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Glossary: Real World Data

Real World Data (RWD): real data from real people in real environments.

Real world human data refers to subject orientated data captured without interference or bias (effectively noise) from the environment and methodology of the data collection itself.

The ISPOR Real-World Data Task Force considered “real-world data” as data used for clinical, coverage, and payment decision-making that are not collected in conventional randomized controlled trials (RCTs).

One dimension of the real-world data is type of outcome, a second dimension of real-world data is in terms of evidence hierarchies, a third dimension operationally categorizes real-world data by type of data source.

Real-world data has a lot of benefits but also have some important limitations, for all non-randomized data, the most significant concern is the potential for bias. This depends from the variable quality of all data (whether prospective or retrospective, or experimental or observational) so it is important that efforts follow well-established research practices.

A real good explanation of this topic, value and use, and issue on the ISPOR website:

How a good use of Real World Data may change pharma drug development: “With modern technology you can now capture real world data to measure the effectiveness of a drug in a real subject in the right environment, captured continuously at the right time, DURING the drug development phase. And now, the results you obtain will show the effectiveness of the drug in the real world.”

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