Impact of a targeted monitoring on data‐quality and data‐management workload of randomized controlled trials: A prospective comparative study

Abstract

AimsMonitoring risk‐based approaches in clinical trials are encouraged by regulatory guidance. However, the impact of a targeted source data verification (SDV) on data‐management (DM) workload and on final data quality needs to be addressed.MethodsMONITORING was a prospective study aiming at comparing full SDV (100% of data verified for all patients) and targeted SDV (only key data verified for all patients) followed by the same DM program (detecting missing data and checking consistency) on final data quality, global workload and staffing costs.ResultsIn all, 137 008 data including 18 124 key data were collected for 126 patients from 6 clinical trials. Compared to the final database obtained using the full SDV monitoring process, the final database obtained using the targeted SDV monitoring process had a residual error rate of 1.47% (95% confidence interval, 1.41–1.53%) on overall data and 0.78% (95% confidence interval, 0.65–0.91%) on key data. There were nearly 4 times more queries per study with targeted SDV than with full SDV (mean ± standard deviation: 132 ± 101 vs 34 ± 26; P = .03). For a handling time of 15 minutes per query, the global workload of the targeted SDV monitoring strategy remained below that of the full SDV monitoring strategy. From 25 minutes per query it was above, increasing progressively to represent a 50% increase for 45 minutes per query.ConclusionTargeted SDV monitoring is accompanied by increased workload for DM, which allows to obtain a small proportion of remaining errors on key data (<1%), but may substantially increase trial costs.

Impact of monitoring approaches on data quality in clinical trials

“…The analysis included an evaluation of the query burden in both monitoring strategies and found that significantly more queries were made in the targeted SDV strategy, which had impact on the DM and site staff burden. By different estimates of the time spent per query, the authors conclude that the additional query burden alone may increase the total trial cost with little or no benefit in trial data quality as a whole 10 …”

“…A prospective study comparing full SDV vs targeted SDV not only found that full SDV yielded few improvements in terms of residual data errors but also found that the workload for data management (DM) teams was higher in the targeted SDV group. The latter observation is relevant as it indicates that the workload is shifted from on‐site monitor to DM and, depending on the time needed for query resolution, may have a positive or negative impact on the total cost of the study 10 . Together these studies fulfil the updated GCP guidelines, but no large‐scale empirical data comparing a CM with a fully implemented RBM approach have to the knowledge of the authors been published 11 …”

Monitoring advances including consent: learning from COVID-19 trials and other trials running in UKCRC registered clinical trials units during the pandemic

“…The collection of non-essential data has long been known to increase the burden on both participating sites and sponsors, and this is now starting to be quantified. Recent data from Fougerou-Leurent et al [ 14 ] suggest that only 13% of the data collected are critical data items and Crowley et al [ 15 ] found 5% of items were for the primary outcome of the trial.…”

Monitoring Advances Including Consent; Learning from COVID-19 Trials and Other Trials Running in UKCRC Registered Clinical Trials Units During the COVID-19 Pandemic

“…The collection of non-essential data has long been known to increase the burden on both participating sites and sponsor teams, and this is now starting to be quanti ed. Recent data from Fougerou-Leurent et al (12) suggest that only 13% of the data collected are critical data items and Crowley (13) at al found 5% of items were for the primary outcome of the trial.…”