Workflow in Clinical Trial Sites and Data Quality Figure 5. The Workfow of all process simulated for three situations: Planned, with reword identified and wirh policies suggested. doi:10.1371/journal.pone.0039671.g005 ability, the former being achieved by the data collected at each site. Although we conducted our study in a developing country (Brasil), there is little evidence to suggest that the problems we describe are restricted to developing countries. Moreover, the low granularity of our system level recommendations is justified given its occurrence every time a new approach is applied to a field. Given that, to the best of our knowledge, this is the first study evaluating and mapping workflow at clinical trial sites while also simulating its results using System Dynamics. Finally, we make a substantial assumption that near-miss events are a proxy for real data quality events. This assumption was made given the qualitative nature of our study, where samples are frequently small and exploratory, therefore unable to reach results that would qualify as definitive. However, we would also like to point that an assumption of association between near miss and ‘‘real events’’ has been made in a wide range of the literature and ratified by entities such as the Institute of Medicine in its report ‘‘To err is human’’ [54]. In conclusion, in order to reduce rework and optimize trial performance, it is essential to improve the efficiency prevailing in trial sites. Clinical trial sites and sponsors should review and improve their standard procedures and manage human resource allocation to better address the workflow issues summarized in our study. Sponsors and site managers can improve support systems for CRCs. Although some interventions such as integration between EMR and EDC, might not seem cost-effective or even technologically possible at this time, strategic decisions should be made to facilitate their future integration. For example, when planning for an EMR system, hospital administrators should evaluate the ease of integration with external EDCs. Also, future research should integrate systems modeling simulation so that these changes can be constantly monitored and frequently evaluated in the quest for data quality excellence. As a future study we intend to submit a new manuscript about the new taxonomy for what should be compared in workflows across sites focusing on areas of dissonance between workflow and data quality. Supporting Information Supporting Information S1 List of all task categories found through the field notes. (DOC) Supporting Information S2 UML - Activity Diagram for pre-signature consent form process. (DOC) Supporting Information S3 UML - Activity Diagram for signature consent form and first visit. (DOC) Supporting Information S4 next visits. (DOC) UML - Activity Diagram for Supporting Information S5 Emergent themes main var- iables in Vensim simulation software. (DOC) PLoS ONE | www.plosone.org 9 June 2012 | Volume 7 | Issue 6 | e39671