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In Academic medicine : journal of the Association of American Medical Colleges

PROBLEM : The COVID-19 pandemic has challenged health care systems in an unprecedented way by imposing new demands on health care resources and scientific knowledge. There has also been an exceedingly fast accumulation of new information on this novel virus. As the traditional peer-review process takes time, there is currently a significant gap between the ability to generate new data and the ability to critically evaluate it. This problem of an excess of mixed-quality data, or infodemic, is echoing throughout the scientific community.

APPROACH : The authors aimed to help their colleagues at the Rambam Medical Center, Haifa, Israel, manage the COVID-19 infodemic with a methodologic solution: establishing an in-house mechanism for continuous literature review and knowledge distribution (March-April 2020). Their methodology included the following building blocks: a dedicated literature review team, artificial intelligence-based research algorithms, brief written updates in a graphical format, large-scale webinars and online meetings, and a feedback loop.

OUTCOMES : During the first month (April 2020), the project produced 21 graphical updates. After consideration of feedback from colleagues and final editing, 13 graphical updates were uploaded to the center's website; of these, 31% addressed the clinical presentation of the disease and 38% referred to specific treatments. This methodology as well as the graphical updates it generated were adopted by the Israeli Ministry of Health and distributed in a hospital preparation kit.

NEXT STEPS : The authors believe they have established a novel methodology that can assist in the battle against COVID-19 by making high-quality scientific data more accessible to clinicians. In the future, they expect this methodology to create a favorable uniform standard for evidence-guided health care during infodemics. Further evolution of the methodology may include evaluation of its long-term sustainability and impact on the day-to-day clinical practice and self-confidence of clinicians who treat COVID-19 patients.

Gruber Amit, Ghiringhelli Matteo, Edri Oded, Abboud Yousef, Shiti Assad, Shaheen Naim, Ballan Nimer, Neuberger Ami, Caspi Oren