Smith et al., 2007;
Thompson et al., 2003). In particular, measures fail to capture aspects of
care that are relevant for low-income, Medicaid-insured children. More-
over, quality measures are lacking for many important areas of health care,
even though major studies have demonstrated significant shortcomings in
these areas both for the general population (such as inpatient care or men-
tal health services) and with respect to disparities in access to and use of
services (such as oral health care).
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MEASURES OF QUALITY OF CHILD AND ADOLESCENT HEALTH CARE
CURRENT EFFORTS TO IMPROVE THE
MEASUREMENT OF QUALITY OF HEALTH CARE
FOR CHILDREN AND ADOLESCENTS
Recognizing the shortcomings detailed above, recent health care leg-
islation places new emphasis on the importance of measuring health care
quality for younger populations. This legislation includes CHIPRA (espe-
cially Title IV), the Patient Protection and Affordable Care Act (ACA), the
American Recovery and Reinvestment Act (ARRA), and the Health Infor-
mation Technology for Economic and Clinical Health (HITECH) initiative
included in the ARRA.
2009 Congressional Action and Title IV of CHIPRA
In reauthorizing the CHIP legislation in 2009, Congress renewed its
initial efforts to foster the use of health care quality measures for Medicaid
and CHIP populations, adding new dimensions that had emerged as major
concerns. The new legislation required that quality measures specifically
address three broad types of care (prevention, acute care, and chronic care)
and specific elements of clinical quality (effectiveness, safety, patient and
family experience, and equity [disparities]). Congress also directed that
child health care quality measures specifically address mental as well as
physical health care, care across the full spectrum of child development,
care integration and access as reflected by accessibility of care in inpatient
and outpatient settings, and the duration and stability of health insurance
coverage.
Title IV of CHIPRA (P.L. 111-3) significantly expanded various child
health care quality improvement initiatives and authorized several new ef-
forts, including
• development of an initial core set of health care quality measures
for children enrolled in Medicaid or CHIP, to be supplemented by
research grants to address incomplete or missing measures (known
as the U18 awards);
• a new program of 10 quality demonstration grants to states as the
basis for a future national quality system for children’s health care;
• creation of the Medicaid and CHIP Payment and Access Commis-
sion (MACPAC) to review Medicaid and CHIP access and payment
policies and report recommendations to Congress;
• creation of a Federal Quality Workgroup of the CHIPRA Steer-
ing Committee to ensure that the expertise of key HHS entities is
brought to bear on improving quality measurement and the quality
of health care for all children;
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164 CHILD AND ADOLESCENT HEALTH
adolescents typically lose public coverage, they often fall out of the system
and experience dramatically decreased care (Adams et al., 2007; White,
2002). However, population surveys are cross-sectional and do not follow
the same adolescents through the transition. Further, there is a shift in
the methodology used in cross-sectional surveys at this juncture: parents
answer for children through age 17, whereas individuals answer for them-
selves thereafter. Questions are also different on child and adult surveys,
hampering comparisons across age ranges.
Measuring Across Settings, Across Multiple
Domains of Care, and Across Time
Measurement of quality for a specific hospital stay or given outpatient
visit is more straightforward than measurement of the overall quality of
care across an episode of illness. New measures of health care quality for
children and adolescents will need to track individuals over time and across
multiple encounters with different care settings within the health care sys-
tem. For adults, these episode-of-care measures tend to focus on curative
outcomes (such as reduced hospital stays or lower rates of readmission).
But this approach may need to be modified when applied to children with
chronic conditions, for whom the issues are rehabilitative and functional
rather than curative. Emerging work within NCQA and the American
Academy of Pediatrics is focused on such efforts, for example, through
the use of medical or health home measures or the new NCQA health care
supervision measures (AAP, 2002; NCQA, 2010).
