Introduction

Local, state and national data systems contain data about individuals and services delivered to families receiving home visiting. These data can provide valuable information about program effectiveness and family well-being. However, there are significant barriers to fully utilizing this data due to a lack of common definitions in the field and data sharing considerations.

Data Sharing and Interoperability

An specific to home visiting provides the necessary framework and definitions to advance home visiting research. Developing a home visiting ontology will allow researchers to combine existing data more easily across models, states, territories, tribal entities, and localities. This will provide large sample sizes of families and programs providing enough power for multi-level modeling and other multi-variable analytic techniques. Further, the ontology can help index research papers and results using to speed the process of systematic reviews and increase knowledge about a particular home visiting concept or intervention using information gathered across many studies.

In , an ontology is an organizing framework made up of three layers: knowledge, information, and data. Knowledge or the upper layer, provides a high-level view of key concepts relevant to home visiting and their relationships to each other. The information layer explains how concepts from the knowledge layer are defined and connects those concepts from the knowledge layer with the data layer. The data layer specifies how data are defined, organized, and stored in databases. Modern solutions (e.g., National Information Exchange Model) are driven by the information layer which allows researchers to store data in-house, while allowing for data sharing and collaboration across centers. Often the emphasis is on sharing at the data layer, however the field can benefit from sharing at the information (e.g., surveys, screenings) and knowledge (e.g., publications) layers.

As an example, we cannot adequately study the intricacies of family engagement without a standard operational definition across the many home visiting models. Once we have a definition of family engagement, the information layer can be used as a tool to identify gaps between what data is needed to answer research questions of interest and the data currently available in home visiting models’ management information systems (MIS). It may be that the data needed to answer some of the questions around family engagement are not available within existing MIS. This finding may inform opportunities for modifications in data collection. Changes to MIS systems could be tested with small-scale projects that are low burden but high impact.

HARC plans to use the ontology layers to conceptualize common definitions, promote data sharing between agencies at all levels, and use linked data sets to produce high-quality home visiting research. Data linkage between models of home visiting, across states, and among state agencies will more fully encompass family’s’ experience and strengthen generalizability of findings across the field.   


For More Information

A Scoping Review of Home Visiting Research Using Linked Data

HARC recently conducted a scoping review of published, peer-reviewed research using early childhood home visiting (HV) data linked with other administrative datasets to identify data sources, methods for linkage, study designs, research questions, and outcome categories in the literature. Collectively, the included articles demonstrate the value of linking data to answer research questions that cannot be readily answered with home visiting program data alone; they also highlight gaps and opportunities for research questions, study designs, data linkage work, and partner and community engagement.
A Scoping Review of Home Visiting Research Using Linked Data

Resource List to Support Data Sharing for Collaborative Home Visiting Research

Researchers from the HARC team reviewed resources related to sharing home visiting data and compiled a list of resources that can support this work. The brief includes resources that are relevant to home visiting program administrators and data leads who are interested in sharing data with other administrative data sources, especially other early childhood programs. Resources are organized by stages of data management to inform each stage of the process and linked to make resources easily accessible as different needs arise. This work is intended to support the advancement of precision research and program evaluation of home visiting programs.
Resource List to Support Data Sharing for Collaborative Home Visiting Research
An ontology is a framework for organizing and defining concepts and how they are related to one another.
Machine learning is the process by which a computer is able to improve its own performance using algorithms that continuously incorporate new data to create a model that can be used to describe, predict, or prescribe actions.
Informatics is the science of processing data for storage and retrieval; information science.
Interoperability is the ability of a system to communicate with another system without human intervention.

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