Choosing Between Manual & Automated EHR Data Conversion

The case for adoption of medical records is compelling. The use of EHR systems opens the door to opportunities for federal incentives. Furthermore, EHR systems can help protect healthcare organizations from fines while maintaining compliance. Additionally, when chosen, implemented, and used appropriately, EHR systems 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.

The last decade has seen significant growth in adoption of EHRs by healthcare organizations. A decade ago, around 90% of physicians updated their patient records by hand. By the end of 2014, 83% of physicians had adopted EHR systems. As the adoption of EHR systems has grown over the last 10 years, so too has the need to change systems due to physician dissatisfaction and mergers and acquisitions.

Many healthcare organizations have turned to a process known as EHR data conversion to maintain access to and integrity of legacy data. Understanding the differences between manual and automated EHR data conversion can be a challenge. Here, we explore the different types of EHR data conversion available to your organization.

What is EHR Data Conversion?

EHR data conversion is one of three primary options to move all data from a legacy EHR system to a new system. This is accomplished through a process known as ETL. During an ETL EHR data 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 be performed through manual data abstraction or automated data conversion.

Manual EHR Data Conversion

Manual EHR data conversion (chart abstraction) is the process where important information is collected from a patient’s medical record and transcribed into discrete fields or locations within the new EHR. This is a manual data entry effort where organizationally-defined, clinically relevant elements of data are collected from the legacy system and manually entered into the new target system.

Manual abstraction and data entry has a lower initial cost. However, costs exponentially increase with each record. Therefore, it is cost effective when the data set is small, but prohibitive in many instances when the data set includes greater than 30,000 records. Furthermore, this method of conversion is subject to a great deal of human error, and each record runs a significant risk of manipulation.

Automated Data Conversion

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 transformed, the conversion utility monitors 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.

EHR Data Conversion

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. While the initial cost is higher than a manual data abstraction, the additional costs associated with each record are substantially less. Therefore, it is cost prohibitive for smaller data sets, but cost effective for data sets greater than 30,000 records.

Automated data conversion is the most efficient and effective way to retain and access patient data in a new EHR. Health systems and medical practices have chosen this data conversion path for the following reasons:

• Reduced legal risk

• Clinical convenience

• Preservation of access to valuable data

• Faster decommissioning of legacy EHR

• Full utilization of new EHR

• Efficiency of a single system

• Increased patient interaction time

• No risk of data manipulation

• No delay in patient history retrieval

• Limited variable costs

Preparing for a data conversion? Download EHR Data Conversion Guide & Workbook!


Leave a comment