Overcoming Data Lag and Harnessing Hyperlocal Data – Key Takeaways from 2023 Spring Conferences

Public health conferences this Spring focused on health equity and the opportunities, barriers and lessons learned coming out of the COVID-19 pandemic. Metopio, along with our partners and clients, led and engaged in meaningful discussions.

Across al of them, three key themes emerged:

• Addressing the lag in data releases

• Getting hyperlocal data

• Appreciating the power of place-based analytics

Addressing the lag in data releases

Government agencies are responsible for collecting, analyzing, and disseminating a vast array of data ranging from economic indicators and public health statistics to crime rates and population demographics. Yet, despite the advancements in technology and data management systems, delays in reporting this crucial information remain a common phenomenon.

This lag undermines leaders’ ability to formulate effective strategies and hinders their capacity to respond swiftly to emerging issues. For example, the last time the federal government released zip code level flu vaccination rates was 2016. Since then, we’ve had a pandemic and major changes in public perceptions about vaccines. Being able to have current vaccination data would help providers understand trends in hesitancy. Similarly, census tract life expectancy figures haven’t been calculated since 2015. Just these two datasets alone are critical for understanding how best to target programs like vaccine outreach.

The causes for the data lags are well known:

• Government agencies often operate within complex bureaucratic structures, involving multiple layers of approval

• Outdated data management systems and infrastructure can impede the efficient processing and dissemination of data

• Accuracy requires rigorous data quality checks and verification processes that can prolong reporting timelines.

Whether it was HIMSS, ASTHO, AHA’s Accelerating Health Equity or CMS’s Inaugural Health Equity conference – there are some clear solutions being put into action.

First, the CDC is laser focused on its Data Modernization Initiative (DMI). As it takes shape, the DMI work should create more interoperability of data systems and timelier reporting so decision-makers can access insights “at the speed of need.”

Academic institutions like our partners at UIC’s PHAME Center are working on small area estimates. Creating modeled data serves as an important interim step while waiting for primary data to be collected and reported.

Health systems and public health departments are often sitting on valuable data ranging from pulse surveys and patient satisfaction interviews to utilization and program outcome data. Creating effective, safe and secure ways to share these datasets and combine them with public data like what’s found in Metopio’s curated data library, provides rich, actionable insights.

There’s local and then there’s hyperlocal data

The need for hyperlocal data in community health cannot be overstated. Data at the county level cannot reflect the diversity and richness of neighborhoods as well as critical drivers of health outcomes. Hyperlocal data that provides granular information specific to small geographic areas such as neighborhoods, census tracts, or even individual streets is the roadmap necessary to build healthy and resilient communities.

Hyperlocal data allows public health professionals to understand the specific social, economic, and environmental nuances influencing health outcomes at the most localized level possible. This detailed perspective is crucial in identifying and addressing health disparities that may vary even within close proximity.

And being able to focus avoids a one-size-fits-all approach that often falls short when it comes to addressing complex health challenges. Hyperlocal data, especially census tract level, avoids spreading very limited resources too thin. By understanding the local context, community health professionals can develop targeted strategies that consider cultural practices, socioeconomic factors, key stakeholders and existing resources, thereby increasing the likelihood of successful outcomes.

Effectively sharing hyperlocal data is equity. Often individuals with lived experience don’t have access to data and individuals with data don’t have lived experience. Individuals and community-based organizations that have access and can work together to fill gaps in the data are able to work together to prioritize specific health risks, leverage or create resources within their own neighborhoods, advocate for change, and own better health outcomes in the community.

The Power of Place-Based Analytics

At Metopio we know place-based analytics holds immense promise. At each conference, leaders shared successful interventions that were the result of doing an analysis with a geographic component.

Place-based analytics recognizes that locations matter. Understanding the characteristics, dynamics, and interactions of specific places provides an understanding of the relationship between people and their environment, driving valuable insights for decision-making.

Where you live is one of the most significant components of overall health outcomes and life expectancy. Up to 60% of your health is determined solely by your ZIP Code which is why timely, hyperlocal data matters. Disparities like higher rates of poverty, inadequate infrastructure, or limited access to healthcare reveal themselves when everyone can access the data.

Accessing the data is one essential component. Visualizing data is another. With maps, charts, tables and scatterplots accessible to a broader audience, it means all stakeholders can tell their story more effectively and identify challenges and opportunities specific to their community. This engagement empowers communities to actively contribute to the development and implementation of solutions, ensuring that interventions are responsive to local needs and priorities.

With these critical data infrastructure improvements underway at the federal, state and local levels and the tools we’ve built at Metopio to work with hyperlocal and place-based data, we’re at a point where we can better forecast future trends, anticipate emerging issues, and optimize resource allocation.

This forward-looking approach is what we need to address the unique challenges each community faces and maximize our impact.