An interesting article on the communications of Data Trends from the Q4 SCDM Newsletter...
Finding and Communicating Data Trends Effectively Throughout a Clinical Trial
By Shelina Thomas, PharmaNet, LLC
Whether you work in Pharma or at a CRO, one of the key responsibilities as a data manager working on clinical trials is to ensure high data quality. As stated in Good Clinical Data Management Practices, "Data collected during a clinical trial must have as few errors as possible to be able to support the findings or conclusions drawn from that trial." One way data managers can work to ensure data quality is by identifying and communicating data trends. As such, data managers are challenged with identifying data trends and providing the project team with effective feedback throughout a trial.
While most data managers are familiar with reviewing data listings and validation output, they may not realize that these same review methods provide valuable information in identifying data trends.
Here are a few examples to illustrate this:
• Reviewing a concomitant medication listing will let the data manager know that the site properly recorded Tylenol for an adverse event. However, the same listing may also draw attention to the fact that a site consistently recorded Benadryl as a pre-medication for every subject.
• Reviewing a lab listing for out of range results is a common item for data review. The lab listing may also identify that some sites are consistently recording commas (,) in place of decimals (.), which are causing many lab results to fall out of range.
• Reviewing data listings can also detect potential fraud, such as noticing that many subjects at a site experienced the same adverse event on the same day, or that many subjects appear to share the exact same weight and height measurements.
Validation output, or reviewing discrepancies, identifies where data discrepancies are located. However, reviewing a validation "trigger count" report provides a complete look of all programmed edit specifications and is a quick way to pinpoint data trends. The "trigger count" includes the name of the edit check, how many times the edit check fired, and the number of times the discrepancy was issued as a data query to the site. It provides a wealth of information to the data manager and the project team, and may help in understanding which data field/CRF caused the most data queries, or by indicating where an edit specification may not be working properly.
For data managers working on a global trial, it is recommended that trends pertaining to a specific region or country be identified. For example, if it appears that an issue of repeating medications is frequently appearing for sites in India or Germany, that is constructive information that needs to be communicated to the team. This information will allow the team to understand where their attention should be focused, and enables them to drill down to the specific root of a problem.
Data trends should be shared with the project team as early as possible. Identifying these trends early, can indicate the need for additional CRA and/or site training, possible database and/or edit specification changes, or show the need for additional data cleaning. These can all have a financial impact on the trial regarding the amount of time spent performing data review, as well additional time spent by the CRA working with the site to correct CRF entries on site. Identified data trends may also show the need to update the CRF Completion Guidelines, which is often the best tool in helping the internal and external team understand how to record trial data within the CRF.
There are several ways to communicate data trends to a project team, and the data manager needs to consider the best method for communicating any data trends to his/her specific team. Holding a round table group discussion during a CRA/DM meeting is one way to accomplish this. However, for a global trial it is recommended to hold small group sessions with regional CRAs, which focuses on specific issues with their sites.
Providing specific information to the appropriate CRAs and choosing the best method of communication can be very productive for resolving data issues. Often times, data management will hold a general teleconference with all study CRAs to discuss data issues. If this type of meeting is not planned properly, it will not be productive. Sharing a lot of information at one time will often cause those invited to tune out and miss important information. Inviting a smaller group of CRAs to discuss issues that affect their specific sites will result in a more engaged audience and yield better results. Tailoring these meetings to address specific needs will also help the project financially in reducing the number of additional re-trainings that are required.
Other ways to communicate data trends include providing handouts or delivering Power Point presentations that summarize overall trends across the study. Whichever method is chosen, the data manager should ensure that his/her chosen method of communication is clear and concise, and that it provides suggestions and/or examples on how to eliminate these data trends. The data manager should also solicit comments from the CRAs on the CRF Completion Guidelines and/or edit specifications. As the CRAs have first-hand knowledge of working with the sites, they are able to provide beneficial feedback on what updates may be needed to these documents in order to improve the data trends.
Identifying and communicating data trends is an essential component of data management processes for all clinical trials and it plays an integral part in ensuring overall data quality. Review trends periodically to determine whether a reduction in frequency of identified issues has been noted. This will highlight whether the efforts made by the team have yielded the desired results. Team members and sites should be re-educated as needed, and CRF Completion Guidelines should be revised as necessary to include decisions made throughout the trial that affect CRF completion. For more information on whats going on in clinical trials, be sure to vist DZS's Knowledge Center at: http://www.clinplus.com/knowledge-center-resources