What health data execs need to manage an infectious disease response
Ebola and hantavirus outbreaks illustrate the tools and capabilities that must matter to those leading health data management initiatives.
When healthcare leaders hear the words “ebola” or “hantavirus,” many assume these are problems for infectious disease specialists, epidemiologists or public health agencies. Yet history has repeatedly demonstrated that emerging infectious diseases expose something much broader – the strengths and weaknesses of our data ecosystems.
Outbreaks rarely become crises because information is unavailable. More often, they become crises because information is fragmented, delayed, disconnected or inaccessible to the people responsible for making decisions.
For health data management leaders, Ebola and hantavirus offer important lessons that extend far beyond the pathogens themselves. They serve as reminders that organizational resilience increasingly depends on the ability to transform data into actionable intelligence.
Why these diseases matter
Ebola virus disease (EVD) has historically been associated with outbreaks in Central and West Africa and is characterized by severe illness and high mortality rates. According to the World Health Organization, case fatality rates have ranged from approximately 25 percent to 90 percent depending on the outbreak and available healthcare resources.
Hantavirus Pulmonary Syndrome (HPS) can progress rapidly from flu-like symptoms to severe respiratory failure, while other hantavirus strains can cause hemorrhagic fever with renal syndrome.
At first glance, these diseases appear unrelated. However, both reveal a common challenge facing healthcare organizations worldwide – the ability to identify emerging threats early enough to respond effectively. The issue is not geography; the issue is visibility.
The real challenge is data, not disease
Healthcare organizations today generate unprecedented amounts of information through electronic health records, laboratory systems, surveillance platforms, environmental monitoring programs, wearable technologies and population health initiatives.
Despite these investments, many organizations still struggle to answer a fundamental question – can we identify an emerging threat before it becomes an operational problem? This is where health data management leaders play a critical role.
The value of data is not measured by volume. It is measured by the ability to detect patterns, identify anomalies and support timely decision-making. In many outbreak scenarios, the earliest warning signs are subtle. They can show a cluster of unusual symptoms; a shift in laboratory results; an increase in respiratory complaints within a specific geography. Individually, these signals may appear insignificant. Collectively, they may represent the beginning of a larger event.
Organizations that can connect these signals gain time. More typically in the past, organizations often find themselves reacting rather than leading.
Why this matters to the C-suite
Emerging infectious diseases are no longer solely clinical concerns. They have become enterprise risks.
For chief executive officers, outbreaks can affect organizational resilience, community trust and strategic priorities.
For chief operating officers, they can disrupt staffing, patient flow, capacity management and operational continuity.
For chief financial officers, financial uncertainty arises from workforce disruptions, resource-allocation pressures, supply chain challenges and changing utilization patterns.
For chief information officers and chief digital officers, they test whether information systems can deliver accurate, timely intelligence when leaders need it most.
For chief medical officers and chief nursing officers, patient safety, workforce protection and care delivery challenges require rapid decision-making.
The boardroom conversation has evolved. The question is no longer whether organizations have data. The question is whether they can use that data to anticipate and respond to risk.
The One Health imperative
The growing adoption of the One Health framework reflects an important reality – human, animal and environmental health are interconnected.
Both Ebola and hantavirus illustrate this principle. Ebola outbreaks have been linked to interactions between humans and infected wildlife reservoirs. Environmental conditions, rodent populations and ecological changes influence hantavirus transmission patterns.
However, healthcare data systems often remain isolated from environmental, agricultural and veterinary surveillance efforts. This fragmentation limits situational awareness. Future-ready health data ecosystems must move beyond traditional healthcare boundaries and incorporate information from multiple sectors. Organizations that embrace this broader perspective will be better positioned to identify emerging risks before they manifest as clinical crises.
For health data leaders, this means developing governance models, interoperability frameworks, and partnerships that extend beyond hospitals and health systems. The future of disease surveillance will require a more comprehensive view of the factors influencing population health.
