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Societal Costs of Child and Adolescent Mental Health Disorders

Abstract and Keywords

Costs related to mental health and neurodevelopmental conditions (MHNCs) in childhood are experienced by multiple groups, including families, public and private service systems, and society as a whole. This chapter provides a conceptual model of MHNC-related costs, reviews estimates of short-term and long-term costs, and discusses the role of economic evaluation of services. Our conceptual model suggests that it is critical to consider costs from a broad point of view, but current literature on cost of MHNCs is uneven, with significant focus on short-term health system costs and very little emphasis on long-term costs or costs outside the health system, such as costs to families. There is a growing body of literature on MHNC costs, but more emphasis is needed in areas where there is little data to ensure that decision-makers have comprehensive data on the impact of MHNCs in order to manage scarce resources equitably and efficiently.

Keywords: conceptual models of costs, short-term costs, long-term costs, scarce resources, economic evaluation of services, mental health costs, neurodevelopmental condition costs

Introduction

Mental illness and neurodevelopmental conditions in childhood are common and can cause significant disability and suffering for children and their families (Merikangas, Nakamura, & Kessler, 2009). Fortunately, there are growing numbers of treatments and programs that can significantly reduce symptoms and improve long-term outcomes for children (Effective Child Therapy, 2017; Substance Abuse and Mental Health Services Administration [SAMHSA], 2017). However, providing services for children with mental health and neurodevelopmental conditions (MHNCs) is virtually always constrained by scarce resources and competing needs by a variety of groups. There are never sufficient resources to meet all of the possible needs of society, and whether we like it or not, this scarcity seems to be a permanent feature of most healthcare, education, and social services environments. For this reason, it is important to have a clear understanding of the costs related to child and adolescent mental health.

Understanding the costs associated with childhood MHNCs is complex, and costs are experienced by multiple groups, including families, public and private service systems, local communities, and society as a whole. These costs differ by type and severity of condition and are affected by the local environment (e.g., available services) and choices made by health systems, providers, and families. Several different types of economic studies can contribute important understanding regarding the implications of mental health policies and programs, whether at the level of state and federal policy or insurance coverage or the relative value of different approaches to treat MHNCs. This chapter provides an overview of an economic approach to understanding children’s MHNCs and the costs associated with these conditions.

The discussion begins with a conceptual model of the costs of children’s MHNCs. Next, the chapter defines some of the most common terms used in economic studies of MHNCs, discusses the (p. 137) components of cost estimates, reviews estimates of short-term costs related to MHNCs and long-term costs, and discusses the role of economic evaluations of specific MHNC services. Rather than provide a comprehensive review of all literature in each of these areas, this chapter provides brief reviews of what is known and examples of each of these economic approaches from recently published studies. Interested readers are guided to recent literature and comprehensive reviews on each topic if they exist.

Review of the Literature

To identify recent studies on the cost of childhood MHNCs, we searched PubMed, Medline, and PsycINFO for peer-reviewed journal articles published in English from 2006 to 2016. Search terms included a wide range of terms related to costs and economic evaluation (e.g., cost, cost-effectiveness, expenditures); MHNCs (e.g., mental health, psychiatric); and specific diagnostic terms (e.g., autism, anxiety). Only articles that focused on children or adolescents were included, and we excluded studies about MHNCs that did not include specific information on costs or that focused solely on use of psychiatric medication. While psychiatric medication is an important treatment strategy, there are a large number of cost studies that are limited to the cost of medications for some specific disorders (e.g., attention deficit hyperactivity disorder, ADHD) and are beyond the scope of this chapter, which broadly discusses MHNC costs and does not comprehensively review all possible economic information on all conditions and treatments. Also, we do not include review papers that depended only on past analyses to calculate costs. Article titles and abstracts were reviewed, and articles were selected to provide a variety of recent economic studies to illustrate key issues in cost estimation and to help to identify gaps in the literature. All monetary cost figures reported were converted from the cost reported in the original study into 2016 US dollars for comparability.

Conceptual Model

A conceptual model of child MHNC cost is presented in Figure 11.1. The model is broken into three periods to represent the longitudinal nature of MHNC costs, including prior periods (before recognition or treatment of MHNCs), current period, and future periods. The model is a simplification, showing only three discrete time periods; however, in reality there are a multitude of periods between first identification of an MHNC and the long-term outcomes described in the future periods section of the model.

The purpose of the model is to illustrate the longitudinal nature of MHNCs and their associated costs and to lay out the process involved in accruing costs over time. The key features are (a) child, family, and community factors that influence MHNCs and how families respond to MHNC symptoms and behavior (e.g., family ability to pay for services); (b) types of care actually used in a current period and the short-term costs associated with this care (e.g., cost of care received, such as psychotherapy appointments); and (c) long-term consequences of care received in prior periods (e.g., improved educational outcomes due to improvement in child functioning from services received in prior periods). The model could represent the accrual of costs for a group of children (e.g., all children with MHNCs in a community) or for a specific child. In the descriptions of the model that follow, we use a hypothetical child with ADHD, Jayden, to illustrate different types of costs over time.

The left section of Figure 11.1 represents the period prior to receipt of any type of care for MHNCs. A child’s MHNC arises and is identified within a specific community and family system. Factors related to these systems may be related to the occurrence of a MHNC or to the recognition of the MHNC. A number of child-related factors influence the model. A child’s experiences (i.e., exposure to abuse or neglect) could affect child symptoms and behavior. Other important child factors are genetics, temperament, and demographic characteristics (e.g., age, gender). Factors such as these may also influence whether a child is identified as having a disorder or whether treatment is sought. Given the specific range of symptoms or behaviors that the child/youth is having, the family or community may identify the child’s/youth’s need and seek intervention to help the child. The severity of the symptoms and the complexity of the disorder (e.g., single condition or comorbid conditions) likely influence whether the child is identified (Merikangas et al., 2009, 2010).

In our hypothetical example, we have a young boy, Jayden, with ADHD. The child is identified as having challenges at school at age 5 due to having a difficult time following directions, disrupting other children by running around the room during quiet time, and repeatedly talking out of turn. The school requests that the parents consider getting the child evaluated by his health provider. (p. 138)

Societal Costs of Child and Adolescent Mental Health DisordersClick to view larger

Figure 11.1 Conceptual model of mental health and neurodevelopmental costs in children.

(p. 139) Family characteristics will influence whether the child’s need is recognized and the type of response that families have to that need (O’Connell, Boat, & Warner, 2009). Several aspects of the family are critical for considering costs related to MHNCs. Demographic factors such as household configuration (e.g., number of parents in the home, number of siblings) and whether the parents are employed will influence financial and time resources available to the family. For example, single-parent families may have less time or other resources to pay for professional care.

Family financial resources play an important role in access to and use of services and subsequent costs. Families with greater financial resources may be able to pay for more extensive services, especially services not covered by insurance.

Parents’ characteristics will also play an important role. A parent’s culture, knowledge, and beliefs about mental health conditions will influence their recognition of the child’s symptoms, and this is often the first step in getting help for the child. If a child’s condition or symptoms are not recognized by parents, the symptoms may go untreated and contribute to costs in future periods.

Parenting skills and knowledge may influence the parent’s ability to provide home care related to the child’s condition. The parent’s own physical and mental health are also important factors that could influence MHNC costs (O’Connell et al., 2009). If a parent is experiencing personal health issues, such as depression or substance abuse, the parent may be less able to recognize or respond to the child’s need. Along similar lines, the parent’s own experience with MHNCs and services may influence their beliefs about the effectiveness of services and the types of services they seek for the child or are willing to accept on behalf of the child; this will influence the types of costs experienced in current and future periods.

