Transformation Directorate

Health Records team use Robotic Process Automation to clear backlog of 40,000 documents

Background

Following the merger of Staffordshire and Stoke-on-Trent Healthcare NHS Foundation Trust and South Staffordshire and Shropshire Healthcare NHS Foundation Trust, the newly formed Midlands Partnership NHS Foundation Trust became the second largest community and mental health Trust in the country.

Having grown in size, the Trust experienced a significant increase in the volume of work within the Health Records team.

Situation

Due to the increased size of the Trust, the Health Records team reported a backlog of 40,000 documents to be scanned and added to patient files.

If processed manually each of these would take 3-4 minutes, equating to one person working 170 days to clear the backlog.

As well as the heavy administrative burden on the team, the backlog also meant that it may take weeks for some clinical records to appear on the system, which carried a certain level of risk.

Aspiration

The Trust wanted to automate the scanning and processing of these documents. This would free up staff from these high volume, repetitive tasks and allow them to focus on other business critical processes, whilst clearing the backlog.

Solution and impact

Midlands Partnership NHS Foundation Trust worked with NDL, deploying its NDL Automate Robotic Process Automation platform to automate this process.

The platform uses software robots that takes a PDF file produced from the scanned document and searches the Electronic Patient Record system, attaching the document to the correct patient file.

The robots replicate the steps that the Health Records team take when processing the scanned documents, ensuring a strict business logic dictates the robot’s actions. The team conducts ad hoc audits on the records to ensure the integrity of the process.

By using this platform, the process time was reduced from the original 3-4 minutes to less than a minute - a time saving of 75%.

The Trust also noted the following benefits:

  • The backlog of 40,000 documents was cleared.
  • Since clearing the backlog, the robots could process between 200-300 files per day, ensuring no backlog was created, improving real-time data quality and reducing risk.
  • Staff members have been able to redirect their time towards tasks more beneficial to the Trust, such as Freedom of Information requests.

Functionality

The NDL Automate platform:

  • Picks the scan files up from a shared drive.
  • Navigates the Electronic Patient Record system and attaches scanned documents to the correct patient file.

Capabilities

  • Patient documentation can be processed faster.
  • Backlogs of documentation can be avoided.
  • Staff can redirect their time to other tasks.

Scope of capacity

Robotic Process Automation for document scanning could be used in a wide range of settings in which large quantities of documentation are dealt with, especially where there is a need to clear a backlog or create more agile systems.

Key learning points

One of the key lessons during this process was to get the machines right that would be running the software and performing the RPA.

We had to use physical machines due to needing physical smartcards. We then also had to ensure that the machines were secured and always available. Ensuring that the machine was always logged in and never went to a sleep state.

We also had to ensure we could build in recovery methods that meant should there be an unknown issue the robot could cleanly close off all processes and start again.

Overall though the biggest learning was that we could achieve automation that we didn't think was possible within our core clinical system.

Key figures/ quotes

The process time was reduced from the original 3-4 minutes per scan to less than a minute - a time saving of 75%.

Find out more

NDL Automate: Robotic Process Automation

Key contact

Shaun Allcock, Head of Application Development, Midlands Partnership NHS Foundation Trust
Shaun.Allcock@mpft.nhs.uk

Tom Wright, Head of Digital Engagement, NDL
tom.wright@ndl.co.uk

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Page last updated: October 2022