Measuring child and adolescent health care requires having the ability
to look across visits and services to determine whether all required com-
ponents of care were delivered for a particular age (Scholle et al., 2009). It
also requires the ability to determine whether the appropriate combination
of drugs was prescribed for a given mental illness, for example, or whether
appropriate care was provided after a hospitalization (not merely whether
there was a visit) or whether the child was rehospitalized for the same
condition.
Current measurement systems and metrics are not capturing these vital
longitudinal dimensions of care. Much of the information on health care
quality comes from administrative data that measure services delivered (for
example, a lead screening test), but not the outcome of the test or follow-
up treatment. While organizations understand the potential for medical
record abstraction to create such quality measures, they face numerous
barriers (financial, privacy, and infrastructure) to implementation. In addi-
tion, rehabilitative and other services are delivered in non−health care set-
tings, such as special education services and social work support services.
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MEASURES OF QUALITY OF CHILD AND ADOLESCENT HEALTH CARE
Adequate assessment of the quality of care would require capturing these
services as well.
Measuring Quality in Preventive Care Services
The conceptualization of “health” for children embodied in Children’s
Health, the Nation’s Wealth and elsewhere calls for departure from think-
ing of health as physical health and absence of illness and extends the con-
cept of prevention into health promotion and well-being (IOM and NRC,
2004). Measurement of this broader concept of “health” is now reflected
in cross-sectional population surveys such as the National Survey of Chil-
dren’s Health, but it is generally not present in the design, organization, and
financing of the health care system. Significant efforts are now under way,
however, to introduce broader concepts of prevention and health promo-
tion into the routine services offered as part of well-child visits, especially
through screening and practice changes to promote healthy development for
children with or at risk for developmental delays. One such effort is the As-
suring Better Child Health and Development (ABCD) initiative, sponsored
by The Commonwealth Fund, in which state Medicaid agencies partner
with others to increase the use of such screening and practice changes for
low-income children (Kaye et al., 2006).
The Child and Adolescent Health Measurement Initiative (CAHMI)
conducts two surveys aimed specifically at prevention measures: the Young
Adult Health Care Survey (YAHCS) and the Promoting Healthy Develop-
ment Survey (PHDS). The YAHCS seeks to assess whether young adults
(aged 14–18) are receiving preventive services through a 54-question survey,
which can be administered via telephone or mail (an online version is in
development). The results are scored according to nine measures of care
quality, emphasizing preventive screening and counseling on risky behav-
iors, sexual activity, and emotional health, as well as private and confiden-
tial care (CAHMI, 2010). The survey has been adopted by several states
(California, Florida, New York, and Washington) for use in their quality
improvement efforts (CAHMI, 2010), and its results can be used to create
community-specific assessments of adolescent health.
The PHDS is a family-focused survey intended to capture both pro-
vider- and parent-based data that can be used during a well-child visit and
can then become part of the medical record (Bethell et al., 2001). Parents
may fill out the PHDS before the visit (either by mail, in the waiting room,
or online), answering questions regarding concerns about the child, antici-
patory guidance, and parental education needs and providing a brief assess-
ment of the child’s development and family risk factors. If physicians have
access to EHRs, they can use a link in the EHR to review the survey results
for family risk screening, family risk assessment, and priority educational
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166 CHILD AND ADOLESCENT HEALTH
needs prior to the visit. During the visit, physicians and other clinicians use
the results to prioritize and individualize the content of the visit.
The PHDS-PLUS is an adaptation of the PHDS that provides a tele-
phone/interviewer-administered survey for parents of young children (aged
3–48 months). One study indicates that data have been collected using the
PHDS-PLUS from almost 14,000 children in Medicaid programs in seven
states. These data provide a basis for comparing state-based performance
in 11 designated topic areas, such as assessment of concerns about child
development, family psychosocial assessment, and help with care coordina-
tion (Bethell et al., 2007).
Both the ABCD initiative and the PHDS-PLUS effort have developed
quality measures that states can use as baseline information systems to
improve their efforts to implement preventive and developmental services
for children served through Medicaid managed care plans. These measures
allow states to track the use of and experience with such preventive care
services (Bethell et al., 2007; Scholle et al., 2009).
