Workflow in Clinical Trial Sites & Its Association with Near Miss Events for Data Quality: Ethnographic, Workflow & Systems Simulation Elias Cesar Araujo de Carvalho1,2,3, Adelia Portero Batilana1, Wederson Claudino4, Luiz Fernando Lima Reis5, Rafael A. Schmerling5, Jatin Shah6,9, Ricardo Pietrobon7,8,9* 1 Research on Research Group, Department of Surgery, Duke University, Durham, North Carolina, United States of America, 2 Cesumar, Universitary Center of Maringa, Parana´, Brazil, 3 UEM, State University of Maringa, Parana´, Brazil, 4 Oncologistas Associados Cancer Institute, Rio de Janeiro, Brazil, 5 Institute for Teaching and Research, Sirio Libanes Hospital, Sa˜o Paulo, Brasil, 6 Research on Research Group, Duke-NUS Graduate Medical School, Singapore, Singapore, 7 Department of Surgery, Duke University Health System, Durham, North Carolina, United States of America, 8 Duke - NUS Graduate Medical School, Singapore, Singapore, 9 Research on Research Group, Duke University, Durham, North Carolina, United States of America Abstract Background: With the exponential expansion of clinical trials conducted in (Brazil, Russia, India, and China) and VISTA (Vietnam, Indonesia, South Africa, Turkey, and Argentina) countries, corresponding gains in cost and enrolment efficiency quickly outpace the consonant metrics in traditional countries in North America and European Union. However, questions still remain regarding the quality of data being collected in these countries. We used ethnographic, mapping and computer simulation studies to identify/address areas of threat to near miss events for data quality in two cancer trial sites in Brazil. Methodology/Principal Findings: Two sites in Sao Paolo and Rio Janeiro were evaluated using ethnographic observations of workflow during subject enrolment and data collection. Emerging themes related to threats to near miss events for data quality were derived from observations. They were then transformed into workflows using UML-AD and modeled using System Dynamics. 139 tasks were observed and mapped through the ethnographic study. The UML-AD detected four major activities in the workflow evaluation of potential research subjects prior to signature of informed consent, visit to obtain subjects informed consent, regular data collection sessions following study protocol and closure of study protocol for a given project. Field observations pointed to three major emerging themes: (a) lack of standardized process for data registration at source document, (b) multiplicity of data repositories and (c) scarcity of decision support systems at the point of research intervention. Simulation with policy model demonstrates a reduction of the rework problem. Conclusions/Significance: Patterns of threats to data quality at the two sites were similar to the threats reported in the literature for American sites. The clinical trial site managers need to reorganize staff workflow by using information technology more efficiently, establish new standard procedures and manage professionals to reduce near miss events and save time/cost. Clinical trial sponsors should improve relevant support systems. Citation: Araujo de Carvalho EC, Batilana AP, Claudino W, Lima Reis LF, Schmerling RA, et al. (2012) Workflow in Clinical Trial Sites & Its Association with Near Miss Events for Data Quality: Ethnographic, Workflow & Systems Simulation. PLoS ONE 7(6): e39671. doi:10.1371/journal.pone.0039671 Editor: David Joseph Diemert, The George Washington University Medical Center, United States of America Received May 13, 2011; Accepted May 29, 2012; Published June 29, 2012 Copyright: 2012 Carvalho et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Funding: The study was funded by Sanofi Aventis. The funder had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Competing Interests: This study was funded by Sanofi Aventis, with Mr. Carvalho and Batilana being directly compensated as consultants. Dr. Claudino is currently conducting clinical trials with Sanofi-Aventis. Dr. Reis is Chief Scientific Officer of CRC Sao Paulo. This does not alter the authors’ adherence to all the PLoS ONE policies on sharing data and materials, as detailed online in the guide for authors. * E-mail: rpietro@duke.edu Introduction While clinical trials have typically been conducted in developed countries such as the United States of America, developing countries have recently emerged as important new locations for clinical research [1]. In particular, the BRIC countries (Brazil, Russia, India and China) and VISTA (Vietnam, Indonesia, South Africa, Turkey, and Argentina), with their large and ethnically diverse populations, have become major players in the globalization of clinical research [2]. At the same time, pharmaceutical companies are differentiating clinical research capabilities across these countries to inform their investment decisions. Among the most important capabilities is the ability to deliver high quality data. As a result, efforts to improve and ensure the production of high quality data in all countries are essential for enhancing their competitiveness as viable locations for the conduct of clinical trials, especially in light of previous studies that have linked research in developing countries with lower levels of data quality [3]. Even usual errors in data acquisition and transcription during clinical trials can directly affect data quality, due to the additional effort necessary to correct possible errors and ensure an acceptable level of data quality. The typical example is that of a busy clinical research coordinator (CRC) who is not adequately trained to PLoS ONE | www.plosone.org 1 June 2012 | Volume 7 | Issue 6 | e39671