The public health practice community has reached a turning point. To accelerate how we detect, respond to, and mitigate public health threats, we must improve public health's data infrastructure. The COVID-19 pandemic is a stark reminder of the vital, centuries-old role that hundreds of thousands of public health professionals play in protecting the health and safety of communities in the United States. Historically, public health's impact has been “behind the scenes.” When it works, communities are vital, well, and healthy. COVID-19 has shown what happens when public health faces challenges due to chronic underfunding and a lack of clear transformational planning for modernizing data systems, which are the critical backbone of all public health programs.
As a data-driven field, we have seen the critical need for better data infrastructure during the pandemic. The response thus far? Increased federal and philanthropic funding opportunities have positioned the United States to launch a transformation. Like any critical public service—such as law enforcement and fire protection—there must be ongoing investment beyond the recent down payments. While Congress, the Centers for Disease Control and Prevention (CDC), and a host of national public health organizations have recognized the need for this effort previously—referred to by CDC as the Data Modernization Initiative—since 2019,1 funding in this area has increased significantly as COVID-19 relief funds have been allocated to data modernization efforts.
An Enterprise Approach to Integrating Data Siloes
The success of data modernization is not solely dependent on technology, because the solutions we need exist today. Simply purchasing new software or integrating new data standards is not the answer. Our success rests on transforming the operational norms within the field to embrace enterprise architecture (EA) and coordinated approaches to data management and analysis. While private and public sector entities have successfully done this for years, it is a major shift for public health, which has typically been funded by, and operated within, programmatic and functional focus areas. Yet, true, long-term data modernization calls for integrating efforts across all public health program sectors.
EA increases the efficacy of an organization's digital and informatics capabilities and resources by leveraging across the enterprise.2 It connects the business (ie, the public health program) function and information technologies or systems of an organization to better harness the power of data to protect against public health threats. Several EA frameworks emphasize information exchange between agencies by focusing on functional roles and responsibilities such as planner, owner, designer, builder, and the system itself.3 Some of the barriers evidenced by a review of various health care organizations include limited understanding of EA frameworks by the current workforce, lack of technical infrastructure, limited interoperability of systems, poor alignment of organizational and information technology strategies, and lack of senior management or leadership involvement.2 Enterprise-level transformation is vast, and local, state, and territorial health leadership needs the right project and change management efforts to successfully lead their agencies and workforce through comprehensive, integrated data modernization well after COVID-19 subsides.
Modernized Public Health Surveillance
A highly diverse and complex network of federal, state, territorial, local, and tribal agency surveillance systems is responsible for collecting, analyzing, and acting on public health surveillance data for a plethora of disease-specific needs and functions. CDC alone maintains more than 100 surveillance systems for a variety of conditions and uses.4 Hundreds more exist across state and local public health agencies, all key components of CDC's data ecosystem. The resulting landscape of US public health surveillance is a complex one, comprising siloed and legacy data systems, a diverse technology vendor community with widely different approaches and solutions, in addition to variations in surveillance processes and platforms across jurisdictions and levels of government. Together, these factors significantly hinder rapidly collecting, exchanging, and integrating data for public health action.
National data modernization efforts hold the promise of transformative change for our public health surveillance infrastructure. And while these efforts have an initial focus on 5 core data systems—syndromic surveillance, electronic case reporting, notifiable diseases, electronic laboratory reporting, and vital records5—it is incumbent on public health leaders at all levels of government to adopt a holistic view as they assess opportunities to modernize all critical information systems. This means, for example, incorporating immunization information systems and many others into modernization efforts and broadening activities to include connections to data systems outside the public health sector, such as health information exchanges, Medicaid data systems, and the Veterans Health Administration.
We can support a modernized surveillance infrastructure by bolstering connections between information systems and ensuring existing technologies are available where they are needed. More importantly, we must tackle the policy challenges, organizational behaviors, and resource distribution patterns that may, in some cases, limit our ability to integrate surveillance data for a more complete picture of the public's health. For example, advanced molecular technologies are available to detect and respond to outbreaks and viral variants—but these technologies must be readily accessible to all state health agencies in order to ensure rapid public health response to new threats.
In addition to strategic investments in an expanded public health informatics workforce, our readiness to transform the public health data and surveillance infrastructure relies on the vision and leadership of federal, state, and local officials. Equally mission critical are breaking down siloes of federal funding to align across agencies and grant streams, ensuring flexibility to meet jurisdiction-specific needs, and generating sustainable resources to ensure long-term change.
A Vision for the Future
Over the coming years, expect to see various public health data collection and analysis efforts relying on common platforms or technologies built on common standards and interoperable across systems and jurisdictions. All of these will be supported by an advanced informatics and technology workforce that is shaping the future of the nation's public health capabilities. Ongoing investments are crucial to realizing this once-in-a-generation opportunity to transform our nation's defense against public health threats.
To sustain this new era of public health practice, we must take a multifaceted approach. First, Congress will need to continue its bold leadership and investments begun in 2019 before the first US COVID-19 case was confirmed. Second, we will need to work together—across public health programs at the federal and state levels—to plan data strategies and share investments where possible. Finally, we must explore payment incentives to providers for mandatory public health reporting through partnerships with Medicare, state Medicaid programs, and health plans.
Public health is only as effective as our data and the information systems that drive its use. A foundational reconstruction of our data systems, methods, standards, and partnerships is all an expression of our renewed desire to protect the health of the public. We have recognized—both as public health practitioners and as active, caring members of the communities we share with our families and friends—that we value the ability to share information and relevant data to improve our public health intelligence and our ability to protect our neighbors from emerging health threats.
1. Centers for Disease Control and Prevention. Data Modernization Initiative. https://www.cdc.gov/surveillance/data-modernization/index.html
. Accessed January 6, 2022.
2. Jonnagaddala J, Guo GN, Batongbacal S, Marcelo A, Liaw ST. Adoption of enterprise architecture for healthcare in AeHIN member countries. BMJ Health Care Inform. 2020;27(1):e100136.
3. Haron N. The Importance of Enterprise Architecture in Public Health Surveillance System. ResearchGate. Preprint posted online February 2020. https://www.researchgate.net/publication/339290072_THE_IMPORTANCE_OF_ENTERPRISE_ARCHITECTURE_IN_PUBLIC_HEALTH_SURVEILLANCE_SYSTEM
. Accessed January 6, 2022.
4. Office of Public Health Scientific Services, Centers for Disease Control and Prevention. Public health surveillance: preparing for the future. https://www.cdc.gov/surveillance/pdfs/Surveillance-Series-Bookleth.pdf
. Published September 2018. Accessed December 11, 2021.
5. Centers for Disease Control and Prevention. Data Modernization Initiative: an urgent need to modernize. https://www.cdc.gov/budget/documents/covid-19/COVID-19-Data-Modernization-Initiative-Fact-Sheet.pdf
. Published November 18, 2020. Accessed December 11, 2021.