In the past, quality measures for preventive care have been largely
process focused, examining whether a specific service had been delivered
without examining the content of the visit or appropriate follow-up care.
For example, there are HEDIS measures for whether a well-child visit has
taken place or whether a chlamydia screening has occurred, but such mea-
sures do not consider the outcome of the screening procedure, or whether
recommended treatment services were provided in a timely and effective
manner (Scholle et al., 2009). This is largely because measures are derived
from the claims data generated from a single visit. In the absence of EHRs
and detailed clinical data on processes of care, efforts to abstract this infor-
mation encounter major issues related to feasibility and cost.
Recently, important work has been done to expand the scope and flex-
ibility of measurement approaches, particularly with regard to well-child
visits (Scholle et al., 2009). New measures have been proposed that go be-
yond whether a visit has taken place to encompass the content and outcome
of the visit. These new proposed measures assess whether all services that
are required by age have been delivered across four domains: protection
of health, healthy development, safe environment, and management and
follow-up of health problems (Scholle et al., 2009). The age groups are
infancy to 6 months, by age 2, by age 6, by age 13, and by age 18. Box
5-3 shows as an example the elements of care that need to have occurred
by age 6. What is not yet known is the extent to which adherence to these
services is associated with child health outcomes.
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BOX 5-3
Quality Measures for Well-Child Visits (by age 6)
Protection of Health
• Immunizations
• Vision screening
• Oral health exam
• Blood pressure assessment
• Hearing
Healthy Development
• Developmental screening
• Weight assessment and counseling for nutrition and physical activity
• Counseling on screen time
• Parental competencies
Safe Environment
• Environmental tobacco assessment and counseling
• Domestic violence
• Firearm safety
• Vehicle safety
• Water safety
• Sports safety
Management and Follow-Up of Health Problems
• Individualized care plan
SOURCE: Scholle et al., 2009.
Opportunities to Link National Databases
Improved outcomes for populations of children and adolescents may
be monitored through efforts to link to more national databases. The po-
tential to link files across two or more national databases holds promise for
providing further insight into contextual factors that constitute important
health influences for children and adolescents, demographic variables that
may be correlated with the use and quality of health care services, impor-
tant outcomes for populations of children and/or adolescents, and improve-
ments at the community and national levels.
A National Research Council (NRC) workshop summary reviews the
strengths and limitations of key national databases that serve as sources for
estimates of insurance coverage for children (NRC, 2010). These databases
include data collected by the American Community Survey, the Current
Population Survey, the National Health Interview Survey, the Medical Ex-
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penditure Panel Survey (Household Component), the Survey of Income and
Program Participation, and the National Health and Nutrition Examina-
tion Survey. The report notes that “the presenters emphasized conducting
targeted methodological research, building bridges between the surveys so
that they could benefit from the strengths of each other, and providing data
users more information for analyzing and possibly further adjusting data”
(NRC, 2010, pp. 3–12).
Jurisdictional Issues Among Federal Agencies
One persistent barrier to efforts to achieve an optimal national mea-
surement system for child and adolescent health and health care quality
involves jurisdictional issues among federal agencies. The surveys described
in the preceding section, for example, are conducted by separate agencies
within HHS as well as other federal departments. Although a coordinating
mechanism exists in the form of the Federal Interagency Forum on Child
and Family Statistics, no agency is charged with leadership in striving for
greater consistency and standardization in such basic areas as definitions
of race and ethnicity or the inclusion of common age breaks that could
facilitate comparisons across multiple surveys. Furthermore, research on
the design and use of innovative measures, especially in such areas as a
life-course perspective, social and behavioral determinants of health, and
family-focused measures, is limited. Although various coordinating and
high-level workgroups have attempted to solve these problems, their efforts
have met with little success. The absence of a central registry of all federally
supported longitudinal studies of children and adolescents, for example, is a
sign of the limited resources and support allocated for efforts to coordinate
interagency data sets.
