Methodology

The 2020 Home Visiting Yearbook combines 2019 data from various sources to describe—

• Home visiting in each state through evidence-based model data
• The federal contribution to home visiting through MIECHV administrative data
• Home visiting provided nationally by emerging models through model-provided data
• Who could potentially benefit from home visiting through data from the American Community Survey (ACS)

Model and MIECHV Data

Data Collection Updates

Since the release of our inaugural yearbook in July 2017, the NHVRC has continued to streamline our data collection process, engage with models, and expand data collection to share counts of home visits and of children and families served. For the 2020 Yearbook, we included a new model—Maternal Infant Health Program (MIHP)—that was reviewed and designated as evidence based by the Home Visiting Evidence of Effectiveness (HomVEE) project. Of the 16 evidence-based models operating in 2019 in the United States, 15 shared some data with us.

We also continued to expand data collection of emerging models that have demonstrated a contribution to home visiting but have not received a designation of evidence based after HomVEE review. These models are referred to throughout the 2020 Yearbook as emerging models. Nine out of 10 emerging models responded to our request for data, including a new emerging model, Early Steps to School Success (ESSS). Recognizing that this list is not comprehensive, we did not combine data from emerging models with data from the evidence-based models in the 2020 Yearbook. Rather, we compiled data from nine emerging models and presented them separately. See the “Emerging Models Identification and Recruitment” section of this appendix for more information on how we selected these models.

Sample and Recruitment

The team collected data from various stakeholders to capture comprehensive information about home visiting at the local, state, and national levels. As with past yearbooks, we reached out to all evidence-based models operating in the United States in 2019 and state MIECHV agencies, and worked with the Administration for Children and Families to gather data on Tribal MIECHV programs. The team received data from—

• State and territory MIECHV agencies (53 of 56)
• Evidence-based models (15 of 16) (Source: Models represented in the evidence-based numbers include Attachment and Biobehavioral Catch-Up (ABC), Child First, Early Head Start Home-Based Option (EHS), Family Connects, Family Spirit, Health Access Nurturing Development Services (HANDS), Healthy Families America (HFA), Home Instruction for Parents of Preschool Youngsters (HIPPY), Maternal Early Childhood Sustained Home-Visiting (MECSH), Maternal Infant Health Program (MIHP), Minding the Baby, Nurse-Family Partnership (NFP), Parents as Teachers (PAT), Play and Learning Strategies (PALS), and SafeCare Augmented.)^{Go to footnote #>1}
• Emerging models (9 of 10) (Source: Models represented in the emerging models numbers include Baby TALK, Early Steps to School Success (ESSS), HealthConnect One’s Community-Based Doula Program, Maternal Infant Health Outreach Worker Program (MIHOW), Nurses for Newborns, Parent-Child Assistance Program (PCAP), ParentChild+, Team for Infants Exposed to Substance abuse (TIES) Program, and Welcome Baby.)^{Go to footnote #>2}
• National Tribal MIECHV program (1 of 1)

Model Administrative Data

We contacted each of the 16 home visiting models operating in the United States in 2019 that met HomVEE criteria for evidence of effectiveness at that time: Attachment and Biobehavioral Catch-Up (ABC), Child First, Early Head Start Home-Based Option (EHS), Family Check-Up (FCU), Family Connects, Family Spirit, Health Access Nurturing Development Services  (HANDS), Healthy Families America (HFA), Home Instruction for Parents of Preschool Youngsters (HIPPY), Maternal Early Childhood Sustained Home-Visiting (MECSH), Maternal Infant Health Program (MIHP), Minding the Baby, Nurse-Family Partnership (NFP), Parents as Teachers (PAT), Play and Learning Strategies (PALS), and SafeCare Augmented. The 2020 Yearbook contains model profiles for two other evidence-based models operating internationally (Early Start in New Zealand and Healthy Beginnings in Australia) but does not include their service numbers in the data presented.

The team sent emails inviting each model to share data on the characteristics of participants served in 2019 and a list of the local agencies that served them. To the extent possible, we requested that participant demographic data mirror MIECHV administrative data required for federal reporting, so we could align model data with data shared by state and tribal MIECHV agencies.