Returning to the hypothetical example, several family-related factors influence identification of Jayden’s condition. Jayden lives with his single mother, who works full time; his father lives in another state, so he provides little ongoing care for Jayden. It is difficult for Jayden’s mother to take time off work, and Jayden’s provider is a 45-minute drive each way from the school. The mother’s parents do not think there is anything wrong with Jayden, are worried about him being labeled as “difficult,” and discourage the mother from seeking care. It takes most of Jayden’s first year of school to get him evaluated and diagnosed.

The broader environment plays a significant role in which types of costs are accrued related to MHNCs. Some communities have more extensive resources available, such that a child with a MHNC is more likely to be identified or to receive care and thus incur treatment costs. For instance, some local areas may have specialized early psychosis programs to help adolescents who are experiencing the first symptoms of psychotic disorder. Youth in these communities may incur greater costs in the current period than youth living in communities that do not have such programs, but the programs could reduce symptoms, improve functioning, and lower costs in future periods. Other public and private systems will also influence costs. For instance, in a community with well-funded public schools, services for some conditions may be provided through the school system (e.g., aides in classrooms for children with ADHD). Some communities, such as larger cities and wealthier communities, may have many services including public health clinics, specialty mental health services, social welfare programs and special schools for children with MHNCs. However, in other communities, such as very low-income or rural areas, few services may be available. Children in communities with fewer resources may have lower short-term costs, but incur larger costs in the long term.

In addition to the services that are available in communities, other environmental factors may influence MHNCs. For instance, in communities with high levels of violence, children may be subject to traumatic events or persistent stress that may increase symptoms and need for services. Conversely, environments that support a healthy lifestyle (e.g., more parks, access to healthy foods) may help to reduce symptoms and improve child functioning. In addition, local public health programs or policies will influence recognition of MHNCs and available treatment resources. For instance, some local areas may have legal mandates for insurance companies to provide specific levels or types of care, such as applied behavioral analysis (ABA; Fifield, 2016) for children with autism spectrum disorder (ASD). In these communities, it will be easier for parents to find such care. In addition, if insurers cover ABA because of a mandate, more providers may start offering such services, potentially increasing competition and reducing the cost of the service.

Returning to our hypothetical example, Jayden and his mom live in a medium-size city, and Jayden goes to a public school. The school has some resources for children with ADHD, but due to recent (p. 140) budget cuts, they provide little to students unless the students are severely affected by ADHD. Jayden does not meet the school’s severity threshold for services. The health system in which Jayden receives his care has limited ADHD-specific services, although the pediatricians are well trained to diagnose ADHD. The primary treatment offered at Jayden’s health system is stimulant medication. The community has some private learning centers that provide behavioral services for children with ADHD, but Jayden’s mom’s health insurance does not cover this type of service.

The center column of Figure 11.1 represents the “current” period in which some type of help or care is sought for a child’s MHNC. The family may try to manage the child’s MHNC with informal care, such as trying different types of approaches to managing symptoms at home, or may seek professional help from the medical care system, such as the child’s pediatrician. Children may also be identified as needing help at school or in other public systems (e.g., child care). The care received by the child will result in short-term costs related to the specific care the child has received.

Services received are represented in Figure 11.1 by ovals and could include informal help from family or others and formal services in public or private systems, such as the healthcare system, schools, or other public systems (e.g., social welfare). Given the appropriateness, amount of care, and quality of the services received, the care will result in short-term health outcomes for the child, represented in the oval marked “child symptoms.” The care sought will also result in short-term costs; these are represented in the rectangular boxes. Costs in the economic sense include opportunity costs rather than being limited to purely financial transactions, and include unpaid MHNC-related care time provided by caregivers. Short-term costs are the costs of treating or managing a specific MHNC in the current period, for instance, the costs in the year following services. Costs often accrue to multiple sectors.

In Jayden’s case, his mother seeks care from his pediatrician, followed by two visits to a child behavior specialist in the health system and a trial prescription for stimulant medication. Jayden’s mom meets with the teacher and other school staff to see what school services might be available for Jayden and meets separately with a school system psychologist. These services result in several types of costs. There are direct costs to the two service systems consulted, the health system and the school system; these costs include the visit time with the professional staff, time for the staff to coordinate across the two systems, and costs of laboratory services to rule out contraindication for medication.

Jayden’s mother also experiences direct costs related to Jayden’s condition. She pays out-of-pocket copays for each health system visit, laboratory tests, and medication. She also has to take time off work to take Jayden to the health system visits and to meet with school staff as these are only available during the workday. In addition to the short-term direct costs, Jayden’s mom incurs some short-term indirect costs. The stress of managing Jayden’s care has decreased her work performance, and this resulted in her losing the opportunity for a promotion, which would have significantly increased her salary.

The right column of Figure 11.1 represents future periods. Longer term outcomes will depend on the appropriateness and effectiveness of the services received in the prior short-term periods. For instance, early intervention programs for children with ASD may reduce symptoms and improve functioning, such that needs for services in future periods are reduced. Conversely, an unrecognized or untreated MHNC in one period may lead to increased symptoms or poorer functioning, thus increasing a child’s needs and costs in the subsequent period. If a child receives appropriate and sufficient care in prior periods, improvements in clinical and other outcomes may reduce long-term costs for public sectors, such as special education; may reduce reliance on social services; and may reduce caregiving time and missed time from work for families. These changes could also result in reduced future spending or cost offsets for care in both the public and private sectors.

In Jayden’s case, stimulant medication is moderately helpful, and Jayden is somewhat better able to focus at school and has fewer behavioral difficulties at school. However, the medication also causes problems with sleeping that lead to additional doctor’s appointments and a prescription for sleep medication. In addition, Jayden’s mother is concerned about Jayden falling behind in school and feels he needs extra help to allow him to overcome some of the ADHD symptoms. Over several years, Jayden’s mother spends considerable time researching different options for Jayden. She finds a charter school in a wealthy suburb that provides innovative learning programs for kids with ADHD; it is about 1 hour from their home. She moves the family to the suburb, moving from a three-bedroom house with a yard to a small two-bedroom (p. 141) apartment. She is able to enroll Jayden in the program, and it is a great fit for Jayden; he graduates from high school with acceptance at a competitive public university.

There are direct costs to the two service systems: ongoing costs of medication to the health system and costs to the school system to offer the charter school program. Jayden’s family also experiences direct costs related to Jayden’s condition in the longer term, including ongoing out-of-pocket copays for each health system visit and for the medication. In addition, there are both increased costs in some sectors and decreased costs in other sectors. Jayden’s family incurs significant costs related to moving to the suburb that provides Jayden’s new school, including moving costs and higher transportation costs because Jayden’s mom has a much longer commute following the move. There are also reductions in costs for Jayden’s family. His mom has to take fewer days off work after the move and is much less stressed knowing that Jayden is doing well at school. In addition, there are likely other cost reductions related to Jayden’s improved outcomes. He is less likely to need public services as a young adult (e.g., welfare, public health) because he has successfully completed high school and is much more likely to have improved employment outcomes.

