When healthcare organizations change EHR systems, they must consider many factors. Without proper planning and support, they risk making costly mistakes. Choosing a trusted advisor and partner streamlines the process and delivers positive outcomes for providers, patients, and the organization. Patient data is the key to solving many of the challenges facing healthcare today. It is important to put together a plan and work with a partner that will ensure its integrity. EHR data conversion services is the process of taking data from a legacy electronic health record system and transferring it to a new system.
This process, commonly called ETL, involves EXTRACTING patient data from the legacy system, TRANSFORMING it to fit the mapping for the new system, and LOADING it into the new system.
Two Methods for EHR Data Conversion
Manual Abstraction
Chart abstraction involves collecting essential information from a patient’s medical record and entering it into discrete fields or locations within the new EHR. This process requires manually transcribing organizationally-defined, clinically relevant data elements from the legacy system into the target system.
While manual data abstraction has a lower initial cost, its expenses increase exponentially with the number of records. It proves cost-effective for small data sets but often becomes prohibitive when the data set exceeds 30,000 records. Additionally, this method is highly prone to human error, with each record carrying a significant risk of manipulation.
Automated Data Conversion
In an automated conversion, the system extracts source values from the legacy system and transforms them to match the specifications of the new system. This process creates a conversion map that aligns legacy system values with the target system’s data format. The map is then loaded into conversion utility software, which transforms the data and applies the conversion specifications to all legacy records. This ensures the target system can properly ingest and display the legacy data. Throughout the transformation process, the conversion utility monitors total errors, parsing errors, mapping misses, percent complete, estimated completion time, and success rates. Once the data meets the required standards, it is loaded into the new system.
During an automated data conversion, no patient record is manually touched. Companies specializing in healthcare data conversion services should employ a failsafe ETL methodology specifically designed to minimize clinical risk.
Although the initial cost of automated conversion is higher than manual data abstraction, the per-record cost is significantly lower. This makes automated conversion cost-effective for datasets exceeding 30,000 records, though it may be less practical for smaller data sets.
EHR Data Conversion Process
1. Discovery
During the discovery phase of the process, your team will play a large role. Keystone will extract in scope data from the legacy system or work with your internal IT staff to gain access to the data from the current system. Keystone collaborates with your designated leader, IT staff, and Physicians Advisory Committee (PAC) to identify the available data, determine which data needs conversion, and assess the accuracy of the legacy data.
2. Scope Definition
In the scope definition phase, both parties agree on the portions of data to convert, the conversion method, and data prioritization. During this time, the teams schedule reviews of the records, format them to meet new requirements, and establish processes to update record fields excluded from the conversion.
3. Testing
After fully defining the scope and understanding the formatting requirements, the vendor takes primary responsibility for the conversion. Using input from the scope definition step, the vendor’s data architect maps data fields and formatting from the old system to equivalent fields and formats in the new system. Once the map is complete, the data architects upload the test conversion data to a testing environment.
4. Validation
This step is a shared responsibility between you and Keystone. After loading the data into the test environment, the data architect evaluates it. Then your team reviews the content, validates the records, and signs off on the final data set. This step may require several cycles and is imperative for the success of the conversion.
5. Migration
After validating the data, Keystone executes the final migration. During the migration, Keystone’s conversion utility monitors total errors, parsing errors, mapping misses, percent completion, estimated finish time, and success rates. Once all data is converted and migrated to the new system, your new EHR goes live!
Extract-Transform-Load (ETL) Conversion Methodology
Data Security as the Foundation
Keystone’s ETL methodology begins with the security of the data in mind. All extracted data will remain within a client’s secure internal network under any security policies and procedures that are in place for the client. We accomplish this by making use of development devices placed on the local network, such as VM’s and servers to perform the ETL work onsite. Local and remote VPN access to these devices provides the ability to perform work onsite, whether actually onsite, at the client site, or working remote.
Access to Accurate Data
Key to the success of any automated data conversion is full access to the data, whether the actual database itself, a restored backup of the database, or access to a report-writing tool that the client has in place for data access. Our clients experience the greatest success when testing actual production data rather than test data. Test data does not typically follow complete workflows as records set up in test environments are to test specific items and leave other required items non-populated.
Framework for Data Transformation
Our ETL framework transforms extracted data into the receiving system’s import specifications which can include direct database loading, generations of HL7 or CCD formats, or produce flat-files for loading into the target system. This framework also logs all modifications made to the data and flags any errors that could prevent a record from successfully loading. These logs help generate lists of items that require terminology mapping to align with target system values.
Comprehensive Testing and Validation
We ask clients to provide resources to thoroughly test the converted data before concluding any data conversion project, ensuring it resides in the new system as intended. We also require sign-off on the testing giving us permission to load the data into the New production environment.
Supporting Healthcare’s Evolving Needs
As the healthcare industry prepares for the aging population, a shortage of providers, increased need for chronic disease management, and financial pressures, technology and data are becoming ever more important. As a result, healthcare organizations that take steps to prepare for these changing demographics, prioritize physician satisfaction, and utilize systems to improve care coordination will require a strong IT partner.
The Importance of Choosing the Right Partner
EHR’s have already proven that they have a positive impact on patient care. However, many providers have expressed dissatisfaction with their current EHR provider. Furthermore, the industry is experiencing a merger and acquisition movement. These two trends are driving the need for EHR data conversion services for many healthcare organizations.
Not all EHR data conversion vendors are the right partner for you. It is important that you find a partner who values your data, can meet your needs, and will deliver a successful conversion.