The full data request included the following variables:

Local agency characteristics

• Agency names and addresses
• Geographic service areas
• Total number of full-time equivalent (FTE) home visitors implementing the model at the end of the reporting year
• Total number of FTE supervisors implementing the model at the end of the reporting year

Participant characteristics

• Total number of children served
• Total number of families/households served
• Total number of home visits completed
• Caregiver ethnicity
• Caregiver race
• Caregiver educational attainment
• Child age
• Caregiver age
• Child insurance status
• Primary language exposure of child
• Low-income status

Not all models were able to provide data for each variable, but we accepted the data that these models had available. The following number of models shared administrative data:

• Fifteen models shared local agency information: ABC, Child First, EHS, FCU, Family Connects, Family Spirit, HANDS, HFA, HIPPY, MIHP, Minding the Baby, NFP, PAT, PALS, and SafeCare Augmented.
  • Ten models shared participant zip codes: Child First, Family Connects, HANDS, HFA, HIPPY, MECSH, MIHP, Minding the Baby, NFP, and PAT.
  • Fifty-three state MIECHV grantees shared Form 4 data. Zip codes were collected from Table A.2: Place-Based Services.
• Fourteen models shared service numbers: ABC, Child First, EHS, Family Connects, Family Spirit, HANDS, HFA, HIPPY, MIHP, Minding the Baby, NFP, PALS, PAT, and SafeCare Augmented.
  • Twelve of the models provided data on the number of home visits completed: ABC, Child First, Family Connects, Family Spirit, HANDS, HFA, HIPPY, MIHP, Minding the Baby, NFP, PALS, and PAT.
  • Thirteen of the models provided data on the number of families served: ABC, Child First, Family Connects, Family Spirit, HANDS, HFA, HIPPY, MIHP, Minding the Baby, NFP, PALS, PAT, and SafeCare Augmented.
  • Twelve of the models provided data on the number of children served: ABC, Child First, EHS, Family Spirit, HANDS, HFA, HIPPY, MIHP, Minding the Baby, NFP, PALS, and PAT.
• Ten models shared participant data: Child First, EHS, HANDS, HFA, HIPPY, MIHP, Minding the Baby, NFP, PAT, and SafeCare Augmented.
  • Ethnicity includes data from Child First, EHS, HANDS, HFA, HIPPY, MIHP, Minding the Baby, NFP, PAT, and SafeCare Augmented. Child First, HANDS, HFA, HIPPY, MIHP, Minding the Baby, NFP, PAT, and SafeCare Augmented reported ethnicity for adult participants. EHS reported ethnicity for children and pregnant caregivers.
  • Race includes data from Child First, EHS, HANDS, HFA, HIPPY, MIHP, Minding the Baby, NFP, PAT, and SafeCare Augmented. Child First, HANDS, HFA, HIPPY, MIHP, Minding the Baby, NFP, PAT, and SafeCare Augmented reported race for adult participants. EHS reported race for children and pregnant caregivers.
  • Educational attainment includes data from Child First, EHS, HANDS, HFA, HIPPY, MIHP, Minding the Baby, NFP, and PAT.
  • Child age includes data from Child First, EHS, HANDS, HFA, HIPPY, MIHP, Minding the Baby, NFP, and PAT.
  • Child insurance status includes data from Child First, EHS, HANDS, HFA, HIPPY, MIHP, and NFP. Public insurance includes Medicaid, Children’s Health Insurance Program (CHIP), and TRICARE.
  • Primary language includes data from Child First, EHS, HFA, HIPPY, MIHP, NFP, and SafeCare Augmented. EHS reported primary language for children and pregnant women. SafeCare Augmented reported language of service delivery. Child First, HIPPY, and MIHP reported primary language of children. HFA and NFP reported primary language of adult participants.

Although models do not uniformly report data, the NVHRC team combined as much of the data we received as possible. These data represent the most comprehensive summary of home visiting services provided by evidence-based home visiting models across the nation. We aggregated data across models and then used the summarized data to create—

• The NHVRC National Profile featuring model data on service numbers and participant demographics
• NHVRC State Profiles featuring model data on service numbers and participant demographics by state and ACS data on potential beneficiaries by state
• NHVRC Model Profiles featuring model data on service numbers, participant demographics, survey information on model requirements, and geographic information on where models operate
• Two National Maps featuring model data on local implementing agency locations and model data combined with MIECHV data on participant geographic service areas

MIECHV Administrative Data

MIECHV legislation requires awardees to report data yearly to the federal government. These data include information such as the number of home visits conducted, number of participants served, and participant demographics. The team asked MIECHV agencies in each state to share a copy of this administrative data report. Most were able to share data, but a few were not.