Definitions of Economic Cost Concepts and Methods

The conceptual model discussed indicates that an economic approach to understanding cost is broad and includes both immediate monetary costs (e.g., the labor, facility, and material costs of providing specific services such as psychotherapy) and indirect effects on families and others (e.g., effects on work for parents). It is important to note that the concept of cost in economics can be different from accounting costs, which typically are limited to financial costs. Table 11.1 provides definitions of some of the key concepts related to costs used in economics to understand outcomes related to childhood MHNCs (for more details on these terms, see Drummond, Sculpher, Torrance, O’Brien, & Stoddart, 2005; Gold, Siegel, Russell, & Weinstein, 1996).

Economic cost estimates are typically broken into several main categories: direct costs, indirect costs, and intangible costs. Direct costs are costs that occur directly related to the health condition, and these are often further broken down into direct medical costs and direct nonmedical costs. The direct medical costs are what one might first think of as the cost of MHNCs and would include things like the labor, facility, and material costs to provide mental health treatment visits, cost of diagnostic testing, and cost of psychiatric medications. However, in addition to the costs related to providing services or treatments for MHNCs, direct medical costs include costs to families, such as copayments for services. Direct nonmedical costs include costs to other systems related to identifying and managing MHNCs, including costs to the education system and social services and costs to families to pay for services not provided by insurance (e.g., special schools for MHNCs).

Indirect costs are losses that occur as a result of the child’s MHNC, not directly related to treating or caring for a child’s MHNC. The main indirect cost that is typically included in economic cost analyses is the productivity losses to parents related to a child’s MHNC (i.e., parents’ reduced productivity while at work from the stress of the child’s MHNC). In the long term, indirect costs can include lost productivity for the young adult with a MHNC.

Finally, economic analyses sometimes identify intangible costs related to MHNCs. Intangible costs are typically aspects of the burden of disease that are difficult to quantify or measure, such as impacts on quality of life of the child with a MHNC, emotional burden or stress on families, or pain and suffering. Although these are important to consider, these costs are not reviewed in detail in this chapter (see, for example, Brannan, Heflinger, & Foster, 2003).

There are several different types of cost analysis that are used to understand the cost of MHNCs (see Drummond et al., 2005; Gold et al., 1996, for more information). Cost-of-illness (COI) studies are typically conducted to understand the magnitude of the burden of a particular illness or category of illnesses. COI may include all direct and indirect costs and sometimes includes intangible costs, but often these are not explicitly measured. Some studies are designed specifically to measure COI, but frequently data collected for other purposes are used to calculate COI. The results of COI are typically an estimation of the annual cost per patient or the lifetime cost per patient associated with a specific illness (see Ganz, 2007, for example). These types of estimates are often used in policy discussions to motivate the importance of particular conditions and to help prioritize investments in service systems or research to develop new treatments for specific conditions. (p. 142)

Table 11.1 Definitions

Types of Costs

Definition

Examples

Direct Costs

Costs that occur directly related to a health condition or illness that can be borne by the health care system, patients’ families, or the community.

Direct medical

Direct health care inputs to identifying, managing health condition or illness.

Psychiatrist visits, family copay for psychotherapy, cost of antidepressants, cost of diagnostic testing.

Direct nonmedical

Nonmedical costs related to identifying, managing health condition or illness.

Cost of transportation to care, informal caregiving related to child’s health condition by family members, school aide for child with autism.

Indirect Costs

Indirect costs for patient

Productivity losses experienced by the person with the health condition or illness.

Work loss, loss of human capital development, early mortality.

Indirect costs for family/others

Losses experienced by other persons related to a patient’s health condition or illness.

Work loss, loss of human capital development

Intangible Costs

Burden of disease that is difficult to quantify in dollars but that impacts the quality of life of patients, families, and communities.

Pain and suffering from symptoms of depression, feelings of stress or burden on family members.

Types of Cost Analysis

Cost of illness (COI)

Estimation of the costs related to a health condition or illness; usually includes direct medical and nonmedical costs associated with the illness and sometimes includes indirect costs associated with lost productivity or other losses due to morbidity or premature mortality.

  • Annual costs per patient with autism in a population.

  • Lifetime costs per person with conduct disorder in a population.

Economic evaluation

A general term for a group of methods where two or more alternative interventions, programs, or policies are evaluated in terms of both their costs and their consequences; economists usually distinguish several types of economic evaluation differing in how consequences are measured.

Most common types are cost-effectiveness analysis (CEA), cost–utility analysis (CUA), cost–benefit analysis (CBA).

Cost-effectiveness analysis

An economic evaluation method in which two or more interventions are compared and where all included costs are related to a common effect; results are usually stated as additional cost expended per additional health outcome achieved; results are typically reported as incremental cost-effectiveness.

Compared to usual care in outpatient clinics, a new group cognitive behavioral therapy (CBT) program for teen depression has an incremental cost of $10 per depression-free day achieved.

Cost–utility analysis

A form of CEA where the health outcome is measured as quality-adjusted life years (QALYs).

Compared to usual day treatment in hospital clinics, a new psychotherapeutic program for post-traumatic stress disorder (PTSD) has an incremental cost of $1,000 per QALY gained.

Cost–benefit analysis

A type of CEA in which all costs and benefits are converted into monetary (dollar) values and results are expressed as either the net present value or the dollars of benefits per dollars expended; can be used to compare different types of interventions or programs, including programs for different health conditions.

Net present value (NPV) of new diabetes program is $10,000; NPV for new depression management program is $20,000.

Other Definitions

Perspective of a cost analysis

Determines which costs and benefits will be considered.

Some common perspectives are the health system, public service system, or societal perspective.

Societal perspective

Seeks to consider all costs and benefits regardless of who incurs the costs and who receives the benefits.

Quality-adjusted life years

A measure of health outcome used in some types of cost-effectiveness analyses and recommended by several national governments for policy decisions.

QALYs are typically measured with preference-based utility questionnaires such as the EQ-5D or the HUI1/HUI2.

Cost offset

The reduction in cost, or the cost savings, associated with providing an intervention or service.

Reduced long-term cost of special education following early intervention for children at risk for significant mental health and neurodevelopmental conditions.

Opportunity costs

An economic term that indicates all resources that are foregone to produce a service or activity; these are not limited to monetary costs and can include unpaid time that is used to produce a service or activity.

Monetary cost of providing a medical care visit (labor, facility, materials), unpaid time spent by caregivers to provide treatment in home.

Incremental costs

The additional cost to provide one service or program over another.

EuroQol 5D (EQ5D) and the Health Utility Index (HUI1/HUI2) are generic quality of life instruments.

(p. 143) Economic evaluations differ from COI in that they typically focus on the costs and health outcomes associated with alternative treatments or systems of care. For instance, an economic evaluation might look at the costs and clinical outcomes from a brief cognitive behavioral intervention for depression compared to costs and clinical outcomes of antidepressant therapy. There are a number of different types of economic evaluation, with the most common types being cost-effectiveness analysis, cost–utility analysis, and cost–benefit analysis. They all attempt to evaluate the relative value of different approaches to achieving a similar goal, taking into account clinical or other intangible outcomes, as well as the related costs. Most experts in the field of economic evaluation suggest that direct and indirect costs should be included in any economic evaluation (Drummond et al., 2005; Gold et al., 1996). In (p. 144) some countries, economic evaluations are required for services to be approved for payment by public health systems; in these cases, there are guidelines about which types of costs must be included and how they should be measured. Nevertheless, there is still considerable heterogeneity in both inclusion of different types of costs and of measurement techniques (Woolderink et al., 2015).

Findings From the Literature Review

Short-Term Costs of MHNCs

Returning to the conceptual model, the first set of costs we review are short-term costs that occur close in time to receipt of services or treatment for MHNCs. Depending on the perspective of the cost study (e.g., health-care only, societal, etc.), different types of costs may be included in studies that estimate short-term costs. Table 11.2 reports examples of recent literature (published from 2006 to 2016) that estimate short-term costs for several common childhood MHNCs.

