Clinical Data Managers Should Do These Three Things for Any Post-Production Changes

Post production changes in clinical data management can be difficult to navigate, and a lack of talented pharmaceutical industry resources has driven up demand for Clinical Data Managers . In the last 4 years alone, massive growth has come for clinical data managers resulting in a more than 93 percent growth rate according to Recruiter.com. Those who understand what do with difficult tasks, like dealing with post-production changes (PPCs) or mid-study updates (MSUs) after a clinical database has gone live, or into the production environment, are scarce.
Post-production changes (PPC) in clinical data management often include changes to forms, structures, fields and/or edit checks, and they can be attributed to planned or unplanned updates, meaning:
-
- Planned post-production changes (PPCs) refer to study specific updates that were known by a clinical data manager in advance or specified in the clinical study protocol or an amendment; and
- Unplanned post-production changes (PPCs) refer to updates not included in the clinical study protocol and are needed for reasons that may include Sponsor requests or misinterpretation of, or new knowledge about, the clinical study protocol.
In either case, a post-production change (PPC) can result in a disruption of the clinical study and present many challenges to the timelines and budget. In speaking from experience, and further with other Clinical Data Managers at MMS, there multiple ways to navigate these challenges.
Anticipate potential post-production changes
In the clinical data management environment, a post-production change (PPC) or mid-study update (MSU) is almost inevitable in the evolving pharmaceutical industry. Thus, clinical data managers can anticipate and plan for these possible updates to mitigate the risk of the post-production change (PPC) derailing timelines.
We recommend that clinical data managers:
- Identify possible updates before go-live,
- Consider the time it will take to implement a post-production change (PPC), should it be required, and
- Include buffer timelines in the planning in case of added issues.
As with any project, clear communication and setting expectations for timeline impacts is crucial and should be done before commencing with any post-production changes (PPC).
Justification, impact assessment, and validation
A solid justification for the post-production change (PPC) must be provided. Clinical data managers should ask, “why is the update necessary?”
Once this question is answered, the next important consideration is the impact of the post-production change (PPC). What impact will this update have on clinical data that is already present in the database? On top of this, it needs to be stated if the update will apply to existing data or only to newly-entered data.
All post-production changes (PPC) will need to be validated through user acceptance testing (UAT). If the update is applicable to existing and new data, then it is worth considering a test of the post-production change (PPC) on a live copy of the clinical study first. This will help in assessing the impact of the changes on existing clinical data.
Clinical data managers need to maintain the integrity of clinical data
Any updates to the already existing database could undermine the integrity of the clinical data.
For this reason, it is vital that clinical data managers follow an exact process, ensuring that all steps are documented thoroughly. It is equally important to consider the electronic data capture (EDC) software being utilized for the study, as there are limitations with many individual systems.
Approval by other teams is also key. Have any post-production changes (PPC) approved by Programmers and Statisticians to ensure data integrity in exports and gain confirmation that primary or secondary outcomes are not negatively impacted.
Post-production changes (PPC) can come with numerous obstacles. Yet, with proper planning and understanding of the necessary steps to take, clinical data managers can seamlessly integrate the updates into the ongoing database and train new data management professionals to fill pharmaceutical industry needs along the way.
Please click here to start a conversation with a clinical data manager about post-production changes (PPC) or if you have any questions related to this article.
Authored by:
Minya Engelbrecht, Data Team Lead, Biometrics.
Suggested For You

perspectives
July 23rd, 2024
PSI 2024 Ignited Conversations on External Data Sources, Requirements for Estimands, and Bayesian Methodology for Statisticians in Pharma

perspectives
December 27th, 2023
Clinical Data Science: Five Ways it Evolved from Clinical Data Management

perspectives
October 17th, 2023
Proven Ways to Meet Key Study Start-up Timelines within Clinical Data Management

perspectives
March 16th, 2023
10 Things to Consider When Discussing and Planning a Decentralized Clinical Trial (DCT)

perspectives
October 19th, 2022
eCOA and ePRO: Embrace Accurate and Efficient Real-Time Electronic Data Collection

perspectives
December 6th, 2018
Ask the Expert: Clinical Data Management Standards, Benefits, and its Future

perspectives
June 6th, 2024
Datacise and Diversity in Patient Enrollment: Combining Geospatial and Demographic Data to Aid Site Selection

perspectives
April 29th, 2024
Validation of Clinical Dashboards for Decision Making

perspectives
December 14th, 2023
Data Provenance in Real World Evidence Studies, Explained!

perspectives
October 24th, 2023
How to Find the Right CRO to Support Your Data Management Needs

perspectives
September 28th, 2023
What You Need to Know About Phase 1 Clinical Trial Designs and Bioequivalence (BE)/Bioavailability (BA) in the US and EU

perspectives
September 8th, 2023
FDA and the Real-World: Key Changes from Draft to Final Guidance on RWD and RWE