Data conversion is one of the most important parts of switching from one electronic health record (EHR) system to another. To make sure that critical data can be easily found and understood in the new EHR,¹ health systems must map both the legacy and new EHR systems to correctly label and transfer data. Historically, this process has been a challenge — a lack of healthcare data standardization has resulted in “messy” data, which can make the data conversion process difficult to plan, tedious, error-prone, and costly.  

How health systems deal with this challenge depends on many factors, such as system size, the capabilities of legacy and future EHRs, and available staffing. But while there is no silver bullet for converting EHR data,¹ there are opportunities for health systems to develop partnerships and adopt technologies that can make the process easier. For example, generative artificial intelligence (AI) can speed up certain data conversion activities.

This piece delves into four questions health systems should ask themselves before tackling EHR data conversion. It accompanies “How to effectively prepare for (and implement) an EHR switch”.