National Public Health Week 2026: The role of data in advancing public health

When a person gets sick, they go to the doctor. When a community struggles with health concerns, frontline care is just one part of the treatment plan.

The field of public health is dedicated to promoting well-being at the community level through policymaking, prevention, education, and emergency response. During the first full week of April, the American Public Health Association celebrates the impact of public health and its 154-year history in the U.S.

What is National Public Health Week?

National Public Health Week (NPHW) is a yearly observance that recognizes the community health workers, clinicians, researchers, and advocates who collaborate to improve public health, and to raise awareness around public health issues.

More than 30 years since its initial recognition via proclamation by President Bill Clinton, NPHW 2026 arrives at an inflection point in U.S. public health policy.

The past year has seen sweeping cuts to the Centers for Medicare & Medicaid Services, Food and Drug Administration, Centers for Disease Control, and National Institutes of Health, leading to the shuttering of some programs dedicated to public health research, monitoring, prevention, and direct care—and leaving many others with fewer resources and staff.

As the federal government reduces its investment in public health, factors like rising healthcare costs, workforce shortages, and evolving patient needs will require organizations in both the public and private sectors to seek every advantage to carry out their missions effectively.

Facing headwinds, public health benefits from better data

The ability to access, analyze, and act on timely healthcare data has always been foundational to advancing public health outcomes. Anticipating the health needs of communities and populations before they escalate is central to the field’s work, and the right data enables a proactive approach to strategy and decision-making.

Using reliable, real-world data sources like procedure and diagnosis claims, de-identified clinical activity from electronic health records (EHRs), population-level consumer insights, and social determinants of health (SDOH), public health organizations can:

• Identify at-risk populations earlier
• Track disease progression across regions
• Detect gaps in care delivery
• Monitor the effectiveness of interventions in real time
• Align more effectively with other organizations
• Make faster, more informed decisions

For example, at the height of the COVID-19 pandemic—a period that saw labor, supplies, and financial resources strained immensely—data played a critical role in tracking infection rates, allocating resources, and guiding policy decisions for local, regional, and federal administrative entities.

COVID-19 also revealed the risks of leveraging incomplete or unreliable data and highlighted the value of cross-regional data standardization. Early on in the pandemic, decision-making and predictive models were often hindered by overreliance on seven-day incidence figures, underreporting of hospitalizations, and lags in data reporting.

Post-pandemic, healthcare data continues to support efforts to address chronic conditions, behavioral health challenges, and health inequities. Even where the federal government has let datasets go dormant, regional health alliances and medical societies have stepped up to fill some of the gaps.

Data drives early intervention, better outcomes

A fundamental goal of public health is to intervene early, before health issues escalate into health crises. It’s typically less resource-intensive, less invasive, and more effective to address health issues at an early stage, both when it comes to individuals and populations.

But early intervention depends on knowing who is at risk, and when. By integrating multiple data sources, organizations working to improve public health can build comprehensive risk profiles that permit a more nuanced and dynamic view of populations’ well-being than limited studies or demographic trends.

Geography-bound claims, privacy-compliant EHR data, and population intelligence on consumer behaviors and preferences provide community-specific insights into:

• De-identified clinical activity, including diagnoses, lab tests, and medication adherence
• Utilization patterns, such as facility usage, readmissions, and emergent care
• Social determinants of health, like income, transportation access, and housing stability
• Consumer preferences, indicating ideal channels for engaging specific populations within a community

This data gives public health organizations a multidimensional view that helps uncover risk factors across communities. But the most effective analytical models leverage huge datasets—the larger the community, the broader the dataset—creating a potentially massive lift, even for organizations with dedicated data scientists.

Analytical tools powered by artificial intelligence and machine learning algorithms enable predictive modeling and correlation detection at greater scales, augmenting human insight. Equipped with the right data and the right analytics, healthcare organizations can be more proactive in their risk assessments, interventions, and outreach.

Health equity goes further with data-driven visibility

Health inequities remain one of the most pressing challenges in public health. Racial and ethnic minorities in the U.S.—but especially Black and Indigenous Americans—face higher rates of infant mortality, mortality related to pregnancy and chronic illness, and shorter average lifespans than their White peers.

The inequities don’t just fall on demographic lines. Americans living in rural regions are more likely to rely on federally supported critical-access hospitals and Affordable Care Act subsidies—both impacted by major funding cuts in 2025.

On top of the human cost, the Deloitte Health Equity Institute estimated that health inequities were responsible for $320 billion in annual healthcare costs in the U.S., with annual costs expected to rise to $1 trillion by 2040, barring intervention.

Healthcare data provides public health and provider organizations with the visibility needed to uncover disparities in access to care, treatment patterns, and outcomes across demographic and geographic groups.

With insights gained from procedure and diagnoses claims, reference and affiliations data, and population data, organizations can spot disparities and shape strategies around access expansion, patient engagement, and clinical trial design more equitably.

Finding the path forward for public health

As we recognize National Public Health Week, it seems clear that the immediate future of public health is likely to be shaped by innovations in insight generation just as much as (or even more than) innovations in treatment.

Robust, reliable, and real-time healthcare data gives organizations working in public health the ability to anticipate community needs, coordinate care more effectively across communities, and deliver stronger, more equitable outcomes—even as headwinds continue to pick up.

Definitive Healthcare’s portfolio of data and analytics products includes deep insights into patient populations, healthcare organizations, and scientific and medical experts. To learn more, sign up for a demo today.