A few studies include data on multiple MHNCs. For instance, Costello and colleagues (Costello, Copeland, Cowell, & Keeler, 2007) reported annual costs of health and other services received by youth from the Great Smoky Mountains psychiatric epidemiologic study, reporting on costs separately for depressive disorders, anxiety disorders, and disruptive behavior disorders. Along similar lines, studies in the United Kingdom have reported on costs using the British Child and Adolescent Mental Health Surveys (BCAMHS; Snell et al., 2013). Most studies have focused on one MHNC, such as ASD (Lavelle et al., 2014) or ADHDs (Hakkart-van Roijen et al., 2007).

There are many more studies on some types of MHNC than other types. We identified 14 recent studies that provided some type of estimate of the short-term cost for ASD; 12 articles focusing on ADHD; 7 on internalizing disorders (e.g., depression, anxiety); and 4 on conduct disorders in childhood. Previous reviews have observed this same pattern (see Beecham, 2014). Further, reviewing references in the studies reported in Table 11.2 and previous reviews, we identified comprehensive review articles for some disorders. For example, there have been several comprehensive reviews of the cost of ASD. Ganz (2007) brought together data from a number of sources, including both previous studies and some new analyses, to provide a national estimate of cost of ASD for the United States. Knapp and colleagues (Knapp, Romeo, & Beecham, 2009) also provided a comprehensive review of ASD costs. Along similar lines, there have been several articles reviewing the literature on costs associated with ADHD (e.g., Doshi et al., 2012). We identified no reviews of cost studies for any internalizing disorders or conduct disorders, and we note that such reviews also were not identified in previous work (Beecham, 2014; Knapp & Evans-Lacko, 2015).

The scope of cost data included varies substantially between studies. Looking back at the conceptual model in Figure 11.1, we note that youth can receive services from multiple service sectors, especially health and education. In addition, parents or families may provide some informal care, or older youth may seek self-help resources. Health economists and health services researchers have noted the importance of this broad view of services because changes in policies in one sector may shift costs toward or away from other sectors (Costello et al., 2007; Foster, Jones, & the Conduct Problems Prevention Research Group, 2006). For instance, where significant services are provided in schools for a condition like ADHD, there may be fewer costs incurred in the health system. Community psychiatric epidemiologic studies have emphasized the importance of the education sector as it may be the most common source of help for many children (Costello et al., 2007). Table 11.2 reports on the scope of costs reported for recent studies.

Some studies included a wide range of costs, including direct medical, direct nonmedical costs, and indirect costs (e.g., Barrett et al., 2012; Bodden, Dirksen, & Bogels, 2008; van der Kolk et al., 2015). But, even within studies that take a broad view, there can be significant differences regarding estimates. For example, using baseline data from a randomized controlled trial including children 2–5 years old, Barrett and colleagues (2012) estimated short-term costs for young children with ASD and included a broad range of service costs, including health, mental health, education, social care, family out-of-pocket expenditures for services, and indirect costs due to parents’ lost time from work. They estimated total annual care costs per child with ASD to be “$9,501 (2016 US$). In contrast, a review using data from a variety of studies (Buescher, Cidav, Knapp, & Mandell, 2014) estimated total annual care costs per child with ASD to be between “$10,689 and $16,203 (2016 US$) for younger children in the United Kingdom and $67,474 to $115,100 for younger US children. Along similar lines, for children with ADHD, Hakkaart-van Roijen and colleagues (2007) estimated total annual (p. 145) (p. 146) (p. 147) (p. 148) (p. 149) (p. 150) (p. 151) care costs per child of $6,360 (2016 US$), while van der Kolk and colleagues (2015) estimated total annual care costs per child of $11,656 (2016 US$).

Table 11.2 Types of Costs Collected in Recent Studies

Category of Mental Health Condition First Author/Year

Sample Source of Data

Country Years of Data

Public and Private Service Costs

Family Economic Outcomes

Autism

Direct Costs

Direct Costs

Indirect Costs

Barrett 2012

N = 152

Ages 2–5 years

Baseline data from RCT

United Kingdom 2006–2007

Health, mental health, education, other public services

Parent out-of-pocket expenses

Parents’ work loss

Cidav 2012

N = 261

Ages 3–17 years

MEPS, NHIS

United States

Not included

Not included

Parent employment outcomes

Cidav 2013

N = 45,948

Medicaid claims data

United States 2005

Health, mental health, Rx

Not included

Not Included

Croen 2006

N = 3053

Ages 2–18 years

Claims from large population-based health system

United States 2004

Health, mental health, Rx

Parent out-of-pocket cost for health services

Not included

Ganz 2007

N not reported

Literature review, MEPS, NHIS

United States 2003

Health, mental health

Parent work outcomes

Horlin 2014

N = 521

Ages 0–18 years

Parent report, questionnaire, Autism Registry

Australia

2010–2011

Health, mental health, Rx, education—use only not cost

Parent out-of-pocket cost for multiple types of services

Parent work productivity

Lavelle 2014

N = 109 ASD health service

N = 137 ASD non-health services

MEPS/NHIS health service

Patient panel survey nonhealth

United States 2001–2008

Health, mental health, Rx, dental, education

Parent out-of-pocket costs for services

Caregiving time

Leslie 2007

N = 9,506

Age 0–17 years

Medicaid insurance claims

United States 2000–2004

Health, mental health, Rx

Parent out-of-pocket costs for health services (not reported separately)

Not included

Liptak 2006

N = 111

Age

MEPS, NHAMCS

United States 1997–2000

Health, mental health, Rx

Parent out-of-pocket expenditures

Time missed from school for child

Ouyang 2014

N = 363

Age

National Survey of Children With Special Health Care Needs

United States 2009–2011

Not included

Financial burden

Parent work outcomes

Peacock 2012

N = 8,398

Medicaid claims

United States 2003–2005

Health, mental health, Rx

Not included

Not included

Petrou 2010

N = 11

Age 11 years

EPICure Cohort Study

UK, Ireland

2006–2007

Health, mental health, other services

Not included

Not included

Shimabukuro 2008

N = 2,169

Age

Marketscan claims data

United States 2003

Health, mental health, Rx

Parent out-of-pocket costs for health services

Not included

Wang 2013

N = 18,108; N = 2,366

Ages 0–17 years

Medicaid claims/Marketscan private insurance claims

United States 2003

Health, mental health, Rx

Not reported

Not included

Internalizing Disorders

Bodden 2008

N = 118

Ages 8–18 years

Clinically anxious youth

Baseline data for an RCT

Data from cost diaries

Netherlands

2003

Health and mental health care, Rx, education

Parent out-of-pocket costs

Expenses for services, informal care

Parent absence from and reduced productivity at work

Costello 2007

N = 132

Ages 9–16 years

Depression or anxiety diagnosis

Epidemiologic study, parent self-report data

United States 1993–2003

Health, mental health, education, other services

Not reported separately

Not included

Domino 2009

N = 433

Ages 12–17 years

With depression

Baseline data from an RCT

United States 2003

Health and mental health care, education, social care, justice system

Parent out-of-pocket expenses for time and travel

Not included

Liptak 2006

N = 524

Ages 0–18 years

MEPS, NHAMCS

United States 1997–2000

Health, mental health, Rx

Parent out-of-pocket expenditures

Time missed from school for child

Petrou 2010

N = 16

EPICure Cohort Study

Emotional disorders

United Kingdom, Ireland 2006–2007

Health, mental health, other services

Not included

Not included

Snell 2013

N = 445 (all conditions)

