Towards clinical data-driven eligibility criteria optimization for interventional COVID-19 clinical trials | Zendy

Jae Hyun Kim | Zendy; Casey Ta | Zendy; Cong Liu | Zendy; Cynthia Sung | Zendy; Alex Butler | Zendy; Latoya A. Stewart | Zendy; Lyudmila Ena | Zendy; James R. Rogers | Zendy; Junghwan Lee | Zendy; Anna Ostropolets | Zendy; Patrick Ryan | Zendy; Hao Liu | Zendy; Shing M. Lee | Zendy; Mitchell S.V. Elkind | Zendy; Chunhua Weng | Zendy

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Towards clinical data-driven eligibility criteria optimization for interventional COVID-19 clinical trials

Author(s) -

Jae Hyun Kim,

Casey Ta,

Cong Liu,

Cynthia Sung,

Alex Butler,

Latoya A. Stewart,

Lyudmila Ena,

James R. Rogers,

Junghwan Lee,

Anna Ostropolets,

Patrick Ryan,

Hao Liu,

Shing M. Lee,

Mitchell S.V. Elkind,

Chunhua Weng

Publication year - 2020

Publication title -

journal of the american medical informatics association

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 1.614

H-Index - 150

eISSN - 1527-974X

pISSN - 1067-5027

DOI - 10.1093/jamia/ocaa276

Subject(s) - covid-19 , clinical trial , medicine , medical physics , computer science , virology , disease , infectious disease (medical specialty) , outbreak

This research aims to evaluate the impact of eligibility criteria on recruitment and observable clinical outcomes of COVID-19 clinical trials using electronic health record (EHR) data.

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