Lauren H. Supplee

Effectiveness of Home Visiting in Improving Child Health and Reducing Child Maltreatment

BACKGROUND AND OBJECTIVE: The Patient Protection and Affordable Care Act established the Maternal, Infant, and Early Childhood Home Visiting Program, which provides

Overview of the Federal Home Visiting Program

1.5 billion to states over 5 years for home visiting program models serving at-risk pregnant women and children from birth to age 5. The act stipulates that 75% of the funds must be used for programs with evidence of effectiveness based on rigorous evaluation research. Home Visiting Evidence of Effectiveness reviewed the home visiting research literature and provided an assessment of the evidence of effectiveness for program models that serve families with pregnant women and children from birth to age 5. METHODS: Home Visiting Evidence of Effectiveness included a systematic search and screening process, a review of the research quality, and an assessment of program effectiveness. Reviewers rated studies’ capacity to provide unbiased estimates of program impacts and determined whether a program met the Department of Health and Human Services’ criteria for an evidence-based model. RESULTS: As of July 2012, 32 models were reviewed, of which 12 met the Department of Health and Human Services criteria. Most of these models were shown to have favorable effects on child development. Other common favorable effects included health care usage and reductions in child maltreatment. Less common were favorable effects on birth outcomes. CONCLUSIONS: Home visiting is a promising way to serve families who may be difficult to engage in supportive services. Existing rigorous research indicates that home visiting has the potential for positive results among high-risk families, particularly on health care usage and child development.

Introduction to the Special Issue: Subgroup Analysis in Prevention and Intervention Research

On March 23, 2010, the President signed into law the Affordable Care Act (Public Law 111-148), which included an amendment of Title V of the Social Security Act authorizing the creation of the Maternal, Infant, and Early Childhood Home Visiting (MIECHV) program. Authorized and funded at

The Intersection Between Prevention Science and Evidence-Based Policy: How the SPR Evidence Standards Support Human Services Prevention Programs

1.5 billion for 5 years, the MIECHV represents a large investment in health and development outcomes for at-risk children through evidence-based home visiting programs. The MIECHV presents unprecedented opportunities to integrate early childhood services systems, not only on the federal level but also within states and local communities. The MIECHV is funded in escalating amounts over 5-year period authorized, as follows:

Opportunities and Challenges in Evidence-based Social Policy

100 million in fiscal year (FY) 2010,

Opportunities and Challenges in Evidence-based Social Policy and commentaries

250 million in FY 2011,

New Opportunities and Directions in Home Visiting Research and Evaluation.

350 million in FY 2012,

Erratum to: Introduction to the Special Issue: Subgroup Analysis in Prevention and Intervention Research

400 million in FY 2013, and

Maltreatment Effectiveness of Home Visiting in Improving Child Health and Reducing Child

400 million in FY 2014. Most of the funding is being provided to states and territories to provide home visiting services in their at-risk communities. In addition, the legislation included a 3% set-aside for tribes, tribal organizations, and urban Indian organizations and a 3% set-aside for research and evaluation. This investment has spurred the creation of more comprehensive and coordinated early childhood service systems across the United States. This article provides an overview of the MIECHV program, including descriptions of the various requirements under the Affordable Care Act. These include partnering with states to provide evidence-based home visiting services to at-risk families, working with tribal communities to implement culturally competent home visiting programs, and developing a mechanism to systematically review the evidence of effectiveness for home visiting program models and to conduct a national evaluation of the MIECHV program.

Introduction to the Special Section: The Application of Effect Sizes in Research on Children and Families

Prevention scientists, intervention developers, patients, providers, and clients are continually seeking more effective and efficient treatments for a wide range of social, behavioral, and public health problems. Across this range of problems, there is a common interest in developing a better understanding of impacts of interventions on specific subgroups. Among policymakers, an interest in the question “What works?” is now often accompanied by “What works for whom?” For example, the Obama administration has been emphasizing the use of rigorous research as part of evidence-based policy-making. In a 2009 memorandum to federal agencies and departments, the Office ofManagement and Budget emphasized both the importance of rigorous research on program effectiveness as well as evidence aimed at improving the life outcomes of individuals. In medicine and health policy, there has been a strong push toward comparative effectiveness research; the purpose of which is “to inform patients, providers, and decision-makers, responding to their expressed needs about which interventions are most effective for which patients under specific circumstances” (Federal Coordinating Council for Comparative Effectiveness Research 2009, p 3). One implication of this emphasis on what works has been greater attention to the research and methodologies associated with specific populations and subgroups. The analysis of subgroups can matter a great deal in prevention science and intervention research. First, many prevention scientists use subgroup findings to unpack significant main effects or to investigate why there was a lack of significant main effects. Prevention scientists frequently want to explore whether a program was more or less effective for a segment of the target population and why it may have been less effective for another subgroup. Rothwell (2005) argues that the importance of subgroup analysis is not in differential response to treatment, but in identifying how to maximize benefits from treatments and mitigate risk. Rothman (2012) highlights that moderated effects can help prevention scientists to refine theory, tailor prevention to specific contexts or to the needs of specific populations, or target intervention. Policy-relevant research around prevention and intervention science is regularly challenged to answer the question of what works for whom. Subgroup analysis can be seen to be directly linked to policy decisions around programmatic aims (e.g., Upward Bound), funding decisions (e.g., Even Start), and new initiatives targeting funding towards evidence-based programs (e.g., teen pregnancy and home visitation). Subgroup analysis, broadly, aims to measure change within and between groups. Subgroups are defined by characteristics measured at baseline. Subgroups can be characterized by variables that are easier to define, such as age, to those less well-defined, such as risk status. Subgroups can be continuous or categorical; variables with low, moderate, or high measurement error; and variables that are measured, latent, or estimated based on response to treatment. Subgroups can include individual characteristics or site-level variables. Subgroups may occur with more regularity in a population, such as gender, more infrequently such as families with multiple risk factors, or more difficult to represent in large numbers in prevention trials such as rural communities. Work by Rothwell (2005) and Wang et al. (2007) highlighted the issues with subgroup analysis within medical research. Rothwell (2005) specified best practices in study design, L. H. Supplee (*) : B. C. Kelly Office of Planning, Research and Evaluation, Administration for Children and Families, 370 L’Enfant Promenade SW, 7th Fl West, Washington, DC 20447, USA e-mail: lauren.supplee@acf.hhs.gov