Ages 5–15 years

BCAMH survey subsample with emotional disorders

United Kingdom 1999–2002

Health, mental health, education, social services

Not reported

Not included

ADHD

Braun 2013

N = 30,264

Insurance claims

Germany

2008

Health, mental health, Rx

Not included

Not included

Costello 2007

N = 135

Ages 9–16 years

Disruptive behavior diagnosis

Epidemiologic study, parent self-report data

United States 1993–2003

Health, mental health, education, other services

Not reported separately

Not included

De Ridder 2006

N = 537

Survey of parents of children with ADHD

Belgium 2002

Health, mental health, other services

Parent health care and out-of-pocket costs

Not included

Jones 2009

N = 650

Fast Track intervention study

United States 2000

Mental health, education, other

Not included

Not included

Hakkaart-van

Roijen 2007

N = 70

Interview of parents of children with ADHD

Netherlands

2004

Health, mental health

Not reported

Absence from work, productivity at work

Klora 2015

N = 9,083

Insurance claims data

Germany

2006–2008

Health, mental health, Rx

Not included

Not included

Petrou 2010

N = 17

EPICure Cohort Study

United Kingdom, Ireland 2006–2007

Health, mental health, other services

Not included

Not included

Ray 2006

N = 3,122

Claims from large population based health system

1996–2004

Health, mental health, Rx

Not included

Not included

Robb 2011

N = 364

Ages 11–25 years

United States 1999–2003

Education

Not included

Not included

Snell 2013

N = 445 (all conditions)

Ages 5–15 years

BCAMH survey subsample with emotional disorders

United Kingdom 1999–2002

Health, mental health, education, other

Not reported

Not included

Telford 2013

N = 143

Ages 12–18 years

Longitudinal ADHD Survey

United Kingdom 2010

Heath, mental health, education

Not included

Not included

van der Kolk 2015

N = 618

Ages 8–18 years

Parent self-report questionnaires

Netherlands

2012

Health, mental health, Rx, education, other

Out-of-pocket medical costs

Absence from work, productivity at work

Conduct Disorder

Jones 2009

N = 650

Fast Track intervention study

United States 2000

Mental health, education, other

Not included

Not included

McGilloway 2014

N = 103

Ages 3–7 years

Baseline data from RCT

Parent self-report interviews

Ireland

2004–2006

Health, mental health, education, other public

Not included

Not included

Petrou 2010

N = 17

EPICure Cohort Study

United Kingdom, Ireland 2006–2007

Health, mental health, other services

Not included

Not included

Romeo 2006

N = 80

Ages 3–8 years

Baseline data from RCT

Interviews with parents of children with persistent antisocial behavior

United Kingdom 2002–2003

Health and mental health care, education, social care

Parental service use

Parental expenses

Additional parental time on household tasks

Absence from work

Out-of-pocket medical and other costs

Parent work outcomes

Snell 2013

N = 445 (all conditions)

Ages 5–15

BCAMH survey subsample with emotional disorders

United Kingdom 1999–2002

Health, mental health, education, social services

Not reported

Not included

ADHD = attention deficit hyperactivity disorder; ASD = autism spectrum disorder; BCAMHS = British Child and Adolescent Mental Health Surveys; RCT = randomized controlled trial; Rx = prescription; MEPS = Medical Expenditure Panel Survey; NHAMCS = National Hospital Ambulatory Medical Care Survey; EPICure = Epicure is a series of longitudinal studies in the UK.

These differences arise for several reasons. There is no one standard that is required regarding reporting of services; some studies might include all outpatient services, and others might include only outpatient specialty care for MHNCs. Different data sources and inclusion of some but not all family costs in one study compared to another can also partially account for these differences. These differences underscore the importance of considering the scope of services included in different studies as it is not consistent even within disorders or age groups.

Many studies only consider a narrower estimation of short-term costs (e.g., Cidav, Marcus, & Mandell, 2012; Croen, Najjar, Ray, Lotspeich, & Bernal, 2006; Robb et al., 2011). Typically, these studies focus only on direct costs in one service sector, most commonly the health sector (e.g., Croen et al., 2006; Klora, Zeidler, Linder, Verheyen, & von der Schulenburg, 2015; Wang, Mandell, Lawer, Cidav, & Leslie, 2013). There is somewhat more agreement within these narrower categories, particularly if you compare studies that use similar data. For instance, considering annual healthcare costs per child with ASD for privately insured children, three studies provided similar estimates of $7,295 (2016 US$) (Liptak, Stuart, & Auinger, 2006); $6,850 (2016 US$) (Wang et al., 2013); and $7,732 (2016 US$) (Shimabukuro, Grosse, & Rice, 2008).

Although studies that collect a limited scope of data do not provide a comprehensive picture of the costs of MHNC, they tend to have larger samples and may provide more stable estimates of costs in that particular sector. These studies also may have enough subjects to explore important topics, such as the impact of specific patterns of comorbidity or the differences in costs across age groups (e.g., Cidav, Lawer, Marcus, & Mandell, 2013).

A few other studies have focused on other individual categories of cost. For instance, Robb et al. (2011) reported on costs to the education system for children with ADHD. Cidav and colleagues (2012) provided data on parent employment outcomes only.

It is difficult to compare the cost estimates across studies because there are multiple differences in the study designs and populations, including study design, type of data (health system claims vs. self-report), and researcher definition of scope (e.g., health system only, age range, what types of family costs to include). Eight of the studies reported in Table 11.2 used public or private claims data from healthcare systems, while two additional studies used data from other sectors (Jones & Foster, 2009; Robb et al., 2011). The remainder of the studies used data from surveys that depended on parent or youth self-report of services use or cost. Five of the studies were designed to collect data about a particular disorder (e.g., Hakkart-van Roijen et al., 2007; Horlin, Falkmer, Parsons, Albrecht, & Falkmer, 2014). Others used large epidemiologic or health services studies that included surveys of service use or cost. Two of these large surveys were designed specifically to collect data on children with mental health conditions (Costello et al., 2007; Snell et al., 2013), while seven others used data from large surveys that collected data on many health conditions and were not specific to psychiatric disorders (e.g., Busch & Barry, 2007; Lavelle et al., 2014; Liptak et al., 2006). Five additional studies used baseline data from randomized controlled trials to estimate short-term costs for several conditions. For instance, Domino and colleagues (2009) used baseline data from a large trial comparing depression treatments in youth to estimate the annual cost of youth depression.

Each approach has strengths and weaknesses, but it is important to remember that the approaches may yield substantially different results in terms of cost estimation (Woolderink et al., 2015). Large claims databases may provide more stable estimates of health system costs compared to parent self-report. Parents sometimes forget services or may not categorize a service correctly (e.g., not know whether a provider is a doctoral-level psychologist or a master’s-level therapist), and this can influence health system costs. On the other hand, parents can report on all services that youth receive, whether provided by their primary health system or by outside providers. In addition, only parents can report on some types of costs, such as nonhealth expenditures by the family or MHNC-related caregiving or care coordination by families. Large epidemiologic studies, such as the BCAMHS (Snell et al., 2013) or the US Medical Expenditures Panel Survey (Liptak et al., 2006), are carefully constructed surveys that have strong methods and provide generalizable results but may not ask some specific cost questions relevant to MHNCs (i.e., questions about use of services in social welfare or justice systems). On the other hand, smaller studies focused on specific conditions (e.g., Horlin et al., 2014) may provide richer detail on a specific disorder but typically have smaller samples, (p. 152) such that cost estimates may be less stable or representative. Studies that use data from randomized trials (e.g., Domino et al., 2009; Romeo, Knapp, & Scott, 2006) typically have strong protocols for data collection and often include costs in multiple domains, but these studies often have small samples and may not be representative of the overall population because children or families who participate in research may be different from those who do not.

