Leveraging AI and Analytics: Unleashing the Power of Public Health Agencies

**Transforming Public Health: The Impact of AI and Advanced Analytics**

**Introduction**
Public health agencies have been at the forefront of protecting and promoting community well-being for many years. In recent times, these agencies have started to embrace transformative technologies like Artificial Intelligence (AI) and advanced analytics to enhance their capabilities and efficiency. This integration of cutting-edge tools has revolutionized the field of public health, opening up new avenues for data-driven decision-making, disease surveillance, and outbreak response.

**Improving Outcomes with AI and Advanced Analytics**
One of the key areas where AI and advanced analytics have made a significant impact is in the use of data to improve outcomes and inform decision makers. Public health agencies have vast amounts of data, and analyzing and making sense of it manually would be nearly impossible. However, by utilizing AI and advanced analytics approaches to analyze and classify these vast datasets, organizations can enhance accuracy and speed in their operations.

At the May 2023 GovFuture Forum event at George Mason University (GMU) in Washington, DC, experts from the CDC’s National Institute for Occupational Safety and Health (NIOSH) shared their perspectives on advanced analytics. Stacey Marovich, Lead Health Informatics Scientist at CDC NIOSH, and Jennifer Cornell, also from CDC NIOSH, provided insights into how AI and advanced analytics are positively impacting their agency’s work. In a follow-up interview on a GovFuture podcast, Stacey and Jennifer delved deeper into how AI and analytics are applied to NIOSH Industry and Occupation Computerized Coding System (NIOCCS) and how technology is helping in unexpected ways.

**Enhancing the NIOCCS System with Technology**
The NIOSH Industry and Occupation Computerized Coding System (NIOCCS) has been in use for over a decade and is currently in its fourth major version. NIOCCS translates industry and occupation text data into standardized codes for research and analysis purposes. The system is free and publicly available on the web, making it accessible to anyone.

According to Stacy, NIOCCS has significantly improved coding accuracy and streamlined the process. Jennifer shared examples of how public health departments have utilized the latest version of NIOCCS during the COVID-19 response. One jurisdiction reported using the NIOCCS Web API extensively to code health data for workplace outbreaks and survey data, enabling quick and effective response to the pandemic. The system reduced training time for new staff and modernized data collection processes. Another jurisdiction used NIOCCS with real-time coded data to disseminate essential workplace measures to local and tribal health departments rapidly. The unexpected positive outcomes included cross-checking of coding by users and the use of NIOCCS by private entities and nonprofits for workers’ compensation data coding.

**Striking a Balance Between Transparency and Privacy**
While harnessing the power of AI and advanced analytics, public health departments must strike a balance between transparency and protecting individuals’ private information. Transparency ensures that the public remains informed about health risks and mitigation strategies, fostering trust and cooperation. However, privacy concerns must also be addressed to safeguard sensitive data and preserve individual autonomy.

Stacy acknowledges the challenges of maintaining transparency while dealing with health data, which can be sensitive. Restrictive data use agreements may limit the usage and storage of data. However, in NIOCCS, the industry and occupation data collected does not include Personally Identifiable Information (PII) like names, ages, or races, which reduces the risks associated with handling sensitive information. When publishing data, precautions are taken to aggregate and anonymize it, ensuring that no small cell-sized data can be considered PII.

The experts also highlight the potential impact of NIOCCS in the future, stating that as the system expands into more areas, the stakes could become higher. Work data is a key social determinant of health that should be consistently collected and available in electronic health records (EHRs). Coding work data could impact clinical decisions and other areas of clinical care in the future, emphasizing the need for responsible implementation of AI and advanced analytics.

**Advancing Innovation in Public Health**
Integrating AI and advanced analytics in public health departments represents a significant advancement not just in “back-office” tasks but also in disease prevention, surveillance, and response. These transformative technologies enable faster and more accurate decision-making, increasing overall efficiency. However, it is crucial to maintain a delicate balance between transparency and privacy protection. Robust privacy safeguards should be implemented, and open dialogue should be encouraged to ensure responsible and ethical use of technology and data in fostering a healthier and more informed society.

For more details and insights, refer to the GovFuture podcast on this topic.

**Note:**
Kathleen Walch is an Executive Director at GovFuture.