Public Health and IT Environment

As the world of data rapidly changes, the different pieces that must be put together to identify, prevent, and respond to emerging public health threats becomes more complex. This means preparing to scale for future threats with the compute power to handle ever-growing volumes of data. It means learning to use new sources of data that can inform public health science and policy. Historically, computations were performed on data samples, using statistical methods to draw inferences from those samples. Big data means calculations can be performed on all the data, suggesting a world in which there is no sampling error. The ability to tap into more sources of data and quickly analyze and handle the complexity of available data will lead to timelier and more accurate public health decisions.

Public health data is more connected and more automated than ever before. Data now streams between hospitals and public health departments, with thousands of health care facilities exchanging automated, real-time health information. There is an expectation of shorter time for data collection and analysis and publication to CDC’s partners and the citizens served, yet multiple silos still separate parts of the public health ecosystem and continued reliance on older legacy technology limits our ability to bridge those silos. We need every system talking to each other in real time — from local communities, to states, to national and global networks — to stay ahead of whatever comes next. To build a more integrated and connected ecosystem, we must communicate and collaborate with partners, to collect and share information as never before.

CDC envisions a future in which public health threats can be predicted and prevented before they occur. A new wave of capabilities and still-emerging technologies, such as artificial intelligence (AI) and machine learning, make possible rapid data analysis and real-time insights that can get ahead of epidemics and stop them quickly. For these technologies to be integrated successfully will require new approaches to managing and sharing data, such as those enacted by the Foundations of Evidence Based Policy Making Act of 2018, and a workforce whose skills keep pace with rapidly evolving mission needs and technological capabilities. CDC and our partners must be transformed from a culture of primarily historical data analytics to predictive data science.

Discrete, one-off projects or a narrow focus on individual capacities create gaps in our public health data systems that prevent communication and inhibit information sharing. The establishment of enterprise capabilities that are sustainable and adaptable will make public health more responsive and resilient in the future. Legacy solutions must be replaced by modern IT platforms and enterprise services that can be individually and collectively used to meet a variety of mission needs. Adaptable enterprise capabilities–together with standards for data and system interoperability and streamlined IT and data governance–will provide CDC and our partners with the ability to quickly innovate new solutions that provide faster, better insights, promote understanding of public health information, and save lives.

As technology becomes more integrated and more essential to the public health mission, managing cybersecurity risk is mission critical. More digital interactions combined with the increased frequency and sophistication of cyber-attacks threaten sensitive public health data and systems. Cyber forensic and threat prevention capabilities must be maintained to block attacks at the enterprise network perimeter. Vital IT modernization efforts, such as accelerating the migration of public health infrastructure to the cloud, must be accompanied by equally vital investments in cybersecurity.