Richer real world data insights can drive smarter decisions.
real world data (RWD)</a> becomes more important in regulatory and reimbursement submissions, agencies are focusing on the quality of the RWD sources and whether the generated evidence can be used appropriately to support decision making. </p> <p> However, it is unlikely that there will be a one-size-fits-all approach to choosing RWD, as selection will be based on the research question, the stage of product development, and the requirements of the target audience. </p> <p> In this paper, we present an approach for reviewing a real world dataset to see whether it can provide sufficiently high-quality evidence to justify the effort and expense of accessing it and performing the research. </p>" /> real world data (RWD)</a> becomes more important in regulatory and reimbursement submissions, agencies are focusing on the quality of the RWD sources and whether the generated evidence can be used appropriately to support decision making. </p> <p> However, it is unlikely that there will be a one-size-fits-all approach to choosing RWD, as selection will be based on the research question, the stage of product development, and the requirements of the target audience. </p> <p> In this paper, we present an approach for reviewing a real world dataset to see whether it can provide sufficiently high-quality evidence to justify the effort and expense of accessing it and performing the research. </p>" />
Developing IQVIA’s positions on key trends in the pharma and life sciences industries, with a focus on EMEA.
Learn moreDeveloping IQVIA’s positions on key trends in the pharma and life sciences industries, with a focus on EMEA.
Learn moreDeveloping IQVIA’s positions on key trends in the pharma and life sciences industries, with a focus on EMEA.
Learn moreDeveloping IQVIA’s positions on key trends in the pharma and life sciences industries, with a focus on EMEA.
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SEARCH JOBSAs real world data (RWD) becomes more important in regulatory and reimbursement submissions, agencies are focusing on the quality of the RWD sources and whether the generated evidence can be used appropriately to support decision making.
However, it is unlikely that there will be a one-size-fits-all approach to choosing RWD, as selection will be based on the research question, the stage of product development, and the requirements of the target audience.
In this paper, we present an approach for reviewing a real world dataset to see whether it can provide sufficiently high-quality evidence to justify the effort and expense of accessing it and performing the research.
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Richer real world data insights can drive smarter decisions.
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