Four Key Conditions for Linking Data Across Organizations

a Gardner Perspective by Hadar Baharav

A multitude of agencies across a variety of systems serve youth and families. Often, these agencies collect at least some data about their clients including demographics, program participation, and program outcomes. Analyzing available data presents agencies and systems with an important opportunity to better understand the settings they work in.

This opportunity is especially significant when practitioners link rich program data across their individual agencies. This enables them to develop shared insights based on their collective data. For example, they might better understand patterns of participation and gaps in services in their community. Ultimately, they can use this information to improve programming and policies and better serve families and youth.

While working on a recent research partnership, I had the occasion to reflect on the fundamentals of cross-agency data linking. The partnership joined the Gardner Center, First 5 San Mateo County, and the Bella Vista Foundation around a research agenda. Our goal was to gather, link, and analyze data across the many agencies that serve low income families with young children in San Mateo County. We found that there were four key conditions to successfully link individual-level data across many organizations. These include coalescing around a shared vision, ensuring organizational capacity, coping with data constraints, and collecting quality data.

Coalescing Around a Shared Vision

Bringing agencies together as partners around an agreed-upon vision for research is fundamental. Given that agencies serving the same population oftentimes operate under different missions, goals, and constraints, it can be extremely difficult to for partners to coalesce around a shared vision. An existing system, network, or collaborative could be a great starting point. In the absence of an existing network, a strong champion, like a representative of the County Board of Supervisors or the County’s Health System, could have a meaningful impact on forming a research agenda. Beyond that, engaging key partners in the early stages of a project can:

  • make research more relevant for agencies as there is still time to translate their interests into research questions;
  • increase project feasibility by considering constraints upfront; and,
  • enhance trust and buy-in among stakeholders.

Ensuring Organizational Capacity

Agencies that provide direct services to youth and families operate under many competing demands. Resources and time are often scarce, and staff are stretched thin. Further, agencies work with multiple databases to meet many funders’ requirements. Even extracting data can take considerable effort. In our project, an agency reported using more than 20 data sets! As such, an agency must prioritize the work and set aside enough resources for staff to take part. Agencies need outside funding to make resources available, especially in the nonprofit field. I cannot overstate how important it is for funders to support agencies to participate in research projects.

Coping with Data Constraints

Concerns about sharing client data are to be expected. However, as we learned through our experience on this project, such concerns intensify when data covers health-related services such as developmental assessments or those related to mental health. Furthermore, agencies serving undocumented immigrants are likely to express greater protection of their client data, especially when the political landscape suggests that the safety of undocumented immigrants must not be taken for granted.

In our project, despite the fact that the data were secured, used only for research purposes, and only reported at the aggregate level, multiple agencies were worried about linking data without their clients’ consent. In some cases, agencies made explicit promises not to share information without their clients’ permission. Obtaining client consent might not be practical, especially when historical data are sought and when the agency serves many clients. In addition, some agencies are unsure of who owns the data — the agency or a funder — and whether the agency has the authority to share.

Addressing data constraints, especially around the question of confidentiality and client consent, might be the hardest challenge to tackle. I suggest two strategies: making legal counsel available and signing data agreements about the use of the data for research purposes.

Collecting Quality Data

Having data of the quality necessary for meaningful analyses is another key condition. While some agencies collect detailed and identifiable data, others may collect only aggregate data — such as the total number of participants in a workshop — or thin data, like tracking program participation with no additional information about the frequency or length of involvement. As part of a research collaborative, partner agencies will become more knowledgeable about the power of data. They can then improve their data practices over time.

Our experience in research-practice partnerships has shown that building the data capacity of youth serving agencies is a good investment. It strengthens each organization’s capacity to use data to make decisions, form strategies, and evaluate their programming. Collaborating to increase data capacity and alleviate data constraints has benefits as well. Together, agencies can contribute data to solve community-wide problems in the future.

Hadar Baharav is a Senior Research Associate.