An Introduction to Data Frameworks
Dynamics driving health and well-being are complex. In the field of public health and more broadly among those working to advance equitable well-being, frameworks—a basic structure underlying a system, concept, or text—are a powerful tool that aid in understanding and sense-making.
Frameworks provide conceptual infrastructure and help us understand the complex nature of health and well-being. “Framing” is a way of structuring or presenting a problem or an issue; it involves explaining, describing, and adding context. For example, the Social Determinants of Health is a commonly-used framework that acknowledges that the conditions in which we live, work, learn, and play impact our physical and mental health. The Seven Vital Conditions for Well-Being is a similar framework that focuses attention on a small but comprehensive set of conditions that all people depend on to reach their full potential for health and well-being. A framework provides a holistic view and approach to community change work, and prompts users to consider relevant upstream factors they might not otherwise. Importantly, frameworks are not mutually exclusive—in fact, using multiple frameworks offers a way to explore an issue from different perspectives.
How Data Frameworks Can Help You Better-Understand Conditions and Take Action in Your Community
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What are Data Frameworks?
Frameworks can be applied to quantitative data to help us more effectively use data to inform our work. Data frameworks are arranged into a simple series of “domains” (or categories) that categorize a set of indicators that measure community health and well-being. This powerful way of framing data describing a community of focus helps us account for local conditions instead of generalizing or making assumptions about what is needed. But, it’s not always clear what data to examine. Even after you collate relevant data, it can be difficult to identify key takeaways and develop a data-driven action plan. Data frameworks offer evidence-based, predetermined categories and indicators, so you can quickly explore data, make sense of it, and identify where to focus efforts.
When exploring data by frameworks, you can see how a given community fairs across domains to identify broad areas of focus, and dig deeper into the data to explore the indicators nested within each domain. Returning to our example, the Vital Conditions for Well-Being framework consists of seven domains—seven conditions every person needs to be healthy and well—each of which is populated by a series of indicators. One of these domains is humane housing, which measures factors providing safe, stable places to live, and establishment of vibrant, diverse communities, and neighborhoods safe from hazards. Indicators that populate the humane housing domain include: homeownership, housing affordability, and residential segregation, among others.
Below, you can see all of the indicators nested within the Humane Housing domain through a screenshot from IP3 ASSESS, IP3’s web-based data solution to community assessment, where data outputs are organized by frameworks. (IP3 ASSESS computes scores for both individual indicators and composite scores for each domain in a framework, allowing apples-to-apples comparison of data).
Use the dropdown menu at the top of the below screen and select the county you live in to explore humane housing data in your community!
Thinking about housing more broadly helps us consider that housing is the biggest expense for most Americans, and humane housing reduces toxic stress and increases the well-being of children and families. Data frameworks provide a powerful tool to “connect the (community assessment) dots”; from examining data, to prioritizing areas for investment, to developing an implementation plan.
A Vital Condition to Well-Being: Humane Housing: Exploring how stable housing promotes better health
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Bringing the Vital Conditions to Life: Humane Housing
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How Data Frameworks Advance Collective Action and Shared Stewardship
Data frameworks make using data in community-change work more intuitive by translating data into a solution. When applied to data, frameworks add context that helps interpret data and meaningfully quantify health outcomes and costs. Frameworks include categories that reflect common community programming and organizational structures, such as transportation, housing, and urgent services—where the work actually happens in communities. Putting data in a context that is aligned with existing organizations, local government, programming, and policy, allows changemakers to view data in a “real world” way and ultimately, move more quickly into action.
Furthermore, data frameworks make it easier to engage a diverse group of stakeholders, and for multi-sector groups to collaborate to go from community insight to collective action. They enable users to explore many measures simultaneously without creating confusion and prevent unnecessary conflict over measure selection. Frameworks can provide shared language, build consensus around familiar conditions and values, reveal how many factors work together as a system to create (or limit) community well-being, and demonstrate where stewards can and should focus investment efforts for maximum impact.
How Data Frameworks Can Help You Better-Understand Conditions and Take Action in Your Community
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Data Frameworks and Equity Considerations
Data frameworks help us take a holistic approach to community well-being by prompting us to consider myriad categories and conditions that impact our physical and mental health. These conditions are affected and shaped by the distribution of resources, money, and power at global, national, and local levels. Inequities are created when societal barriers prevent groups and individuals from reaching their full potential to be healthy and well. An increase in health equity is demonstrated in data through decreased disparities. Equity-focused frameworks help us identify, measure, and address disparities to aid our most vulnerable and advance equitable well-being instead of just looking at population measures. Established frameworks can also be adapted through qualitative research to better-serve target populations, like rural communities, communities of color, or other marginalized groups.
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Data Frameworks in Practice
Using multiple frameworks provides more insight and nuance, and advances an equitable approach by enabling stakeholders to enter into community change work from multiple frames. For the last several years, IP3 (stewards of Community Commons) has worked with multiple networks focused on improving community conditions related to opioid and substance use disorder and associated impacts. Using IP3’s Opioid and Substance Use Framework alongside the Vital Conditions for Well-Being Framework, we are better able to understand how community conditions give shape to and are shaped by opioid and substance use. For example, in our work with a rural health network we learned about how poor transit access leads to worse outcomes for drug court participants, which led to a focus on ensuring reliable transportation. Similarly, there is an association between economic opportunity and opioid and substance use. By using the two aforementioned frameworks, we are better able to prioritize efforts for ensuring meaningful work and wealth.
Sloan Gingg, MPH (she/her) is the Director of Communications and Strategic Outreach at IP3, and a contributing editor at Community Commons.