In addition, studies can vary significantly in population; for example, Barrett and colleagues (2012) included only young children aged 2–5, while most of the claims-based studies included children of all ages (e.g., Croen et al., 2006; Peacock, Amendah, Ouyang, & Grosse, 2012; Wang et al., 2013), and some ASD-related costs, such as healthcare costs, have been shown to differ by age group (Cidav et al., 2013). In addition, studies vary in the severity of disorder and by type of location, with some in rural and some in urban areas. In addition, there are often large differences in health systems in different countries, and even within regions of large countries such as the United States, and these factors likely influence cost estimates. Thus, although we present example cost estimates to illustrate our discussion, direct comparisons between different studies are not likely to be accurate.

Despite the many differences in the literature, some patterns do emerge. For example, in the United States, studies that have looked at publicly insured children have typically estimated much higher costs than for those who are privately insured. For example, Wang and colleagues (2013) compared healthcare costs for children with ASD; they used similar methods with two claims data sets, the first from a large private claims database and the second from a large database of services for children with public insurance. They found that the healthcare costs associated with ASD were over three times as large for publicly insured children (mean cost private $6,850 vs. $29,536 (2016 US$) mean cost for publicly insured).

Another consistent pattern is that when costs of children with MHNCs are compared to children without a MHNC, the incremental cost of MHNCs is typically quite large, and this finding holds across multiple conditions. For example, Lavelle and colleagues (2014) used two nationally representative health surveys and found that, compared to children without ASD, mean healthcare costs were about $3,224 (2016 US $) more for children with ASD, and education costs were $9,192 (2016 US$) greater for children with ASD in the United States. Similar findings have been reported in multiple studies of children with ASD (e.g., Croen et al., 2006; Liptak et al., 2006; Peacock et al., 2012; Shimabukuro et al., 2008).

The same pattern is seen with other disorders; Costello and colleagues (2007) reported costs for multiple service systems for children and youth with several MHNCs compared to a community comparison group with none of these disorders. They estimated that total annual cost per child with depression was five times greater than for children without disorders, 2.7 times greater for children with anxiety disorders, and 4.3 times greater for children with disruptive disorders. This result was consistent even given differences in study designs. Studies using claims data (Croen et al., 2006; Liptak et al., 2006; Peacock et al., 2012; Shimabukuro et al., 2008); epidemiologic survey (Costello et al., 2007); and data from randomized controlled trials (Jones & Foster, 2009) all found similar differences, with consistently higher costs for children with MHNCs compared to those without such disorders.

Multiple studies found that there are substantial education costs associated with having a child with a MHNC. For instance, several studies have found that education costs are a large proportion of total annual costs of ASD (Costello et al., 2007; Horlin et al., 2014; Lavelle et al., 2014). Education is important for other conditions as well, including internalizing disorders (Costello et al., 2007); ADHD (Jones & Foster, 2009); and conduct disorder (McGilloway et al., 2014; Romeo et al., 2006). Robb and colleagues (2011) closely studied education costs for children with ADHD compared to children without this condition and found that costs occurred across a variety of education domains, including costs for teaching (teachers, special education classrooms); costs to administrators related to disciplinary actions; and costs to classmates from disruptions to the class by youth with ADHD. Although there is widespread recognition of the importance of education costs in understanding societal costs of MHNCs, there are much fewer data on these costs, and even when studies include education costs, they are often only including part of the cost, rather than a comprehensive assessment of cost such as that presented by Robb and colleagues (2011).

While there is quite a lot of data on some components of the costs of MHNCs, such as healthcare costs, there is much less known about other costs. For instance, while experts discuss the need to include a broad range of public services, few (p. 153) studies included a full range, and in particular few looked at costs to the justice system or social welfare system. Yet, these costs can be substantial. For instance, Jones and Foster (2009) reported criminal justice system costs of more than $1,000 per youth for youth with ADHD. It can be hard to get access to information on these service sectors, and to date we know of no studies that focused in depth on costs of services for children with MHNCs in either juvenile justice or social welfare services.

Another area where there are much fewer data is costs to families. Once a child’s need is recognized, families often experience the greatest burden of cost associated with MHNCs. For instance, parents of a child with ASD may need to provide intensive home care, pay for expensive services not covered by health insurance, and change employment arrangements to accommodate the child’s health needs. Some type of family cost was included in about half the recent studies listed in Table 11.2. But, family costs are often considered very narrowly. For instance, several studies included only out-of-pocket financial expenditures by families, and this does not include other important economic impacts. Parent work outcomes are measured quite often, but these have been inconsistently defined and valued, such that it is hard to compare studies. Finally, time for caregiving by parents of families is often ignored. We identified only one study that reported on data related to time in caregiving (Lavelle et al., 2014). Further, surveys often expect parents to report on time or employment outcomes over long periods of time, such as recalling caregiving time for 6–12 months (e.g., National Survey of Children with Special Health Care Needs (NSCSHCN)). This is very difficult for parents to do accurately. Other methods that could improve these estimates could help to make sure all family costs of MHNCs are documented. For example, time diaries (US Bureau of Labor Statistics, 2017) can be used that ask parents to report in detail on the time they spend on caregiving for short periods of times, such as over a 2-week period.

There is a growing body of information on the short-term cost of MHNCs and some information on a range of costs to different sectors; these data can be useful in developing and implementing policies and new treatments for child MHNCs. For example, having information on the annual cost of different disorders can help to prioritize how to invest funds to best improve children’s health. In addition, having data that provide a broad picture of health costs can alert policymakers to the need to pay attention to how new policies or programs in one sector (e.g., education) may impact other sectors (e.g., health). However, it is important to note that a substantial portion of the data that were used in recent estimates was generated over 10 years ago, and this limits its usefulness for policy. For example, new treatments (e.g., new programs for first-episode psychosis) or policies (e.g., state mandates for ASD services) could greatly influence short-term costs. In addition, when there are changes in investments in social services sectors such as education, public health services costs will likely change in response. For instance, if public education funds are cut such that schools cannot provide help to children with MHNCs, MHNC healthcare costs may rise. So, continued monitoring and analysis of short-term cost information is important to inform development and implementation of new policies or programs.

Long-Term Costs and Economic Outcomes

While short-term costs are important to understanding current expenditures, it is important to look beyond short-term costs when considering investments in new treatments or in planning for care of children with MHNC. As in the previous discussion, we focus on recently published (2006–2016) literature and report only on articles that provided new data analyses, not on studies that only reviewed other studies or that provided models from published literature. The articles reporting some type of outcome relevant to long-term costs are listed in Table 11.3. We identified 14 articles that provided some type of long-term economic outcome from MHNCs. Two studies provided data on long-term costs of ASD, four on internalizing disorders, six on ADHD, and two on conduct disorder, and two provided estimates of long-term costs related to mental health difficulties in general.

