Research with the Dashboard: Q&A with Benjamin Spoer

Benjamin Spoer, Co-Director of Metrics and Analytics, leads many of the research efforts here at the Dashboard. We sat down with him to learn more about the Dashboard's involvement with research. Read more about what he had to say:

CHDB: As Co-Director of the Dashboard, what role does research play in the Dashboard’s goals?

BS: There are two types of research to think about, the research we do behind the scenes to calculate our metrics and to produce metrics for the unique geographies we cover like congressional districts or census tracts (neighborhoods), and the research we publish in peer reviewed journals. We extensively research the metrics you see on our websites, doing our best to ensure the numbers are calculated rigorously, are based on reliable data sources, and are meaningful to our users.

The research we publish often captures part of that metric development process, while also describing how our metrics are related to health outcomes. Publishing our work ensures that it meets the rigorous standard of peer review and helps us publicize our findings to researchers and other stakeholders. Finally, our hope is that policymakers read our research and are inspired to take action to address the health determinants and disparities we highlight in our published research.

CHDB: How does the Dashboard team decide what areas of research to pursue?

BS: We often draw inspiration from the metrics available on our website as well as topical public health issues or issues of importance to municipal leaders. An example is our COVID Local Risk Index (CLRI) validation paper. We knew it was vitally important that we add a COVID-related metric to the Dashboard in order to help cities respond to the COVID epidemic, which is why we added the CLRI metric to the Dashboard from June 2020 to July 2023. We later validated that metric in partnership with colleagues at the Urban Health Collaborative. This research demonstrated that the CLRI was a valid tool for evaluating COVID risk that city leaders could use to guide their resource and recovery strategy.

Another example is our broadband access paper, led by Senior Data Analyst, Yuruo Li. In 2021, we had just added broadband connection to the City Health Dashboard, and Congress had recently passed the Bipartisan Infrastructure Deal that included historic investments for broadband improvement. Our hope was that our paper might help steer the allocation of those broadband funds by identifying places that lack broadband access.

CHDB: Can you explain how the Dashboard can be used to support research efforts?

BS: The primary way the Dashboard websites can support research efforts is through our downloadable data and API. Both cities and congressional districts are fascinating political and demographic geographies, and encapsulate various social and structural factors that shape health. There are numerous important public health issues that could be interrogated using our data. The Congressional District, especially, is an under researched health-related geography and area of study.

Second, my team is always on the lookout for interesting research ideas and potential collaborations. We are happy to bring our deep expertise in these data to a potential research project. If you are interested in collaborating with us or have any ideas of your own, we’d love to hear from you!

CHDB: These past few months, there have been quite a few published notable research papers featuring both data from the Dashboard and the team’s own work. Most notably, your recent paper on the validation of geospatial aggregation methods used to create the Congressional District Health Dashboard has obtained some attention. Can you explain the importance of this piece of research?

BS: This paper is important because it attempts to validate the methods we used to calculate estimates for the Congressional District Health Dashboard. Most of the data for the City Health Dashboard existed before we launched the website, and our contribution has been in organizing, cleaning, and making accessible those data, particularly to smaller cities. In contrast, most of our data sources do not provide data at the congressional district level. We had to figure out how to reliably calculate metric estimates for congressional districts. The validation paper describes the method we used and demonstrates that, at least for the specific metrics we highlight in the paper, it can produce accurate estimates. Like what we saw for our COVID work with CLRI, this means that users can trust the accuracy of the data we present on the website and the information they receive about the health and well-being of their district and constituents.