PROMISING STATE AND LOCAL INITIATIVES
In addition to national efforts to do more with existing databases, some
states and localities are experimenting with strategies to enhance their use
of state and local data sources. These efforts include integrating health care
data sets, as well as linking health care information with other data sources.
An alternative approach is “layering” data systems through geocode map-
ping to highlight areas of common interest where problem behaviors tend to
cluster. The feasibility of taking these initiatives to scale involves numerous
questions around agency lead, infrastructure development, and resources
required, among others. The 2011 IOM report For the Public’s Health: The
Role of Measurement in Action and Accountability addresses these linkages
in greater detail (IOM, 2011a).
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Massachusetts: Pregnancy to Early Life Longitudinal Data System
Massachusetts has developed a linked research database—the Preg-
nancy to Early Life Longitudinal (PELL) data system. This system links
maternal and infant hospital discharge records with birth and fetal death
records, and further links these records to additional public health and
social services databases, including Early Intervention; the Supplemental
Nutrition Program for Women, Infants, and Children (WIC); and birth
defects and cancer registry data (BUSPH, 2010). The linkage in the Mas-
sachusetts PELL data system has generated numerous investigations of the
quality of perinatal care (Clements et al., 2006, 2007; Declercq et al., 2007;
Lazar et al., 2006; Shapiro-Mendoza et al., 2006; Tomashek et al., 2006).
Indiana: Child Health Improvement through
Computer Automation System
The Child Health Improvement through Computer Automation
(CHICA) system at Indiana Children’s Health Services aims to strengthen
parental involvement by asking parents about risks and concerns as part
of a pediatric visit. Parental responses help ensure that physicians know
about issues that need to be addressed and can shape the visit to make it
more efficient.
CHICA is a computer-based decision support and EHR system for pe-
diatric preventive care and disease management. Parents fill out a prescreen-
ing form in the waiting room that includes questions about risks, concerns,
and reasons for the visit. The handwritten responses are then scanned and
uploaded into the computer system, which generates customized items on
a form used by the physician when he or she sees the patient. For example,
if the parent has indicated that the child lives with a smoker, CHICA will
prompt the pediatrician to discuss smoking cessation as well as the dangers
of secondhand smoke (Downs et al., 2008). The information is tracked
from clinic to clinic and from visit to visit.
Colorado: County Health Profiles
The Colorado Department of Health Care Policy and Financing
(CDHCPF) has adopted the position that its role is to hold payers account-
able for the health of the populations they serve (Wadhwa, 2010). To this
end, CDHCPF uses a county health ranking model developed by the Uni-
versity of Wisconsin to examine the impact of policies and programs and
population health factors on health outcomes. This model proposes that the
physical and the social and economic environments contribute 50 percent
to health outcomes, while factors within the health care system (clinical
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care and health behaviors) contribute the remaining 50 percent. The social
and economic environment alone (rates of education, employment, income,
family and social support, and community safety) is presumed to contribute
40 percent to population health outcomes. CDHCPF collects data from
multiple state and federal sources and constructs health profiles for each
county within the state. These county profiles organize health conditions
and health care services into three categories: on the right track, needs im-
provement, and major challenges. This type of innovative practice requires
expertise in working with multiple population health and administrative
data sources, as well as statistical methods for comparing and analyzing
data trends over time for selected populations.
Rhode Island: Asthma State Plan
One compelling example of a state-based partnership that uses data
from multiple sources to address a chronic health problem is the Asthma
State Plan adopted by the state of Rhode Island (RIACC, 2009). This plan is
the result of a collaborative effort between the Rhode Island Department of
Health and the Rhode Island Asthma Control Coalition, which consists of a
variety of community health organizations. Recognizing that 11 percent of
children in the state have asthma, the plan draws on an integrated chronic
care health systems approach to effect change. This systems approach iden-
tifies 14 asthma-specific goals within five broad categories, which apply to
both adults and children and include the following examples:
• Ensure that policies, programs, and systemwide changes are based
on and evaluated using timely, comprehensive, and accurate asthma
data.