Just as in the measurement of short-term costs, both direct and indirect costs are important to consider. Direct costs of treatment in the long term may depend on the investments in earlier periods, and if services are effective, there may be cost offsets or cost savings in some direct cost categories. In addition, in the long term, indirect costs become a larger concern, and different indirect cost categories become important. While in the short run the major focus of indirect cost measurement is on how the child’s MHNC impacts the parent’s employment, in the longer run we want to consider impacts on the youth as he or she enters adulthood, especially impact on human capital development (educational (p. 154) (p. 155) attainment, training) and employment and earning ability. Family indirect costs are still important as the family may continue to have indirect effects if the youth is not doing well, such as impacts on a parent’s work. In addition, there may be other effects on other groups beyond the family. For instance, Foster and colleagues (Foster, Damon, & Jones, 2005) reported that in a high-risk group of young people, youth with conduct disorder had almost 10 times greater costs for juvenile justice (p. 156) services than those with no disorder. While the costs reported were direct costs for justice system services the youth received (e.g., jail time, services while in jail), they imply costs to others in the community, notably the victims of the crimes, public costs to provide legal services, and associated costs for families. On the other hand, if a youth receives appropriate effective services while a child, the youth may improve by adulthood and may be less likely to need social welfare services or income support, and these could be cost offsets or cost savings in these categories.

Table 11.3 Examples of Studies of Long-Term Economic Outcomes

Category of Mental Health Condition First Author/year

Sample Source of Data

Country Years of Data

Public and Private Service Costs

Family Economic Outcomes

Autism

Direct Costs

Direct Costs

Indirect Costs

Dillenburger 2015

N = 18,522

Millennium Cohort Study

UK

2000–2013

Not included

Not included

Employment, school outcomes

Liptak 2011

N = 725

National Longitudinal Transition Study

US

2000–2006/2007

Not included

Not included

Employment, school outcomes

Internalizing Disorders

Fergusson 2007

N = 345

Birth cohort, depression in ages 16–21 years, followed until 25 years

New Zealand

1977–2002

Not included

Not included

Educational attainment, unemployment, personal income

Knapp 2011

N = 9,071

1970 British Cohort Study

Anxiety

UK

1970–2004

Not included

Not included

Employment outcomes, income

Smith 2010

N = 433

Ages 12–17 years

Panel Study on Income Dynamics persons with depression

US

2003

Not included

Not included

Income, education

Fletcher 2008

N = 13,000

National Longitudinal Study of Adolescent Health (Add Health) Grades 7–12

Depression

US

Not included

Not included

High school dropout, college enrollment

ADHD

Brook 2013

N = 551

Epidemiologic sample in NY

US

1975–2006

Not included

Not included

Impaired work performance in adulthood

Chorozoglou 2015

N = 177

Epidemiologic study

UK

1989–2014

Psychiatric services, drug treatment

Family cost

Not included

Currie 2006

N = 4000/N = 2200

Population studies of youth in United States and Canada

US/Canada

1994–2000

Not included

Not included

Grade repetition, delinquent status, math score, reading score

D’Amico 2014

N = 83

Ages 9–16 years

Disruptive behavior diagnosis

Epidemiologic study, parent self-report data

UK

1993–2003

Health, mental health, Rx

Not included

Employment, absenteeism

Fletcher 2009

N = 13,000

National Longitudinal Study of Adolescent Health (Add Health) Grades 7–12

Depression

US

Not included

Criminal activity

Not included

Knapp 2011

N = 9071

1970 British Cohort Study

UK

1970–2004

Not included

Not included

Employment outcomes, income

Conduct Disorder

D’Amico 2014

N = 83

Ages 9 16 years

Disruptive behavior diagnosis

Epidemiologic study, parent self-report data

UK

1993–2003

Health, mental health, Rx

Not included

Employment, absenteeism

Knapp 2011

N = 9,071

1970 British Cohort Study

UK

1970–2004

Not included

Not included

Employment outcomes, income

Mental Health

Knapp, et al. 2015

N = 2,461

5–15 years at baseline

BCAMHS population survey

Mental health in general

UK

1999–2002

Health, mental health, education

Not included

Not included

Lucas 2013

N = 4,006

Longitudinal Study of Australian Children

Australia

2004–2008

Health, mental health, Rx

Not included

Not included

Rx = prescription.

Of the studies we identified, six studies reported some type of long-term direct cost. Three studies focusing on ADHD provided estimates of long-term health or mental health services. In a follow-up study of 3-year-old children living in the New Forest and Southampton regions in England, Chorozoglou and colleagues (2015) followed 170 children with ADHD and 88 control children without ADHD up to age 22 and collected a comprehensive service use profile. Youth and young adults who had ADHD at age 3 had significantly higher costs related to mental health, education, criminal justice, and family costs related to their MHNC. In addition, they estimated some direct costs to families, specifically the cost of property damage. Youth with ADHD had higher costs than those without. In a study of youth with ADHD or conduct disorder, D’Amico and colleagues (2014) used data from a population-based cohort of 6- to 7-year-old boys in London. Eighty-three of the original 120 boys were interviewed again between ages 25 and 30. They found that having high levels of childhood conduct problems led to a two- to three-fold increase in service costs in early adulthood.

Two large epidemiologic studies also reported on direct service use in young adulthood following nonspecific mental health issues in childhood. Using data from the BCAMHS, Knapp and colleagues (2015) reported on direct service use for youth 3 years following a baseline interview. They estimated costs for primary care, mental health, education, special education, and social services. They found that mental health symptoms significantly increased costs of mental health services in all models and special education and social services in some models. Using data from the Longitudinal Study of Australian Children, Lucas and colleagues (2013) also looked at service use for children with mental health concerns. They followed children for up to 3 years following baseline indication of mental health concern. They found significantly increased costs for the children who had indications of a mental health concern at an early age, with increased total healthcare costs. They also demonstrated that costs were greater if the child had experienced mental health difficulties at multiple follow-up points. We found no recent studies that estimated long-term direct costs for ASD.

Ten of the studies identified as reporting long-term economic consequences related to MHNCs reported some type of indirect cost related to MHNCs. Eight studies reported on employment outcomes. Two of the eight reported on employment outcomes related to ASD. Liptak and colleagues (Liptak, Kennedy, & Dosa, 2011) used data from the National Longitudinal Transition Study 2 (NLTS2), which followed children with ASD from 2000 to 2007; at baseline, the children were 13–16 years old. They found that children with ASD who had more trouble with communication and who had comorbid intellectual disability were much less likely to be employed at follow-up. Dillenburger and colleagues (Dillenburger, Jordan, McKerr, & Keenan, 2015), reporting on data from the Millennium Cohort study in the United Kingdom, found that adults who were identified as having ASD while children were much more likely to be unemployed compared to adults not identified as having ASD in childhood.

Focusing on depression, Fergusson and colleagues (Fergusson, Boden, & Horwood, 2007) reported on a birth cohort of children from New Zealand and found that frequency of depression episodes in youth (ages 16–21) significantly reduced the likeliness of being employed between 21 and 25 years old. Reporting on data from the 1970 British Cohort Study, Knapp and colleagues (Knapp, King, Healy, & Thomas, 2011) looked at the impact of several childhood MHNCs and reported that anxiety in childhood was not associated with employment status but was associated with lower earnings in adulthood. Antisocial conduct in childhood was associated with higher probability of unemployment, but if employed, employment was associated with higher earnings. ADHD in childhood was associated with lower employment rates, worse jobs, and lower earnings. In a community cohort study in New York, children with ADHD were identified in 1975 and followed through 2005–2006 (Brook, Brook, Zhang, Seltzer, & Finch, 2013). ADHD in childhood was associated with impaired work performance and high financial stress. Finally, D’Amico and colleagues (2014) followed children with ADHD or conduct disorder for 20 years but did not see significant impacts on employment.

