Identification and mapping of worldwide sources of generic real‐world data

PHARMACOEPIDEMIOLOGY AND DRUG SAFETY(2019)

Cited 5|Views14
No score
Abstract
Purpose The demand for real-world data as supportive evidence to traditional clinical studies has increased in the past few years. The present study aimed to identify worldwide generic sources of real-world data and to assess completeness and suitability of selected real-world evidence (RWE) data sources to conduct prespecified research. Methods A systematic literature review was conducted to identify generic (non-disease specific) sources of real-world data in Medline and Embase from January 1, 2010 to September 8, 2015. Data sources used in observational studies were identified and summarized based on their geographical distribution and the type of data. In the next step, the selected data sources were critically evaluated for their completeness. Results A total of 10,069 identified publications were screened, leading to 2635 unique data sources across 102 countries. Europe had the maximum number of data sources (n = 1163) followed by United States (n = 578), and Asia, Middle East, and African Countries (n = 374). The most common type of identified data sources across all countries was structured data sources, ie, administrative databases and registries. Of the identified data sources, 300 were selected for further investigation. From the selected databases, similar to 50% had confirmed information on over 60% of the investigated variables, similar to 61% were suitable for epidemiological research, and 60% had possibility of linkage. Conclusions The present study applied a systematic literature review approach and identified available generic sources of real-world data worldwide, in addition to the United States and Europe, which are suitable for conducting pre-defined researches and support future RWE studies.
More
Translated text
Key words
database mapping,generic data sources,pharmacoepidemiology,real-world data,real-world evidence
AI Read Science
Must-Reading Tree
Example
Generate MRT to find the research sequence of this paper
Chat Paper
Summary is being generated by the instructions you defined