• Decrease the disproportionate burden of asthma in racial and eth-
nic minority and low-income populations.
• Reduce exposure within schools to environmental asthma triggers,
irritants, and asthmagens.
In developing a data system to implement various objectives under each
goal, the Asthma State Plan does not seek to integrate multiple data sets,
but rather relies on a strategy that designates an agency as the principal
actor and specifies the data set that should be used to monitor progress
toward achieving each objective. To reduce exposure within schools, for
example, the Rhode Island databases used by the Department of Education
provide the basis for monitoring the following key objective: “By 2014,
increase the number of ‘High Performance’ schools that adopt construc-
tion, maintenance, and cleaning practices from 0 in 2008 to 20” (RIACC,
2009, p. 36).
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Multiple state-level data sources are used to monitor performance, in-
cluding the 2005 Rhode Island Behavioral Risk Factor Surveillance System
(BRFSS), the 2008+ Rhode Island BRFSS Call-back Survey, and the Rhode
Island Chronic Care Collaborative (RICCC) Asthma Database. The Rhode
Island Asthma State Plan demonstrates that federal and state-based data
systems can be used to support collective action and quality improvement
efforts designed to address child health problems. Such efforts require dedi-
cated financial and human resources, however, both to support the initial
organizing, planning, and goal-setting efforts and to sustain the activities
associated with data monitoring, analyses, and progress reports.
Philadelphia: Kids Integrated Data Set
The city of Philadelphia has established linkages among multiple data
sets maintained by the departments of education, human services, law
enforcement, and others. The Kids Integrated Data Set (KIDS) provides
basic guidance for public officials in determining where resources can be
matched with “hot spots” of vulnerable populations and neighborhoods.
At present, however, health information cannot be linked effectively into
the KIDS program because of legal and administrative restrictions that
prevent “memorializing the link” between an individual child’s health and
educational records (Schwarz, 2010).
Austin, Texas: Children’s Optimal Health
Based in Austin, Texas, Children’s Optimal Health (COH) is aimed at
improving children’s health in the central Texas area through the use of
geographic information system (GIS) mapping. The group is a nonprofit
association consisting of approximately 50 members, including hospital
systems, universities, businesses, and local agencies involved in health, edu-
cation, and housing. COH does not aim to integrate separate data sources,
but draws on a wide range of proprietary and public data sets that would
otherwise never be shared. These data sets undergo a layering process that
integrates the data without compromising the confidentiality of individual
patients or the institutional data holders or violating legal restrictions such
as those associated with the Health Insurance Portability and Accountabil-
ity Act and the Family Educational Rights and Privacy Act. The layered
data are fed into the GIS to form a succinct and powerful visualization—
such as color-coded maps—of the community’s health, which identifies
social determinants (such as income or education levels) and highlights
influential geographic factors (such as the location or clustering of specific
businesses). These maps are then used by the participating groups within
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COH to suggest steps for improvement and to formulate opportunities for
collaborative policies (Sage et al., 2010).
In 2008, COH initiated a GIS mapping effort to address obesity trends
among middle-school-aged children in Austin. First, the group sought data-
sharing agreements from nearby hospital systems, federally qualified health
centers, the city’s housing authority, the Austin independent school district,
organizations that offer services to youth and families, and a national
health information exchange. The data sets produced from these agree-
ments included data on students’ body mass index, cardiovascular fitness,
endurance, and flexibility, which could then be mapped to the locations of
specific school districts. COH also collected police incident data that, once
mapped, could account for less time spent outdoors because of a parent’s or
child’s reduced sense of safety. A technical advisory committee ensured that
all data were standardized and deidentified and offered initial interpreta-
tions of resulting maps. The final outcomes were presented at a community
summit to engage the community in analyzing the findings and develop next
steps (Sage et al., 2010).
