IWRS-EDC data reconciliation - You still do that manually ?!!!!!!

Where IVRS (interactive voice response system) or IWRS (interactive web response system) setups are required to manage the randomisation, subject enrollment and drug supply management in clinical trials. IWRS is gradually superseding many of the (manual) tasks that were performed over the phone, fax or with paper and provides users with the flexibility to collect information 24/7. The 24/7 ‘live’ nature of these systems provides study teams with an extremely powerful study aid if utilised to maximum potential, and in association with other platforms, such as EDC. It can help coordinate monitoring visits, detect recruitment issues earlier, highlight missing visits and, in terms of data management, highlights data entry backlogs and drives other data quality checks (eg, treatment and patient status checks). In essence, it can lead to efficient coordination and increased data quality.


However, in many cases these systems are not integrated into the EDC system and data reconciliation between systems is still required for consistency and accuracy.


In a world where we have 'seamless integration' across various platforms, this is one of those examples where inefficiency infiltrates back into the system and yet reconciliation is paramount for the success of the trial with randomisation errors having a pivotal impact - imagine a 20% mismatch in randomisation! It is usually the task of data management, often working with the Global/Clinical Trial Manager, to ensure that reconciliation occurs on a regular basis (at least monthly to ensure errors are fed back to sites, permanent issues are agreed with the study statistician and any updates are made where permissible). However, in many cases reconciliation is often left until very late on in the life of a clinical trial as it can be a resource-intensive activity that appears low on the pririty list. For many study set-ups, this is still being done manually.


Reasons for this being done manually include

  • no study budget for reconciliation

  • no programmer resource available

  • misconception that it's only a few fields to be reconciled

  • the data manager has the capability and resources to do this without any issues

  • listings provided bt a programmer/3rd party may be in a user-unfriendly format





















So what can appear to be a simple task only briefly discussed during study set-up discussions will often turn out to be a time-intensive activity upstream, which is then often left at the bottom of the DM task pile! The more data points that need to be reconciled the bigger the job, of course, and as the enrollment numbers increase the larger the burden becomes, especially with mounting other tasks that the data manager has to perform.


Users should not be eye-balling data in 2020!

How data managers reconcile will differ. Some will print and 'eye-ball' each record individually, others will copy and paste one extract into the other using Excel and others may use a concoction of Excel functions (like "Vlookup"). Not only are most of these error prone, but they are very time consuming and the reproducibility of the activity may be hard to explain upon inspection - imagine the data manager that still prints and highlights any differences spotted between the two extracts, patient by patient! We all know who these colleagues are! Since records may be changed (in the EDC at least), it also means that the records that were reviewed the month before (assuming we have a diligent data manager) would have to be re-reviewed from scratch, just in case a datapoint had changed! Imagine that being done on a monthly basis as the enrollment figures increase from a few hundred to a few thousand. In most cases, we simply know the task is not being performed to schedule.


Typical fields to reconcile:

  • Pt ID

  • Date of Rando

  • Arm (A/B/C)

  • Drug Taken date

  • Visit (SV domain) vs. IWRS visits

  • Patient Status (DS domain) vs. IWRS


Our reconciliation is done in SAS (or other mainstream system) - why would we consider something new?

From our experience, SAS outputs either in the form of SAS listings or Excel outputs can be daunting and, in many cases, cumbersome to negotiate for the end reviewer. These often are not complimented with technology to highlight new or changed records since prior outputs, or come with a way to merge data reviewer comments from old listings to the latest data extracts.


In our solution there is no need for the end user to review again those patients or datapoints that have been reviewed previously - our solution will only look at data that is either new or has been changed since the prior review and any ‘follow-up’ comments are stored.


This task is outsourced to our partner, why would we bring this in-house?

The outsourcing partner (eg, DM CRO) may only focus on their own task, but the sponsor remains the central hub for guidance and support of other partners and teams, such as operations and monitoring. The sponsor may not question how the review is undertaken until issues arise in the data and it may only be then that realisation sets in that reconciliation has been performed manually for the past 3 years under a hidden cost item in the budget "Data reconciliation". In summary, as part of sponsor oversight, there remains an onus on the sponsor to ensure not only that reconciliation has occurred but that it has been performed accurately, and can demonstrate for inspection-readiness/risk-based monitoring purposes that there was clear and regular oversight between systems.





How can we help you?


At Apples & Oranges we are able to customise an effective reconciliation tool which can:

  • Pull in data from your IWRS and EDC systems (format independent)

  • Self-administered by clinical team member; no programming experience required

  • Easily shows reviewer those data points that have a mismatch

  • Allows reviewer to add comments (useful if findings need to be communicated to wider team members such as clinician and statistician / storage of permanent issues)

  • Future data reconciliation will only require the user to review new or changed data - there is no need to re-review all data points again!

  • No need to use the dangerous ‘spot check’ strategy owing to the fully automated method

  • Data is provided in a user-friendly method - no steep learning curves!

  • Our solution harnesses existing Microsoft Office installations; no new software is required


All of our tools are developed with similar interfaces and functionality, which leads to a familiarity for our regular customers. Please view our PK reconciliation tool to have an understanding of the look and feel of our tools ).


Solutions can be provided across your portfolio or custom-built for each study. Please get in touch for more info.


Would you like to learn more? Please get in touch





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