Interoperability as a strategic capability
Interoperability is often discussed as a technical requirement, regulatory expectation or operational efficiency initiative. Outbreaks demonstrate that it is much more than that; it is a public health capability.
Rapid identification of cases, effective contact tracing, coordinated resource allocation and informed decision-making all depend on the ability to exchange information seamlessly across systems and organizations. Data that’s trapped within organizational silos limits response effectiveness, regardless of the sophistication of local systems.
For healthcare executives, interoperability should be viewed as a resilience strategy rather than an information technology project. The ability to move information quickly and accurately can directly influence organizational outcomes during periods of uncertainty.
From reactive reporting to predictive intelligence
The COVID-19 pandemic accelerated investments in analytics, dashboards and digital health technologies. While these investments improved visibility, many organizations continue to operate within reactive reporting models. The future requires something different.
Healthcare organizations must evolve toward predictive intelligence ecosystems that integrate multiple data sources, identify weak signals and support proactive intervention.
This requires strong governance, trusted data, advanced analytics capabilities and leadership commitment. Most importantly, it requires health data leaders who understand how information can be transformed into a strategic advantage.
The future of infectious disease response will depend not only on laboratories, therapeutics and vaccines. It will depend on whether information systems can detect emerging risks early enough to change outcomes.
Next steps for health data management leaders
The question is not whether another emerging infectious disease will appear. The question is whether healthcare organizations are prepared to recognize and respond to it.
Health data leaders should focus on five priorities.
Strengthen surveillance capabilities. Organizations should move beyond traditional reporting and invest in surveillance capabilities that identify unusual patterns across clinical, operational, laboratory and population health data. Early warning systems are most effective when they can detect weak signals before they become visible through traditional reporting channels.
Expand data integration across sectors. The future of disease surveillance will depend on the ability to connect healthcare data with environmental, public health, veterinary and community-level information. The One Health framework requires organizations to think beyond organizational boundaries and develop new approaches to information sharing and collaboration.
Prioritize interoperability as a strategic initiative. Interoperability should be viewed as a foundational capability for resilience. Data that cannot be moved between systems cannot support timely decision-making. Health data leaders should continue advancing standards, governance structures and technologies that improve information exchange across the care continuum.
Invest in predictive analytics and artificial intelligence. Artificial intelligence and advanced analytics offer opportunities to identify patterns, predict risk and support earlier intervention. However, these capabilities are only as effective as the quality, governance and trustworthiness of the underlying data. Strong data management practices and responsible governance frameworks must accompany investments in artificial intelligence.
Elevate data governance to the executive level. Emerging threats reinforce the importance of trusted data. Governance programs should establish clear accountability for data quality, stewardship, privacy, security and decision support. Executives increasingly depend on data to guide operational and strategic responses during periods of uncertainty.
Why it matters
For healthcare data leaders, Ebola and hantavirus are not simply infectious disease case studies. They are examples of how information can influence outcomes.
The organizations that thrive in the future will be those that can rapidly transform fragmented data into actionable intelligence. They will identify risks earlier, respond more effectively, allocate resources more efficiently and maintain trust during periods of disruption.
In many ways, the next public health emergency will test more than clinical preparedness. It will test the maturity of our data ecosystems, the strength of our governance frameworks and the ability of healthcare leaders to turn information into action.
That is why Ebola and hantavirus matter to health data management leaders. Not because they are rare diseases, but because they reveal what happens when data, decisions and preparedness intersect.
Ebola and hantavirus represent more than isolated infectious threats. They are reminders that disease surveillance is fundamentally a data management challenge.
As healthcare becomes increasingly interconnected, the organizations best positioned to respond to future threats will not necessarily be those with the most data. They will be the organizations that can connect disparate information, identify meaningful patterns and translate insight into action. For health data management leaders, that responsibility has never been more important.
Dr. Julia Rehman, DHA, FACHE, FACHDM, is an Executive Fellow of the American College of Health Data Management.