Home » Blog » Alliance Discussion with Dr. E. Oscar Alleyne: Transforming Public Health through Data Modernization and People-Centered Approaches

Alliance Discussion with Dr. E. Oscar Alleyne: Transforming Public Health through Data Modernization and People-Centered Approaches

Epidemiologist and leading public health expert, Dr. E. Oscar Alleyne, Managing Director of the Public Health Division at MITRE, joined us for a special Public Health Thank You Day alliance discussion on November 20. MITRE partners across government, industry, and academia to improve our nation’s public health and well-being. Dr. Alleyne shared how improvements in our public health infrastructure and data modernization have helped communities around the country better tackle public health threats. Dr. Alleyne also shared a call to action for integrating people-centered approaches to delivering public health services. Here are some of his thoughts on:

How the preferences of individuals and communities can be considered in the design of public health services:

“I would say the biggest way is by embracing those community-level inputs. We are in the business of people, so we can’t divest ourselves from the people-based approaches and the impact that may have. Some of the best models that I have seen have been truly integrated by ensuring that individuals and communities are part of the planning process. In that regard, ensuring that when systems are designed, when hypotheses are rendered, when a research imperative, or an opportunity to develop a public health intervention strategy, that there are representatives of those communities that will be impacted at that table and that their ideas are heard. We’re not going to be successful in creating things in a vacuum, or in a clinical laboratory space without necessarily involving those and the dynamic nature of those communities and the populations that we serve.”

If there are new research techniques to better incorporate the public’s perspectives and experiences into research and public health interventions:

“I’ll give two quick examples. I look at the All of Us campaign, how that was really focused on trying to elevate the participatory realm of making sure individuals and communities are represented in clinical data research. That required on the ground, visible exchange, talking with communities, ensuring that they understand their security needs to data access points, and that there’s a sense of ownership from beginning to end. The second is an initiative that CDC, HHS, and other agencies have used – CODI – a clinical and community data initiative role program. What that does is recognize that communities themselves track and store health-related data, in addition to the data that you get from health care and research. The problem is how to standardize, link, and reconcile those resources and information, while at the same time preserving privacy. This CODI initiative looked at how to bring individuals, organizations, collaboratives, as well as the governmental public health and the health care elements to support that community effort to build and ensure that data and data-driven approaches are inclusive, but that they can produce tools that ensure standardize models for individual record keeping and of course, the privacy element.”

Equity centered public health data and how it can help mitigate health disparities and racial injustice and improve population health overall:

“The 10 essential public health services illustrate the various slices of how public health is integrated; central to that is this term of equity. Having an equity-based approach is to ensure that data collection, data integration, and data analytics have that foundational element in mind. A perfect example of how we collect data – sometimes we want to make sure it’s across a continuum, other times we want to make sure it’s reproducible and we’re able to compare it over the course of time. All those things must be shifted when we’re thinking about an equity-based approach. Why do I say that? When we look at an indicator such as race – we have been following this institutionalized approach to this concept of race – our communities have changed over the course of time. Their viewpoint around race and how one will self-identify does not fit the modules or the process that we’ve had over time, so that puts us at a little bit of a disadvantage. When we as researchers, public health strategists, and applied public health professionals are looking at data with this kind of construct that doesn’t match present community-based approaches, it becomes very difficult to recommend strategies, interventions, or identify solutions to improve health when we’re using indicators that do not speak to those communities.”

“The equity-centered approach allows you to change the thought process and how one is in thinking about solutions or descriptors, how one takes indicators in a way, and ensures that they themselves are not part of the problem, but that we’re able to re-adjust and be flexible in the way we are truly doing data visualization, data analytics and community centered approaches toward the solutions that we have in our, in our sector.”

Ways that public health professionals can do a better job of incorporating the voices of marginalized communities to lead to more equitable research:

“One of the first things I would say is that we need to abandon the paternalistic way of looking at things. Most public health professionals have a significant amount of empathy and drive; there’s a fire in our bellies for improving the health and safety of communities. Oftentimes, however, we can’t speak for others unless we have incorporated their lived experience. Let’s say I want to increase the mobility of an aging community and I use the example of self-automated vehicles. Individuals that are getting older may not have the ability to drive themselves, so these self-automated vehicles may be a research idea that we can implement for the solution bearing outcome. However, let’s think about it from the lens of the actual population. What if we have a rural living community where access to these vehicles are not readily available, or we have the other social terms of health in respect to economics or other particular elements that actually say, this solution has actually created more of a disparity because it’s only for those who have the ability [to purchase a vehicle], and not to those [marginalized] communities. If we’re truly trying to improve the health, safety, and wellness of communities, we must make sure we’re lifting the collective and not being lopsided with respect to who we’re actually immediately impacted as a whole.”

The current state of U.S. public health infrastructure and how investments made during the pandemic helped modernize it:

“The [public health] infrastructure has been siloed. There have been differences in design and how databases are covered – how this access point may be for chronic disease, this for communicable diseases, and not necessarily as interoperable as we want. There has been investment prior to the pandemic on data modernization – how to make things a bit more fluid in the way data can be exchanged between healthcare providers, electronic case records, the systems that exists within agencies like CDC, HHS, HERSA, CMS. All these individuals, groups, and programs had data points that were not communicating with each other. With the need for rapid access to data to make better decisions, as we saw with the pandemic, the investments over time were hoping are making things better but we recognize that’s not as rapid as we would like. So, how do we shift to ensure that the investments in both the architecture, the IT, and the ability to improve the exchange of information from a health record to provider to a clinical decision support to a public health authority? It’s complex. It’s not just as easy as flipping a switch and saying the problem is solved with a federal mandate. Each state has their own surveillance systems, their own ways of how their data is integrated, and cross jurisdictional elements are also an era of concern.”

How can we ensure that the data that we are collecting is accurate and reliable to disseminate to the public?

“In research and as epidemiologists, we recognize that data had an apolitical stance, meaning you just review data and put your findings out there. How people interpret it, that’s up to them. I think there’s a moral imperative and a social contract that we have as researchers and public health professionals to really ensure that we are providing information that is not twisted from differences of opinion; that we maintain that trusted partner lens and title. [This is] to ensure that when we are providing information, we recognize that it is for the common good of the community. When people are taking data and misappropriate it’s intent or describe things in a way that we know was not the intent of the researcher, we stand up and fight against the impact of myths and disinformation.”

Watch the full discussion here.