With the release of the 2019 Home Visiting Yearbook, the National Home Visiting Resource Center (NHVRC) has now published four rounds of home visiting data, including service information from 2015 to 2018. The efforts of NHVRC and many other initiatives rely on good data to tell the story of home visiting and how it works for families.
There is a large push in home visiting to find ways to increase data alignment, quality, and capacity. Before the NHVRC began, Pew Charitable Trusts led one of the first national efforts to identify and pilot test common home visiting performance indicators. Federal interest in performance measurement has been a constant in the Maternal, Infant, and Early Childhood Home Visiting (MIECHV) Program as states collect and annually report on demographic information and across key performance indicators. Recently, the Health Resources and Services Administration (HRSA) held regional listening sessions on data exchange standards and funded a separate project to promote data sharing and alignment across models. These are just a few examples of how the field is facilitating conversations about data and how they can be used to inform practice and policy.
Here at the NHVRC, we are also engaged in efforts to improve data quality internally and to share information to help the field tell the home visiting story through data. This year we had a chance to reflect on 4 years’ worth of home visiting data in a way never before possible. We discovered some variation in the number of families served over time. For example, between 2016 and 2017, there was a 1 percent increase in families served. However, there was a 6 percent decrease in families served between 2017 and 2018.
Given the research showing home visiting is effective, we would hope to see an increase over time in the number of families served by home visiting as more families gain access to these beneficial services. This blog post highlights some common reasons data might vary over time and the importance of continuing to improve data capacity and reporting.
Natural Variation in Data
There are many natural reasons why service numbers could vary. Potential reasons for data variation include—
- Changes in local implementing agencies (LIA). For example, a newly funded LIA might add participants, whereas LIA closures might decrease families served. There were 400+ fewer LIAs providing services across models in 2018 than in 2017, which may contribute to the decrease in service numbers seen in this yearbook.
- Better retention of families. Better retention may mean that LIAs are retaining families for longer, providing those families with more home visits but ultimately serving fewer families overall.
- Challenges of flat funding. It is difficult or even impossible in some cases to serve the same number of families with the same funding over time. Increases in operating costs must be absorbed (e.g., salary increases), which could potentially mean reductions in service.
- Workforce turnover. While looking specifically at MIECHV data, HRSA has noted staffing reductions or turnover could reduce the number of participants home visiting programs are able to serve. These types of issues are not unique to MIECHV sites but could apply across many home visiting models.
- Increased emphasis on data quality and capacity across models, states, and LIAs. Any look at data is likely to reveal some changes or areas for improvement in data quality. For example, when data collection for the 2017 Home Visiting Yearbook began, several models did not systematically collect or compile data across all their programs. The number of models who now collect data across their programs has increased, potentially leading to better data collection practices and reporting. While working with models during data collection, we also learned many were reviewing their internal data systems. At least one model took an internal look at operationalizing who “counts” or is most appropriate to include when reporting data. This meant reporting service numbers from fewer LIAs than in previous years so they could include only LIAs implementing the full range of intended services. Reporting on fewer LIAs for this model alone resulted in a notable drop in the number of families reported.
Implications
When NHVRC began, there was no systematic count of who was being served by home visiting across models and funding streams. With the support of models, states, and other stakeholders, we’ve made great progress in capturing how many families are reached by this valuable service.
Data will always vary in some natural ways, and that is normal and expected. While we look to understand this variation in data, we can hope for increases in the reach of home visiting. We must also look internally to ensure we are collecting good data to inform practice and policy.
Recent initiatives around data capacity underscore how the field of home visiting is working toward a goal of data alignment and increased capacity. In conjunction with these efforts, we can also begin to understand what these variations in data might mean, when they are due to typical fluctuation, and when there might be larger issues at play. We’re happy to be part of a larger network of home visiting partners working toward increased data capacity and look forward to keeping this conversation going.