Transforming Healthcare Together

AT A GLANCE

CLIENT: Humber Teaching NHS Foundation Trust

SERVICES: Data Migration

CHALLENGE: Successfully deliver data migration over three stages, moving Child and Adult Mental Health data for Humber Teaching from their legacy Lorenzo environment into their new EPR system.

OUTCOMES: Moved more than 150,000 points of patient data over an eight-month period using RPA, which would not have been possible in the timeframe if done manually.

CHALLENGE

Humber Teaching NHS Foundation Trust needed to migrate a significant number of Child and Adult Mental Health patient’s data from their legacy Lorenzo environment into their new electronic patient record (EPR) system in an 8-month period. Due to competing timeframes, this needed to be done outside of the normal delivery methods supported by the new EPR provider.

SOLUTION

With many EPR software providers, there are typically automated processes to move data from legacy systems into the new one. In this case, Humber planned to move to the new EPR before the resources to do this were available, which would have meant proceeding with no data in their new system or finding an alternative.

Based on the data sets and the existing and new systems involved, Cloud21 determined that the optimal way to deliver data migration services in the timeframe stipulated would be through the use of robotic process automation (RPA) tools. A plan was therefore conceived to deliver a prototype process that could substitute the requirement for a substantial number of manual migrators by utilising RPA technology. This process started with validating the tools and processes used complied with DCB0129 and DCB0160 specifications, ensuring any prototype or deployable product was clinically safe and within NHS Data Standards.

By working closely with the Humber BeDigital Programme team, Cloud21 was able to identify the key data types and activities that could safely and quickly be processed by RPA. This included removing from scope any items where the volumes to be moved did not justify the time needed to develop and train an RPA process. Any document types that contained a high number of variations or variables were also removed, as this would require a significant number of different processes, all of which would also need to be trained and tested to ensure accuracy. Finally, any data that was deemed too complex or not viable for RPA to be trained to do, was compiled by Cloud21 and passed to the data quality and manual migrating team who would manually check and add this information to the system in preparation of go-live. This work would then be monitored to ensure any additional information that needed to be added was picked up by the RPA process and delivered.

Finally, a review of the quality and availability of data was completed by the Trust team to ensure that RPA could accurately process data from the Lorenzo database in a way that would allow for transformation and load it into the new EPR system.

PROCESS

The development process was as follows.

Identifying the workflow process that was needed to enter data within the new EPR.
Document and develop the RPA process to mimic this process, identifying stop gaps and unknown system activity (error handling) which would stop the process.
Train and test the process with a singular RPA agent to ensure full end-to-end processing with test data.
Create underpinning tables that would hold the true patient data from which the RPA agent would read, locate and transpose the information.
Automate the process and error handling and increase scale of delivery from 1 RPA agent to 25.
Review log files for unexpected errors and identify appropriate corrections or pass to manual migration team if clinically or statistically relevant.
Validate processing and handover to client for sign-off.

OUTCOMES

Using the above process and the expertise of the team, Cloud21 was successfully able to deliver the data migration needed through the use of RPA. This work helped replace the need to manually move more than 150,000 points of patient’s health data over an 8-month period and ensured that the trust was ready and able to continue providing excellent mental health services to its patients without impact on their services.

"Humber had a well adopted EPR system previously, which meant we had a wealth of data to be migrated over to a new system. We were disappointed to find that processes hadn’t changed much since our last EPR implementation, so we knew we wanted to work with a company with a proven track record.

"One area of interest specifically was a robotic process, to move as much data as possible in a safe and efficient way. We recognised that there would still be some manual migration involved for us, but Cloud21 offered a great deal of expertise in this area, and we worked extremely well together on a less resource intensive solution. We supported this with extensive validation and testing, and together we reduced our timescales significantly."

- Julie Crockett, Deputy CIO, Humber Teaching NHS Foundation Trust

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