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Suggested Citation:"References." Institute of Medicine. 2013. Sharing Clinical Research Data: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/18267.
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References

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Suggested Citation:"References." Institute of Medicine. 2013. Sharing Clinical Research Data: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/18267.
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Suggested Citation:"References." Institute of Medicine. 2013. Sharing Clinical Research Data: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/18267.
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Suggested Citation:"References." Institute of Medicine. 2013. Sharing Clinical Research Data: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/18267.
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Suggested Citation:"References." Institute of Medicine. 2013. Sharing Clinical Research Data: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/18267.
×
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Suggested Citation:"References." Institute of Medicine. 2013. Sharing Clinical Research Data: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/18267.
×
Page 82
Suggested Citation:"References." Institute of Medicine. 2013. Sharing Clinical Research Data: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/18267.
×
Page 83
Suggested Citation:"References." Institute of Medicine. 2013. Sharing Clinical Research Data: Workshop Summary. Washington, DC: The National Academies Press. doi: 10.17226/18267.
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Page 84
Next: Appendix A: Workshop Agenda »
Sharing Clinical Research Data: Workshop Summary Get This Book
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Pharmaceutical companies, academic researchers, and government agencies such as the Food and Drug Administration and the National Institutes of Health all possess large quantities of clinical research data. If these data were shared more widely within and across sectors, the resulting research advances derived from data pooling and analysis could improve public health, enhance patient safety, and spur drug development. Data sharing can also increase public trust in clinical trials and conclusions derived from them by lending transparency to the clinical research process. Much of this information, however, is never shared. Retention of clinical research data by investigators and within organizations may represent lost opportunities in biomedical research. Despite the potential benefits that could be accrued from pooling and analysis of shared data, barriers to data sharing faced by researchers in industry include concerns about data mining, erroneous secondary analyses of data, and unwarranted litigation, as well as a desire to protect confidential commercial information. Academic partners face significant cultural barriers to sharing data and participating in longer term collaborative efforts that stem from a desire to protect intellectual autonomy and a career advancement system built on priority of publication and citation requirements. Some barriers, like the need to protect patient privacy, pre- sent challenges for both sectors. Looking ahead, there are also a number of technical challenges to be faced in analyzing potentially large and heterogeneous datasets.

This public workshop focused on strategies to facilitate sharing of clinical research data in order to advance scientific knowledge and public health. While the workshop focused on sharing of data from preplanned interventional studies of human subjects, models and projects involving sharing of other clinical data types were considered to the extent that they provided lessons learned and best practices. The workshop objectives were to examine the benefits of sharing of clinical research data from all sectors and among these sectors, including, for example: benefits to the research and development enterprise and benefits to the analysis of safety and efficacy. Sharing Clinical Research Data: Workshop Summary identifies barriers and challenges to sharing clinical research data, explores strategies to address these barriers and challenges, including identifying priority actions and "low-hanging fruit" opportunities, and discusses strategies for using these potentially large datasets to facilitate scientific and public health advances.

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