Navigating the Federal Data Landscape in 2025 — What Community Health Teams Need to Know
Featuring Ben Spoer, Program Director at City Health Dashboard, and Heather Blonsky, Vice President of Data at Metopio
Where Federal Data Stands Today
Federal data sources have long been the backbone of community health assessments, improvement plans, and health equity initiatives across the country. But 2025 has brought unprecedented disruption to that infrastructure — and public health and hospital teams are rightfully asking: what happens next?
In a recent webinar, Metopio hosted Ben Spoer, Program Director for the City Health Dashboard and Congressional District Health Dashboard at the NYU Grossman School of Medicine, alongside Heather Blonsky, Vice President of Data at Metopio, to address these concerns head-on.
The Federal Data Sources We Rely On
Both the City Health Dashboard and Metopio rely heavily on three major federal data sources:
CDC Places — A project that downscales Behavioral Risk Factor Surveillance System (BRFSS) data to provide health outcome estimates at the city and census tract levels.
U.S. Census American Community Survey (ACS) — Provides critical social and economic data, from poverty rates to broadband access to neighborhood segregation metrics.
National Vital Statistics System — Aggregates the nation's birth and death records to produce metrics like maternal mortality, teen births, and disease-specific mortality rates.
"Something like three-quarters of the metrics we provide via our websites are sourced from federal data sources," Spoer explained. "So we're always watching them as closely as we possibly can."
What Happened in 2025
The disruptions began in early 2025, when the entire CDC Places team was eliminated through reductions in force (RIFs). Fortunately, much of the 2025 data release had already been completed, and the CDC Foundation carried it across the finish line — though the release came months later than scheduled.
The Census Bureau's American Community Survey faced similar delays due to government shutdowns, pushing the typical December release into mid-January.
But beyond the immediate delays, there's a deeper concern: the loss of expertise.
Without federal coordination, state-level data becomes harder to compare, standardize, and aggregate — which undermines one of the most powerful aspects of national datasets: the ability to benchmark and identify disparities across geographies.
The Threat to Public Trust
Perhaps even more concerning than staffing cuts is the erosion of public trust in government data collection.
"My biggest fear for the census is that people are losing trust in the government and government data," Spoer said. "So when someone knocks on their door asking a bunch of kind of personal questions, they're less likely to answer — and the robustness of the estimates is going to be lessened."
According to the American Statistical Association, most federal statistical agencies have lost 20-30% of their staff since 2009. As both data collection capacity and public confidence decline, the reliability of the datasets that inform billions of dollars in public health funding and interventions is at risk.
What Community Health Teams Can Do Now
Despite the uncertainty, there are concrete steps that public health departments, hospitals, and community organizations can take to continue their data-driven work.
1. Rely more heavily on state and local data
"There are lots of people at non-federal levels who are interested in the exact same topics," Blonsky explained. "That could be your state government doing what they can, or your local partners and collaborators who may not be a statistical organization but know their area really well."
State health departments, local food banks, homeless services networks, and other community organizations often collect rich, granular data that complements federal datasets — and can fill gaps when federal data is delayed or unavailable.
2. Leverage community surveys
Surveys remain one of the most direct ways to understand community needs and priorities.
"I love a survey," Blonsky said. "It brings in that surveillance data, but also that community voice — the prioritization that you can do with your community input."
Whether through formal BRFSS participation, Community Health Assessment surveys, or targeted local surveys, primary data collection gives organizations direct insight into their populations.
3. Explore alternative data sources
Spoer outlined four approaches his team is investigating to compensate for potential federal data gaps:
State-released datasets — Aggregating publicly available state data, acknowledging it won't be as complete as what the federal government had access to
Small area estimation methods — Using advanced statistical techniques to downscale data from larger geographies, similar to what CDC Places did
AI and predictive modeling — Cautiously exploring machine learning to fill in data gaps, though with concerns about validation and "hallucinations" when there's no reference dataset
Electronic health records (EHR) — Analyzing aggregated, de-identified EHR data to understand disease outcomes and healthcare utilization patterns
Each approach has limitations, but they represent viable stopgaps if federal datasets become unavailable or significantly delayed.
4. Use claims and emergency department data
One of Metopio's strategies has been partnering with organizations to leverage de-identified, aggregated claims data — particularly emergency department visits.
"It's not perfect," Blonsky acknowledged. "But it does tell you a lot about who shows up, who has something they can't manage at home. And it gives you a point where you could intervene."
Emergency department data is particularly valuable because preventable ED visits can be reduced through targeted interventions — and those reductions happen faster than many other health outcomes.
The Limitations of Alternative Data
Both Spoer and Blonsky were careful to note that none of these alternatives fully replace federal datasets.
Electronic health records, for example, only capture people who access the healthcare system — missing those who lack insurance, avoid care due to cost, or have subclinical conditions.
And as health insurance premiums rise and subsidies expire, EHR data becomes an increasingly biased sample.
Similarly, AI-driven imputation methods face a critical challenge: without a gold standard federal dataset to validate against, how do you know the model isn't hallucinating?
Despite these limitations, the alternatives remain valuable — especially for understanding local conditions and designing targeted interventions.
Advocacy Matters
Beyond adapting to data gaps, both Spoer and Blonsky emphasized the importance of advocacy.
"If policymakers hear from six people on a topic, it really grabs their attention," Spoer noted, citing a podcast he'd heard. "Because they actually don't hear from people that often."
Resources for advocacy include:
The American Statistical Association's reports on federal data disruptions
CDC Foundation and Friends of NCHS — organizations that advocate for and fund federal statistical agencies
Federal Data Forum — A resource for staying up-to-date on federal data source changes
Congressional District Health Dashboard — Links users directly to their representatives with data to support advocacy efforts
"Bringing your expertise and telling your story about how you actually use this data to make their communities better is really powerful," Angie Grover, Metopio's COO, added. "Your elected officials have to be experts on about a million different topics — so your voice matters."
Looking Ahead to 2026
The good news is that most of the data expected in 2025 did eventually arrive, even if delayed. The question is what happens in 2026 and beyond, as the loss of expertise, declining response rates, and continued budget cuts compound over time.
"Because of how long these data take to mature, to become available, we are also looking at whether these changes to the federal data infrastructure could have impact even beyond the current federal administration," Spoer said.
For community health teams, the path forward requires a combination of resourcefulness, advocacy, and collaboration. Federal datasets aren't going away entirely — but they're becoming less reliable, timely, and comprehensive.
Organizations that diversify their data sources, invest in local partnerships, and engage in advocacy will be best positioned to continue their work effectively.
““Public health work has always been about resourcefulness and scrappiness. Even when we weren’t facing changes from the federal level.” ”
Local data can be an incredible source. It doesn't replace federal data, but it does give you a lot to work with!
Data Is About Real Lives
As Grover reminded participants at the start of the webinar, "Data is really about real lives, and it gives us the opportunity to have strategic and meaningful change."
That truth remains, even as the landscape shifts. Community health teams have always adapted to resource constraints, policy changes, and uncertainty. The current moment is no different — just more urgent.
The work continues. The need remains! And with the right strategies, community health leaders can navigate this uncertainty and keep driving the change their communities deserve.