Mayo, CDC Leaders: Policy, Coalitions Key Barriers to Data Modernization

To prepare for the next pandemic, healthcare leaders believe that data modernization is key, but several challenges stand in the way, including conflicting policies, lack of interoperability, and the workforce shortage.

At the Association of State and Territorial Health Officials (ASTHO) Public Health TechXpo conference earlier this week, various public and private health organizations shared their strategies for achieving data modernization in the coming years beyond the COVID-19 pandemic.

John D. Halamka, MD, president of Mayo Clinic Platform, gave a keynote address on the second day of the conference, during which he discussed the data problems that the COVID-19 pandemic revealed and how modernization can solve those problems at the local, state, and federal levels.

Halamka noted that healthcare organizations need data to effectively deliver the highest quality supplies and care across systems, but there are multiple challenges that prevent data gathering, standardization, and sharing, including conflicting state and federal policies.

“The challenge in the US is we do not have a single set of policies. What we have is a quilt of state and local policies that overlay federal policy and sometimes override federal policy… So, there is work to do to instrument the country for what will come next, whether that's COVID or flu or something else, [in terms of] standards to work on and policy to harmonize,” Halamka stated.

Alongside policy, modernizing US infrastructure for the next pandemic will require a guiding coalition of local and state health departments, the Centers for Disease Control and Prevention (CDC), health providers, and other public and private partners, Halamka said. Such coalitions were formed during the early days of the pandemic, which allowed for the development of exposure notification technology that is still being used today.

Technical challenges have also prevented data modernization. IT infrastructure systems vary significantly across public health organizations, and many of them are not interoperable, are difficult to maintain, and challenging to integrate. A scalable, standards-based federation of systems that does not require large amounts of manual intervention to work is needed, according to Halamka. A larger number of interoperable data standards are also necessary to facilitate efficient collaboration and allow coalitions to leverage data.

Further, issues related to the dwindling workforce in healthcare and health IT over the course of the pandemic severely limit progress toward data modernization, Halamka noted.

Efforts to replenish and strengthen that workforce is a key aspect of the CDC’s data modernization strategy. At the conference, Leslie Ann Dauphin, PhD, director of the Center for Surveillance, Epidemiology, and Laboratory Services at the CDC discussed the organization’s plans to coordinate people and systems, support strategic innovation, and accelerate data for action. To achieve these ends, the CDC has launched the Data Modernization Initiative (DMI).

The CDC’s data modernization efforts center around three areas: data, the workforce, and policy levers, Dauphin said. In terms of data, the CDC is currently working to upgrade its core systems and capabilities while helping state, territorial, tribal, and local organizations do the same. Efforts to support workforce recruitment, retention, and training are also underway, alongside plans to implement a new grant program under the American Rescue Plan that will help bolster these efforts.

In addition, Dauphin noted that policies surrounding appropriate data use and data sharing are also key to the DMI’s success.

However, the uncertainty of public health visibility in the future and lack of sustained funding are challenging the CDC’s efforts.

"One of the things that we have received as a result of the pandemic is huge visibility on the world of public health… It's still headline news, but that will likely end someday. And so, how do we continue to keep that interest in, you know, public health so that we have really this broad initiative of everyone working together?" Dauphin explained.

The funding that the CDC receives is often reactive and designed to address the current need during a health crisis like COVID-19, she added. This means that in previous years, there has been under-investment in the CDC, which hampers the agency’s current data modernization improvement efforts.

Overall, speakers highlighted that technology is not the main issue preventing data modernization. Funding, workforce, education, security, policy, and the need for more coalition-building present the biggest challenges for data modernization efforts across the US healthcare system.

Despite this, both Halamka and Dauphin pointed to culture shifts that are changing the way people interact with public health and how public health organizations can work to overcome challenges.

Working together is what will allow the healthcare industry to strengthen public health and data modernization, they said. But without collaboration, organizations will have to pick and choose how they prioritize their efforts.  

“We can do anything. We just can’t do everything,” Halamka said in his closing remarks.