The common thread is that we want to make things better in the places that we live, and are committed to using the best and most appropriate tools for getting there.
Our work falls into a few categories: Research, Evaluation, and Technology development.
Pathways to Population Health
With ASTHO and WE in the World, we are adapting a tool + system for public health leaders to examine the direction and balance of the population health activities to specifically improve equity.
Bouncing back from COVID takes collaboration and coordination between thousands of community-based partners and governmental agencies. We work to curate and report back data from these communities so stakeholders can understand what they need to address to work toward health and equity.
Communities RISE is driven by a partnership of diverse, trusted organizations with deep roots via 2400+ BIPOC and older adult connected local organizations within communities who are working to build public health trust, civic capacity and system change in the context of COVID-19.
Within this initiative, we are leading a complex formative summative evaluation on how communities can address vaccine hesitancy while building their infrastructure to address disparities within their communities. This nationwide work involves coordinating different models of change and different stages of readiness to help teams grow and successfully meet their goals.
Coordination and Implementation partners include:
The Rhode to Equity
We are helping the great state of Rhode Island examine how they provide population health services with an equity lens.
By working with the visionary team at WE in the World, convened by Dr. Soma Saha, we get to help build capacity for health equity-infused activities on the population level. This builds off of early work developing “maps” that specific different” amounts of capacities to both inform and guide future planning.
Analyzing RFP applications with Natural Language Processing
So much data is qualitative. But qualitative data is really tough to analyze in community-based projects. As a consequence, people tend to avoid it, or just pick relevant quotes out at random.
Together with Dr. Victoria Scott at the University of North Carolina: Charlotte, we are looking at whether there are textual indicators that predict which way funding decisions go. This is a broad mandate, and we have many different methods and approaches to take: from simple bag-of-words approaches to more nuanced long short-term memory recurrent neural networks.
The New Jersey Health Initiative’s Small but Mighty Data Collaboration
Oftentimes, it can be difficult to even start a community-based collaboration and improvement project. People might not know where to get data, how to interpret it, or how to act on it. That’s where this novel project comes in. Rather than make decisions based on RFPs, the team out of NJHI looks to work aside communities is South Jersey through the whole of the project; from concept, to application, to implementation, to evaluation.
We’re working to enhance the storytelling aspect. How can we help put conditions into place so communities can disseminate their work in a way that has an impact? This includes more partners, more funding, and more ideas.
Together with friends and colleagues at Virginia Tech and the American Institutes for Research, we are studying how readiness at multiple levels (individual, school, community) and across multiple roles (student, teacher, parent, administrator) impacts attitudes and beliefs about school safety. To do this, we have collected a lot of pre-COVID data that we have begun to work through.
One particular area is how we can extract readiness from text-based data. This could be done with a bag of words approach, but we are also using word vectorization method to look for semantic relationships between our big areas of interest.
Here’s a video made by the AIR folks on the project.
School and Community Readiness in Colorado
For the past four years, we have been investigating school and coalition-level readiness. Recently, we have begun consolidating that data to explore the appropriateness of modifying readiness assessment and how readiness clusters together within a network.