Could an Open-Source Clinical Trial Data-Management System Be What We Have All Been Looking For?

Kenya Medical Research Institute-Wellcome Trust Collaborative Research Programme in Kilifi, Kenya.
PLoS Medicine (Impact Factor: 14.43). 04/2008; 5(3):e6. DOI: 10.1371/journal.pmed.0050006
Source: PubMed


The authors argue that research organizations and funders should combine efforts to produce an open-source solution for trial data management.

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    • "This could include 1) nesting methodological research within studies to find optimal approaches or tools for questioning participants to obtain AEs and related data, 2) deciding whether to adopt an existing toxicity grading scheme from another therapeutic area or develop one for malaria endemic populations, or 3) developing guidance on use of a common causality assessment tool. User-friendly open access databases suitable for a range of study designs could also be developed collaboratively to help researchers manage their data efficiently [55]. Where appropriate these should incorporate harmonized fields and terminologies so that they may be used more widely in the non-commercial sector. "
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    ABSTRACT: Participant reports of medical histories, adverse events (AE) and non-study drugs are integral to evaluating harm in clinical research. However, interpreting or synthesizing results is complicated if studies use different methods for ascertaining and assessing these data. To explore how these data are obtained in malaria drug studies, a descriptive online survey of clinical researchers was conducted during 2012 and 2013. The survey was advertised through e-mails, collaborators and at conferences. Questions aimed to capture the detail, rationale and application of methods used to obtain relevant data within various study designs and populations. Closed responses were analysed using proportions, open responses through identifying repeating ideas and underlying concepts. Of fifty-two responses from 25 counties, 87% worked at an investigational site and 75% reported about an interventional study. Studies employed a range of methods to elicit, assess and record participant-reported data AE and related data. Questioning about AEs in 31% of interventional studies was a combination of general (e g, open questions about health) and structured (e g, reference to specific health-related items), 26% used structured only and 18% general only. No observational studies used general questioning alone. A minority incorporated pictorial tools. Rationales for the questioning approach included: standardization of assessment or data capture, specificity or comprehensiveness of data, avoidance of suggestion, feasibility, and understanding participants' perceptions. Most respondents considered the approach they reported was optimal, though several reconsidered this. Four AE grading, and three causality assessment approaches were reported. Combining general and structured questions about non-study drug use were considered useful for revealing and identifying specific medicines, while pictures could enhance reports, particularly in areas of low literacy. It is critical to evaluate the safety of anti-malarial drugs being deployed in large, diverse populations. Many studies would be suitable for contributing to a larger body of evidence for answering questions on harm. However this survey showed that various methods are used to obtain relevant data, which could influence study results. As the best practices for obtaining such data are unclear, anti-malarial clinical researchers should work towards consensus about the selection and/or design of optimal methods.
    Malaria Journal 09/2013; 12(1):325. DOI:10.1186/1475-2875-12-325 · 3.11 Impact Factor
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    • "Let us first consider electronic data capture. This is becoming increasingly common in developing countries and many more groups are using open source products such as OpenClinica for their data management and these systems facilitate electronic data capture.9 Other groups are increasingly using the rapidly advancing use of handheld internet devices to capture clinical trial data in developing countries.10–12 "
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    ABSTRACT: We need more clinical trials in the world's poorest regions to evaluate new drugs and vaccines, and also to find better ways to manage health issues. Clinical trials are expensive, time consuming, and cumbersome. However, in wealthier regions these limiting factors are being addressed to make trials less administrative and improve the designs. A good example is adaptive trial design. This innovation is becoming accepted by the regulators and has been taken up by the pharmaceutical industry to reduce product development times and costs. If this approach makes trials easier and less expensive surely we should be implementing this approach in the field of tropical medicine and international health? As yet this has rarely been proposed and there are few examples. There is a need for raising the awareness of these design approaches because they could be used to make dramatic improvements to clinical research in developing countries.
    The American journal of tropical medicine and hygiene 12/2011; 85(6):967-70. DOI:10.4269/ajtmh.2011.11-0151 · 2.70 Impact Factor
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    • "A large part of clinical centres uses their own developed solution or a single solution not used by any other centre. Open Source CDMS may be an alternative [13], but have not yet been introduced on a large scale so far. Only about 10% of centres use an Open Source solution including GCP BASE™, PhOSCo™, openCDMS™ (PsyGrid™) and EpiData™. "
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    ABSTRACT: The use of Clinical Data Management Systems (CDMS) has become essential in clinical trials to handle the increasing amount of data that must be collected and analyzed. With a CDMS trial data are captured at investigator sites with "electronic Case Report Forms". Although more and more of these electronic data management systems are used in academic research centres an overview of CDMS products and of available data management and quality management resources for academic clinical trials in Europe is missing. The ECRIN (European Clinical Research Infrastructure Network) data management working group conducted a two-part standardized survey on data management, software tools, and quality management for clinical trials. The questionnaires were answered by nearly 80 centres/units (with an overall response rate of 47% and 43%) from 12 European countries and EORTC. Our survey shows that about 90% of centres have a CDMS in routine use. Of these CDMS nearly 50% are commercial systems; Open Source solutions don't play a major role. In general, solutions used for clinical data management are very heterogeneous: 20 different commercial CDMS products (7 Open Source solutions) in addition to 17/18 proprietary systems are in use. The most widely employed CDMS products are MACRO and Capture System, followed by solutions that are used in at least 3 centres: eResearch Network, CleanWeb, GCP Base and SAS. Although quality management systems for data management are in place in most centres/units, there exist some deficits in the area of system validation. Because the considerable heterogeneity of data management software solutions may be a hindrance to cooperation based on trial data exchange, standards like CDISC (Clinical Data Interchange Standard Consortium) should be implemented more widely. In a heterogeneous environment the use of data standards can simplify data exchange, increase the quality of data and prepare centres for new developments (e.g. the use of EHR for clinical research). Because data management and the use of electronic data capture systems in clinical trials are characterized by the impact of regulations and guidelines, ethical concerns are discussed. In this context quality management becomes an important part of compliant data management. To address these issues ECRIN will establish certified data centres to support electronic data management and associated compliance needs of clinical trial centres in Europe.
    Trials 07/2010; 11(1):79. DOI:10.1186/1745-6215-11-79 · 1.73 Impact Factor
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