The concept of the Electronic Health Record (EHR), or the electronic record of patient information and physician encounters, dates back to the late 1960s. While progress was initially slow, the late 1990s and 2000s saw substantial progress toward adoption as a result of the convergence of technological advancements and new regulations. During the George W. Bush administration the budget for healthcare IT doubled, the National of Health Information Coordinator position was created, and there was a call for industry-wide adoption by 2014.
This call was supported by the American Recovery and Reinvestment Act (ARRA) in 2009. The ARRA contained the Health Information Technology for Economic and Clinical Health (HITECH) Act, which has resulted in additional federal investments in programs designed to motivate healthcare professionals to adopt these EHR systems and follow the concept of “meaningful use” by the year 2014.8 Starting in 2015, penalties began to be imposed on organizations that had not upgraded facilities to store medical records.
Beyond federal incentives, the case for adoption of medical records is compelling. When chosen, implemented, and used appropriately, they can make healthcare more efficient, less expensive, and improve the quality of care by making patients’ medical history easily accessible to all who treat them.
We have seen substantial growth in adoption of EHR systems in the last 10 years. Alongside that adoption, healthcare organizations have also seen an increased need to change EHR providers. The two largest reasons for changes in systems are dissatisfaction and mergers and acquisitions.
Healthcare organizations often spend months researching, selecting, and implementing a new EHR that best meets their needs. Each practice area and location might have different and unique requirements, which can make finding the right system a difficult task. However, once an EHR is selected, the real challenge becomes how to import legacy data into the new EHR and maintain its integrity.
Like the initial adoption of a system, changing systems is an enormous project. As these healthcare organizations work to adopt new EHR systems, patients continue to generate more and more data daily. In the US healthcare system, the volume of electronic data roughly doubles every two years. Determining how to maintain and store data from legacy systems while utilizing a new system can be extremely challenging.
Most healthcare organizations want legacy data incorporated into the new EHR system from day one. Out of the myriad of options available for guaranteeing data integrity, the best way to accomplish this is through an automated EHR data conversion.
What is EHR data conversion?
EHR data conversion is the process of moving data from your legacy EHR system to the new system. It is accomplished through a procedure known as ETL. During an ETL conversion, patient data is EXTRACTED from the legacy system, TRANSFORMED to align with the map created for the new system, and LOADED into the new system. EHR data conversion can either be performed manually or through an automated process.
To avoid the risk of manipulation in a manual data conversion, most health organizations opt for automated EHR data conversion when working with large sets of data. During an automated data conversion, not a single patient record is touched. Companies who specialize in healthcare data conversion should utilize a failsafe ETL methodology specifically designed to mitigate clinical risk.
In an automated conversion, source values are extracted from both the legacy (source) system and new (target) system to create a conversion map. That map is entered into a conversion utility software. Data from the legacy system is run through the conversion utility and transformed to meet the needs of the new system. While it is being transformed, the conversion utility is monitoring total errors, parsing errors, mapping misses, percent complete, date/time to finish, and success rate. After the data has met the standards, it is then loaded into the new system.
Given the complexity of the data and variety of potential solutions, one might suppose that handling legacy data when changing EHR systems would be a complex affair. In many ways, that is true. However, it doesn’t have to be. When a healthcare organization partners the strong internal leadership with expert external partners and data architects, successful conversions are likely.