Industry Metric Indicates Low ROI with Full Source Document Verification
There's a rapidly growing trend towards targeted (or risk-based) site monitoring and data review. However, some organizations remain concerned about the potential impact on data quality.
SPOTLIGHT EVENTRisk-Based Monitoring – Part Two In Depth ReviewMarch 13, 2014
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There's a rapidly growing trend towards targeted (or risk-based) site monitoring and data review. However, some organizations remain concerned about the potential impact on data quality resulting from an approach that includes a reduced overall rate of source document verification (SDV) and other data reviews.
One question Medidata asked in this regard is: What percent of data is actually corrected during the course of a typical study as a result of the intensive manual data reviews conducted by sponsor personnel?
To help answer the question the company computed the Post-Capture eCRF Data Correction Rate across hundreds of studies in the Medidata Insights metric warehouse, which draws operational data from more than 50 contributing sponsors. The metric provides the percentage of all eCRF data fields that were observed to have one or more updates following the initial data entry session at the site. The data entry session was defined as a four-hour window following submission of each eCRF form, during which any observed data corrections would be triggered only by programmed auto-queries in the eCRF and not by manual data reviews (e.g., SDV, data management reviews, and safety reviews, etc.).
The graph reveals a rather astounding result - overall just less than 3% of eCRF data is updated after the initial capture session. Put another way, over 97% of all data provided in the study eCRF is in its final form - ready for analysis, reporting, and submission - before any site monitor or data manager reviews the data.
This data is even more compelling when you consider that this metric reflects all data updates, not just corrections but also "natural" updates to time-based patient event data. An example would be an update to the adverse event (AE) outcome fields once an ongoing AE has been resolved. Thus, it is quite apparent that significantly less than 3% of data is actually corrected.
So why are we manually scouring up to 100% of eCRF data - at an incredible cost in resources and time - for such a meager return?
As always, Medidata is interested to hear your take on this result. Please stay tuned as the company delves further into the Insights metric data through 2012.
- Medidata Solutions, www.mdsol.com