SUMMARY
This chapter has provided an overview of child and adolescent health
care quality measures, emerging opportunities to improve the development
and use of measures, and unresolved difficulties that continue to challenge
both the measurement of quality and the delivery of high-quality care for
children and adolescents. A number of factors contribute to the current
state of quality measurement. For example, the committee found that
the motivations for creating and using quality measures for younger and
older populations differ. One reason for this difference is the absence of
private-sector incentives for the measurement and improvement of health
care quality in younger populations. As a result, the state of health care
quality measures for youth lags far behind that for adults. The absence of
private-sector activity, coupled with the compelling need to improve health
care quality and population health outcomes for children and adolescents,
supports the need for a stronger public-sector presence in the design, col-
lection, use, and reporting of such measures.
As described in this chapter, federal agencies have made some progress
in addressing these shortcomings through the identification of an initial core
set of standardized quality measures for children and adolescents. However,
the exclusion of any measure for which validity, reliability, and feasibil-
ity have not been extensively documented has resulted in the neglect of
measures for important areas of health for which evidence is limited (such
as mental health, substance use, oral health, and relatively rare chronic
conditions). Quality measures are especially important for the content of
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and follow-up on preventive and early intervention services for children
and adolescents.
In addition, studies of vulnerable and marginalized populations of
children and adolescents require greater attention to social and economic
factors in assessing health care quality and health outcomes for children
and adolescents. Some measures are available in these areas, but their
implementation is limited in the absence of state and national data systems
that support such measurement.
Although a number of measures of child and adolescent functional
status exist, none have been accepted as “standard” measures. As noted
in the previous chapter, there is no agreement on the appropriate domains
for these measures, and little is known about the sensitivity of most such
measures to medical care interventions.
This chapter has highlighted a number of emerging opportunities to
improve the development and use of child and adolescent health care qual-
ity measures. For example, using a life-course approach to measurement
provides a more comprehensive view of child and adolescent health care. A
life-course perspective can inform understanding of the outcomes of preven-
tive and early interventions, as well as the health consequences associated
with early social environments. Incorporating this perspective will require
longitudinal data sets that can follow population groups across episodes of
care, as well as the management and measurement of care transitions across
multiple settings and across time. Such transitions are especially salient for
children and adolescents with special health care needs or chronic health
conditions, as well as for the general population across specific life transi-
tions, such as those from the prenatal stage to early childhood and from
adolescence to young adulthood.
This chapter has provided examples of state and local efforts that
encourage collaboration; foster the use of population health and admin-
istrative data sets among health care providers and their institutions and
other service settings; support quality improvement practices; and inform
coordinated interventions to prevent and mitigate health risk behaviors, as
well as address the social and environmental contexts in which behaviors
develop. These strategies can improve the timeliness of data collection
and the transparency of data sources, with the ultimate goal of improving
child and adolescent health care quality. However, taking these efforts to
scale will require a full examination of Health Insurance Portability and
Accountability Act regulations and state and local capacity to analyze,
interpret, and report on data, among other issues.
Finally, additional work is needed to expand the existing collection of
measures of child and adolescent health care quality. It will be necessary to
underscore the need for broader availability of outcome measures across
sectors; the collection and reporting of measures of social influences on
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health; and the creation of measures that can follow children and adoles-
cents across different care settings, health plans, and multiple states over
time. Clinical and comparative effectiveness research and the Centers of
Excellence (U18) awards authorized by the CHIPRA legislation offer two
important opportunities to build the evidence base for health care access
and quality measures and to fill critical gaps, especially those gaps that
address the specific characteristics and needs of younger populations. New
initiatives associated with HIT and the creation of EHRs also offer substan-
tial opportunities to foster the incorporation of children and adolescents
into efforts to build the next generation of data sources and data collection
methods. However, these efforts by themselves are unlikely to achieve this
objective. Ultimately, greater alignment among federal agencies concerned
with technology and quality measurement will be necessary.