The following number of agencies supplied MIECHV administrative data:

• State MIECHV agencies (53 of 56)
• National Tribal MIECHV program (1 of 1)

We used the state MIECHV administrative data reports to produce the MIECHV State Data Tables. The Health Resources and Services Administration provides states and territories with guidelines for defining demographic variables.

Emerging Model Identification and Recruitment

In 2018, we broadened our description of the home visiting landscape by expanding data collection to include emerging models. The following details our process for identifying which models to include in data collection for the 2018 Home Visiting Yearbook.

We started by creating a list of potential models to include. Models were included if they met one of the following criteria:

• Reviewed by HomVEE but had not yet reached HomVEE evidence-based status
• Being evaluated through MIECHV as a promising approach
• Recognized as evidence based in either the Substance Abuse and Mental Health Services Administration’s National Registry of Evidence-based Programs and Practices (NREPP) or the California Evidence Based Clearinghouse for Child Welfare (CEBC)

We brought this list to members of the Advisory Committee for their expert feedback and for suggestions of additional models. After receiving their feedback, which included Welcome Baby and First Born, we refined the list following the process below.

• We first removed models that were not operating in the United States or were no longer being implemented anywhere. This resulted in 23 models. Of these, 21 were listed by HomVEE, NREPP, or CEBC.
• We then reviewed the models to determine if they exclusively served prenatal women and children 0–5 years. This ensured we could have accurate counts of families with children in the target age group for early childhood home visiting. This step narrowed the list to 17 models.
• We then sent the list to the Advisory Committee for final review. This resulted in a final list of 13 models to contact.

We reached out to these 13 models, asking them to provide information on their model, service delivery information, and if available, participant demographics. For the 2018 Yearbook, nine models agreed to participate in data collection. In 2019, we again collected data from the models identified in 2018.

For the 2020 Yearbook, we replicated our expansion process to identify additional models eligible to be included in data collection. Of the three eligible models identified, one responded to our data collection request.

Emerging Model Data Collection

We contacted 10 emerging models asking them to provide information on their model, services delivery information, and if available, participant demographics: Baby TALK, Early Steps to School Success (ESSS), Following Baby Back Home, HealthConnect One’s Community-Based Doula Program, Maternal Infant Health Outreach Worker Program (MIHOW), Nurses for Newborns, Parent-Child Assistance Program (PCAP), ParentChild+, Team for Infants Exposed to Substance abuse (TIES) Program, and Welcome Baby.

The team sent emails inviting each model to share data on the characteristics of participants served in 2019.

• Nine models shared number of home visits completed, number of families served, and number of children served: Baby TALK, ESSS, HealthConnect One’s Community-Based Doula Program, MIHOW, Nurses for Newborns, PCAP, ParentChild+, TIES Program, and Welcome Baby.
• Eight models shared participant data: Baby TALK, ESSS, HealthConnect One’s Community-Based Doula Program, MIHOW, PCAP, ParentChild+, TIES Program, and Welcome Baby.

We aggregated data across models and then used the summarized data to create the—

• By Emerging Models section featuring model data on service numbers and participant demographics
• NHVRC Model Profiles featuring model data on service numbers, participant demographics, survey information on model requirements, and geographic information on where models operate

Surveys

Based on feedback, the NHVRC team dropped our request for state MIECHV agencies and models to complete a survey for the Home Visiting Yearbook. Some exceptions were made for—

• Models that did not complete the survey for a prior NHVRC publication
• Models that recently received an evidence-based designation from HomVEE
• Models operating internationally only

The survey covered content related to program, participant, and community characteristics; service capacity and enrollment; program implementation; and funding. Models were asked to share programmatic data, not individually identifiable information. All models had the opportunity to review their program information and to include updates before the release of the 2020 Home Visiting Yearbook. Survey data were used to develop the model profiles.

Data Analysis

We conducted a rigorous data cleaning and analysis procedure for all data sources. For the model data, we reviewed each model dataset to determine which data elements were available among those in our initial data request. We then examined all models to determine how to combine and report data uniformly across models for state and national profiles. We then cleaned the data to ensure all reported elements were complete. Next, we combined data across models using statistical analysis software. NHVRC staff double-entered state MIECHV administrative data to ensure accuracy before the software analysis.

To maintain the confidentiality of model and state data, we conducted cell suppression of race and ethnicity variable categories with 10 or fewer participants. These counts are replaced with an * in the data.

NHVRC data and communications teams verified the final profiles before they were presented to state and model staff for additional review. In coming years, we will continue to work with states and models to address unique data issues and questions as they arise while adhering to our systematic protocols.

