usually require. According to the CRC, the process was slow since, although she had undergone previous training, that training had occurred several months before and most study-related processes were new, requiring constantly re-checking to ensure information accuracy. Since the documentation was long and not easy to search, the whole workflow was significantly delayed, ultimately affecting the CRC’s ability to complete it on time. With this delay, some of the CRF completion was left to another person on staff, enhancing the probability of near miss events for data quality issues. Other unexpected tasks for which there is no automation also prevented that the CRC complete the protocol on time, such as accounting issues related to the appointment such as the CRC spending one complete morning solving financial problems related to the study. In addition, study manuals frequently were confusing and lacked appropriate usability as attested by confusion generated while the CRC attempted to interpret them. Preliminary Simulation Model The preliminary simulation model (Figure 1) envisioned the following three main emerging themes (S5) generating rework: 1) Lack of standardized process for data registration at source document, 2) Multiplicity of data repositories and 3) Scarcity of decision support systems at the point of research intervention. The model has the following features: (a) all emergent themes are represented as stocks (rectangle), (b) a blue arrow represents information input and (c) a red arrow represents some action that will limit the growth of a stock. The theme ‘‘lack of standardized processes’’ has as its central feature represented by a stock ‘‘CRF information accuracy’’. Aligned with our ethnographic findings, the variable representing ‘‘intermediate forms of documentation’’ has a negative influence over ‘‘accuracy of information’’. The variable ‘‘accuracy of information’’ will speed up the processing of CRF completion. In other words, the greater the ‘‘accuracy information’’, less delay in successfully completing CRFs we will have. Workflow in Clinical Trial Sites and Data Quality The second theme ‘‘multiplicity of data repositories’’ is represented by a stock of reliable CRF information. Aligned with our ethnographic observations, it was seen in the form of three types of data repositories of information that would lead to the same information in different formats (Word documents, spread- sheets in Excel and software applications like central pharmacy or laboratories). In our model, we simulated how data multiplicity would affect reliability of CRF information. In our model the variable ‘‘data repository multiplicity’’ is influenced by three distinct variables: ‘‘other applications’’ (laboratories application, central pharmacy application and others), ‘‘text editor files’’ (Word documents), and ‘‘spreadsheet files’’ (Excel documents). The variable ‘‘data repository multiplicity’’ has a negative effect on the variable ‘‘information reliability.’’ In other words, the greater the multiplicity of data sources, the less reliable the information and the greater the delay in successful completion of CRFs. The third theme ‘‘scarcity of decision support system at the point of research intervention’’ indicates that the current work- flows for filling out paper and computer-based CRFs are in need of a better decision support system. The model also contains a variable representing the ‘‘efficiency of a support system,’’ which positively impacts the speed in completing CRFs. Additionally, we can observe that the main variables of our model ‘‘intermediate forms of documentation’’, ‘‘data repository multiplicity’’ and ‘‘support of information’’ are influencing another variable called ‘‘Error Fraction’’. The variable ‘‘Error Fraction’’ is used in our model to represent the stocks – ‘CRF to Do’, ‘Rework’ and ‘CRF Completed’. It receives information from the left part of model, representing the three emergent themes and has a directly proportional relationship with the variable - ‘‘Rework’’ flow. This means that higher instances of ‘Error’ will generate more rework and as a result lesser CRFs will be completed. As we did not have access to real data, we made the following assumptions: the values for ‘‘intermediate of documents’’ and ‘‘multiplicity of data repositories’’ was simulated starting on zero and growing each six months until the limit of 20% and 30% Figure 1. System dynamics model showing the three major emerging themes identified and rework caused by these themes. Available for best visualization in http://goo.gl/XydTd. doi:10.1371/journal.pone.0039671.g001 PLoS ONE | www.plosone.org 5 June 2012 | Volume 7 | Issue 6 | e39671