(p. 157) In addition to the indirect impact of MHNCs on long-term employment outcomes, seven studies reported on the long-term education outcomes related to MHNCs. Dillenburger and colleagues (2015) reported that over 10-year follow-up, children with ASD were more likely to have a host of problems in school, including being expelled, or difficulties with peers in school. Liptak and colleagues (2011) found that communication problems and comorbid mental retardation in children with ASD were associated with lower likelihood of being in secondary education. Fergusson and colleagues (2007) reported that frequency of depression episodes in adolescence was negatively associated with getting a college degree or any type of secondary education qualification. Using data from the National Longitudinal Study of Adolescent Health (Add Health), Fletcher (2008) reported that depression in adolescence was associated with several negative educational outcomes, including not graduating from high school and being less likely to enroll in college. However, he found this effect only for females. Smith and Smith (2010) used data from the Panel Study of Income Dynamics and found that depression and other psychological problems reduced the years of schooling completed compared to those without these problems. Using data from longitudinal population studies of youth in the United States and Canada, Currie and Stabile (2006) found that ADHD in childhood was associated with multiple poor school outcomes, including grade repetition and lower math and reading scores, but some effects were only significant for boys.

In addition to the costs experienced by children and families, long-term studies provided important information on costs to other groups or sectors. Previous studies (Foster et al., 2005; Knapp, McCrone, Fombonne, Beecham, & Wostear, 2002) suggested that children with conduct disorder or ADHD had increased use of social welfare and criminal justice services in adulthood. Using data from the Add Health study, Fletcher and Wolfe (2009) estimated the impact of childhood ADHD on criminal activity 6 years later. They looked at multiple measures of criminal activity, including committing burglary or robbery, selling drugs, and being arrested/convicted. They found that ADHD was associated with increased risk of all types of criminal activity except robbery. They also calculated potential costs related to the crimes, including legal costs and victim costs.

Aside from criminal activity, no studies have looked at costs in other sectors. Most notably, no recent studies have looked at long-term costs to families. Yet, it is likely that if young adults who had MHNCs as children continue to struggle that there are likely to be significant impacts on families. This might include loss of productivity for parents or siblings due to helping to manage or care for the young adult with a MHNC.

Economic Evaluation

These long-term studies suggested that there is potential to reduce long-term costs if the effects of MHNCs in childhood could be reduced or eliminated. However, they did not provide guidance regarding which strategies may improve MHNC outcomes, and investments in prevention and treatment of MHNCs can require significant short-term cost, so understanding the impact of these investments is crucial. Returning to the conceptual model (Figure 11.1), note the middle panel representing short-term outcomes includes an oval indicating appropriateness, amount, and quality of services. These aspects of service are what underlies its potential to help reduce or better manage symptoms or behaviors of MHNCs. The service needs to be appropriate to the child’s needs, the child needs to receive a sufficient amount of the service, and the service needs to be of a high enough quality that it can be effective. If a service is inappropriate, is not of adequate duration, or is of poor quality, the child’s symptoms may not improve or could worsen.

Thankfully, there are growing number of interventions that can improve MHNC symptoms and behaviors in children (see http://effectivechildtherapy.org; see also chapters in this volume). But, given the scarcity of resources in virtually all service systems, we need to consider whether specific programs or policies are worth the investment. Economic evaluations can help to identify whether new programs or policies could improve short- and long-term costs. The literature on economic evaluation of MHNCs is large, and it is beyond the scope of this chapter to review the literature on economic evaluations of all prevention and treatments for MHNC. Several reviews provide detailed information on many such analyses (Beecham, 2014; Kilian, Losert, McDaid, Park, & Knapp, 2010; Mihalopolous & Chatterton, 2015; Romeo, Byford, & Knapp, 2005). Rather, this section briefly discusses what economic evaluation is and provides examples of economic evaluation that have informed the question of short- and long-term costs for MHNCs.

(p. 158) There are several different types of economic evaluation; they are defined in Table 11.1 and were described in more detail in previous reviews (see Beecham, 2014; Romeo et al., 2005). Although the different types of economic evaluation are not equivalent in all ways, they all have similar goals: to aid in decision-making about a service or policy. Full economic evaluations, which include cost–benefit analysis, cost-effectiveness analysis, and cost–utility analysis, all aim to provide information on the relative benefits, costs, and value of one intervention compared to an alternative or alternatives. Often, this is comparing a new program to “usual care,” which should be defined as the best standard of care available for the condition being targeted.

One example of such an analysis was reported by Bonin and colleagues (Bonin, Stevens, Beecham, Byford, & Parsonage, 2011). They used a decision-analytic economic evaluation method and compared an evidence-based parenting program with usual care. They reported that the parenting intervention would cost about $3,096 (2016 US$) per child. So, short-term costs could be substantial if this was offered to a large at-risk group. However, they also estimated that long-term cost savings to society would be about $24,488 (2016 US$) per family over 25 years.

Another example is from a study that used a different economic evaluation approach, conducting a cost-effectiveness analysis alongside a clinical trial for childhood anxiety. In this study, Bodden and colleagues (Bodden, Dirksen, Bogels, Nauta, et al., 2008) compared individual cognitive behavioral therapy (CBT) to family CBT. They found that the incremental cost of individual CBT was less than that of family CBT and was also more effective. However, this study only collected data through 15 months after the intervention, so it could not demonstrate cost savings in the long term. This is a common occurrence because clinical trials often have relatively short time frames. Despite this, they can still provide important information about the relative value of investing in different interventions in the short term.

Conclusions

Understanding the costs associated with MHNCs in childhood is important to guide policy and to help to allocate scarce resources as well as possible. Economic pressures to reduce public service costs continue to be a challenge for policymakers and service providers in the United States and many other countries. This scarcity has increased the need to demonstrate the value of services and to carefully evaluate investments in new programs and services. This review suggested several key conclusions regarding cost studies. It is critical to consider costs from a broad point of view on several levels. Costs can accrue to a variety of stakeholder groups; healthcare costs are only one portion of the cost associated with MHNCs, and consideration of other service sectors, especially education, is important. Families play an important role in the management of any MHNC and to understand the value of improvements in care for MHNCs, one needs to include costs to families. It is also important to take a long view regarding costs. While a strong understanding of short-term costs is necessary to make decisions within a limited budget, short-term investments have long-term cost implications, and acknowledging this can help to make sure that resources are used optimally.

There is a growing body of literature on the costs and cost-effectiveness of services for MHNCs (Beecham, 2014; Kilian et al., 2010; Knapp & Evans-Lacko, 2015; Mihalopolous & Chatterton, 2015; Romeo et al., 2005). However, there are a number of gaps in the literature. There is much more cost information on some MHNCs compared to others. In particular, there is a good amount of cost data on both the short- and long-term costs of ADHD and a number of cost-effectiveness analyses for this MHNC. Likewise, there is quite a bit of data on the short-term costs of ASD, but fewer studies regarding long-term costs or cost-effectiveness of alternative treatments for ASD. And, unfortunately, although depression and anxiety are very common in youth, there are very few studies that estimated the short-term costs of these MHNCs or the cost-effectiveness of services for these conditions. Finally, there is uneven information on different categories of cost. There are substantial data on healthcare costs, but much fewer on costs of education or other service systems or costs to families. Improved methods for estimating nonhealth system costs could greatly aid in understanding the full picture of costs for children with MHNCs and the best strategies to help reduce the burden of these conditions.

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