Treatment of Missing Data

Missing and unknown data were not included in calculations of percentages of demographic data in the national and state profiles. Missing data were excluded in calculations of the following variables:

• Caregiver ethnicity
• Caregiver race
• Caregiver educational attainment
• Child age
• Caregiver age
• Child insurance status
• Primary language exposure of child
• Low-income status

For MIECHV State Data Tables, we also excluded Unknown/Did Not Report data in calculations of percentages of the following variables:

• Caregiver age
• Child age
• Primary language
• Child insurance status
• Caregiver ethnicity
• Household income
• Caregiver race
• Caregiver education

National Map Analyses

We produced two maps as part of this analysis, one to highlight counties where home visiting programs are located, and the other to assess the reach of service areas in each state and territory during 2019.

1. Counties With at Least One Local Agency Delivering Evidence-Based Home Visiting (2019). In this analysis, we identified all counties in the United States and its territories where there was at least one local implementing agency using an evidence-based model in 2019. We estimated county-level coverage using data from 15 evidence-based models on their program locations across the United States and its territories.
2. Percentage of Zip Codes in Which Families Receive Evidence-Based Home Visiting By State (2019). We estimated the percentage of zip codes served by evidence-based home visiting programs using data collected from 10 evidence-based model developers and from MIECHV Form 1 data. Our coverage estimates may be low because not all models reported service areas. On the other hand, the coverage estimates may be high because some models reported service area by county rather than zip code, and we made the simplifying assumption that models reporting county-level service areas served all zip codes in each reported county. Also note that we used population estimates from the 2018 American Community Survey to exclude zip codes with no population from the analysis to make cross-state comparisons more meaningful.

American Community Survey Data and Documentation

The 2020 Home Visiting Yearbook catalogs national- and state-level information on potential beneficiaries of home visiting using information from the ACS. We first define potential beneficiaries broadly. We then examine subgroups of families who might be a higher priority for services based on several targeting criteria. ACS data were analyzed for all 50 states and the District of Columbia, but not for territories or individual tribal communities.

Data Source

The team relied on the 2018 ACS 5-year (2014–2018) file, accessed through the Integrated Public Use Microdata Series (IPUMS). The ACS is a nationwide, ongoing survey designed to provide data on demographic, housing, social, and economic issues. IPUMS grants access to ACS microdata, where each record represents a person.

Potential Beneficiaries of Services

We define potential beneficiaries of home visiting services as families and subfamilies with pregnant women and/or children under 6. (Subfamilies are families that live in the household of someone else.) First, we estimate the number of families and subfamilies with children younger than 6 years old who are not yet enrolled in school (that is, not in kindergarten or a higher grade). To this estimate, we add an estimate of the number of families and subfamilies that include a pregnant woman and are not otherwise counted.

Estimates of pregnant women are based on adjusted counts of families with infants because the ACS does not identify pregnancy status. Specifically, we count the number of families with infants but no other children under age 7 in first grade or higher, as a proxy estimate of pregnant women without a child under age 6 not yet enrolled in kindergarten (assuming rough stability in the number of births from one year to the next). We multiply the number of families with infants by 0.75 to account for 9-month pregnancy. (Source: We do not attempt to refine the estimate to account for (1) fetal and infant deaths or (2) the lag in time before a woman’s pregnancy would be verified; the first adjustment would raise the estimate of pregnant women not already counted, while the second would lower it.)^{Go to footnote #>3}

Families With High Priority For Services

To identify a subpopulation of “high-priority families,” we count the number of families with young children and pregnant women who meet one of five different economic and demographic criteria (as defined below) and the number of families that meet at least two such criteria. We conferred with the Advisory Committee to select our targeting criteria. Although other criteria could also be considered, we chose these because they align with several of the priority areas from the MIECHV legislation, they align with several of the model requirements for enrollment, and they are available in the ACS.

Targeting Criteria

We estimate the number of families with preschool children under 6 and pregnant women who meet each of the following criteria at the national and state levels:

• Presence of an infant; that is, a child younger than 1 year old. By definition, none of the pregnant women without children under 6 meet this criterion.
• Low income, where family income is below 100 percent of the federal poverty threshold.
• Young mother or young pregnant woman. We define young as under 21 years old.
• Single mother, never married.
• Low parental education. We count the number of families in which the child’s parent(s) have not completed 12th grade. (Source: In two-parent households, we consider both parents’ educational levels; in one-parent households, we consider only that parent’s educational attainment. For pregnant women, we look at the education of the mother only.)^{Go to footnote #>4}