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How APIs Streamlined COVID-19 Case Reporting, Enhanced Data Quality

Automatic data transfer via an application programming interface (API) improved data quality for COVID-19 cases and death rates and reduced the COVID-19 case reporting process by over 25 minutes.

The use of application programming interfaces (APIs) overall enhanced the COVID-19 case reporting process, once integrated APIs improved the data quality of COVID-19 case and death numbers and decreased processing time, a recent study published in the Journal of the American Medical Informatics Association found.

Particularly during the pandemic, timely disease surveillance has been important to making decisions on interventions and crafting public health responses.

However, patient data exchange and public health reporting were two major health IT problem areas during the pandemic that needed to be addressed.

During the COVID-19 public health response, CDC created a system to track COVID-19 aggregate case and death data, known as aggregate case and death surveillance (ACS).

Initially, ACS was established to monitor the cumulative and daily number of COVID-19 cases and deaths recorded by the submission date.

Public health jurisdictions (PHJ) such as laboratories, healthcare providers, long-term care and correctional facilities, or contract tracers reported COVID-19 case and death data for ACS.

As PHJs revised the historical COVID-19 case and death data due to data reconciliation and updates, CDC came up with a process to update these records for better accuracy.

Starting in March 2022, CDC integrated APIs from three jurisdictions — California, Florida, and Tennessee — to automatically pull current and historical COVID-19 case and death data.

Automatic data transfer via APIs tremendously improved public health reporting.

“Our experience in using APIs for ACS may aid the development of a generic aggregate surveillance system for future public health emergencies,” Dida Khan, study co-author, said.

“CDC guidance on technical considerations include shared definitions and vocabularies; aligned processes such as frequency of reporting, availability of PHJ resources to setup an API, and to regularly refresh the dataset, which may be helpful to expand use in more jurisdictions.”

The use of APIs required less human intervention, which reduced the overall processing time from nearly 30 minutes to less than five minutes.

In addition, APIs boosted data quality as they reduced the opportunity for human error by using automated processes and reporting.

“The main appeal of going to an API as the middleman was the ability to incorporate 100 percent automation on our side,” the Tennessee Department of Public Health said in a public statement.

The study also noted that the use of APIs alleviated the burden placed initially on staff; by eliminating manual file transfers and data uploads, staff workload was decreased.

APIs helped ensure timely and accurate situational awareness of COVID-19 case and death data while enabling PHJs to have control of the data being viewed.

Ownership and stewardship of COVID-19-related data remained with PHJs without added intervention from CDC.

Lastly, APIs were also found to be highly adaptable for data transfers and can be implemented across a range of surveillance systems, saving developmental costs for PHJs.

On the downside, PHJs may require technical support, resources, and time to build and publish their APIs, which involves a fixed initial investment. 

“An API-based approach to pandemic surveillance provides both more accurate reporting and rapid incorporation of changes to COVID-19 case and death data when compared with the manual approach as discussed above,” the researchers stated. “Collectively, these benefits enable CDC to more frequently refresh COVID-19 case and death time series data than would be possible using only manual updates, and thereby more closely align CDC’s data to data presented on PHJ’s websites on a real-time basis.”

“These API benefits may contribute to future pandemic and other emergency response planning efforts by improving collaboration with PHJ’s and other data modernization initiatives,” the researchers concluded.

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