GovLoop

How CDC Uses Data Analytics to Monitor the Nation’s Health

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Data analytics is a hot topic in government and one that continues to gain traction. Agencies are increasingly relying on analytics to help fight diseases, combat fraud, improve citizen services and more.

To better understand how the Centers for Disease Control and Prevention is using analytics, we heard from Ana Penman-Aguilar, Associate Director for Science at CDC’s Office of Minority Health and Health Equity. Her comments were edited for length and clarity.

GOVLOOP: Tell me about your organization’s mission and projects that are underway and some of the issues you are trying to tackle?

PENMAN-AGUILAR: CDC works 24/7 to protect America from health, safety and security threats. The future health of the nation will be determined to a large extent by how effectively we work with communities to eliminate health disparities among those populations experiencing a disproportionate burden of disease, disability and death. CDC’s Office of Minority Health & Health Equity (OMHHE), located in the CDC Office of the Director, works to decrease health disparities, address social determinants of health, and promote access to high quality preventive health care. OMHHE envisions a world where all people have the opportunity to attain the best health possible.

GOVLOOP: How are you using data and analytics to tackle those issues?

PENMAN-AGUILAR: CDC’s surveillance systems are designed to take the health pulse of our nation. CDC areas of scientific focus are guided by analysis of surveillance and research data. On the programmatic side, requests for proposals/funding announcements, communication campaigns, and technical assistance to funding recipients are all based on the data analysis. In each of these activities, CDC uses data to identify differences among population groups and to target actions accordingly.

GOVLOOP: Can you share a time when your organization used analytics to drive better decision-making?

PENMAN-AGUILAR: The 2011 and 2013 CDC Health Disparities and Inequalities Reports (CHDIRs) relied on various data sources (CDC and external) to characterize health disparities. Scientists from across CDC analyzed data to examine health determinants and health outcomes, access to health care, health behaviors, and exposure to environmental health hazards relative to race and ethnicity, sex, age, household income, educational attainment, geographic location, and some additional factors when data were available.

GOVLOOP: What did you learn, and what were the outcomes?

PENMAN-AGUILAR: For a number of Americans, their health and health outcomes can be related to their income, education level, sex, race, ethnicity, employment status and sexual orientation. The reports also underscored the need for interventions to reduce disparities. In response to this need, OMHHE published a related report, the “Strategies for Reducing Health Disparities — Selected CDC-Sponsored Interventions, United States, 2014.” This report includes selected interventions that reflect public health actions supported by CDC that are proven effective or show promise for reducing health disparities at the local or national levels. A follow up report in 2016 included additional interventions addressing disparities by race and ethnicity, socioeconomic status, geographic location, disability, and/or sexual orientation across a range of conditions.

GOVLOOP: How did you gain buy-in for the project and how are you creating a culture for analytics at your agency?

PENMAN-AGUILAR: CDC is committed to reducing health disparities and values evidence-based decision making. The National Centers at CDC (the centers responsible for areas such as chronic diseases or particular infectious diseases) use data analysis to identify differences among population groups and to target actions to those at greatest need. One aspect of this work is ensuring that those who develop funding announcements do so with the intention of reducing health disparities. OMHHE works with CDC’s National Centers on how funding announcements for public health programs are developed and worded.

GOVLOOP: What do you hope to do with data and analytics near-term and long-term that you cannot do today?

PENMAN-AGUILAR: CDC will continue to learn and adapt based on new insights regarding health disparities. For example, given increasing national attention on the needs of rural populations, CDC is publishing a series of articles that uses data analysis to focus on the health needs of rural populations.

GOVLOOP: What advice do you have for others in government who want to use data analytics?

PENMAN-AGUILAR: It’s important for agencies and OpDivs [operating divisions] to work together, learn from each other, and make use of resources others have made available. This includes using each other’s data to answer important questions that they face. One of the strengths of the CHDIR reports was the variety of data sources used. Using non-CDC data sources in those reports allowed CDC to focus on some of the social and environmental factors that are known to be important for health.

GOVLOOP: Can you share any data visualizations? (graphics/charts that are based on data analytics usage)?

PENMAN-AGUILAR: CDC routinely generates data visualizations such as maps of health outcomes by race and ethnicity or by social determinants of health. Some examples of data visualizations related to health disparities can be found [here]. In fact, the parent website for this page is a resource related to social determinants of health, health disparities, and health equity we would like others inside and outside of government to become more aware of.

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