QCRI’s Rayyan app a hit with foreign users
The system, first launched in September 2014, is being used by medical professionals, researchers, and public health officers to support evidence-based medicine and decide health guidelines.
A systematic review is a literature review that identifies, appraises, selects and synthesizes relevant evidence related to a research question. The kinds of health-related questions asked in systematic reviews have included whether high egg consumption is associated with the increased risk of coronary heart disease; whether evidence supports low-fat dietary recommendations or whether influenza medicines alleviate symptoms.
Rayyan identifies relevant evidence, selects studies for inclusion, assesses the quality of each study and interprets the findings in an unbiased way.
Rayyan’s lead scientist Mourad Ouzzani, who developed the system with Hossam Hammady, said as the amount of medical research exploded to 1.8 million articles in 20,000 journals per year, typical systematic reviews were taking researchers up to two years of work.
Ouzzani said it was becoming almost impossible for clinicians to keep up with the amount of research without using data analytics, particularly as much research was becoming quickly outdated. A recent survey of Rayyan’s users found the aggregated time saving for respondents was around 40 per cent.
“Rayyan is changing the way systematic reviews are produced and is dramatically reducing the time it takes for producing systematic reviews for a large number of users around the world,” Ouzzani said.
“It is responsive and quintessentially intuitive in use with significant potential to lighten the load of reviewers. By automating the production of systematic reviews, Rayyan is expediting the availability of current best evidence for policy and clinical decision-making.”
Testimonials from Rayyan’s users in the survey included: “It is a great feeling to work online and feel the burn. Some people like to job on their own … Rayyan is a bit like a jogging trainer.”
Another user said : “Can’t imagine a collaborative systematic review without Rayyan any more.”
Ouzzani said Rayyan’s success showed how basic research in data analytics, text mining and machine learning could be turned into a software product “with a proven impact on an important area related to public health, evidence-based medicine”.
Rayyan is available at http://rayyan.qcri.org
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