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Peer Reviews (210)

Published on in Vol 2, No 3 (2021): Jul-Sep

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/31551, first published .
Peer Review of “Finding Potential Adverse Events in the Unstructured Text of Electronic Health Care Records: Development of the Shakespeare Method”

Peer Review of “Finding Potential Adverse Events in the Unstructured Text of Electronic Health Care Records: Development of the Shakespeare Method”

Peer Review of “Finding Potential Adverse Events in the Unstructured Text of Electronic Health Care Records: Development of the Shakespeare Method”

Authors of this article:

Haiyan Yu1 Author Orcid Image
Article Authors Cited by (1) Tweetations (2) Metrics

    Peer-Review Report


    This is a peer-review report submitted for the paper “Finding Potential Adverse Events in the Unstructured Text of Electronic Health Care Records: Development of the Shakespeare Method”


    General Comments

    This paper [1] investigated the new and increasing rates of adverse events (AEs) in unstructured text in electronic health records (EHRs). The topic is interesting. The authors used the Shakespeare method to identify attributed and unattributed potential AEs with EHRs. This method would be a useful supplement to AE reporting and surveillance. Although I believe that the topic of the study is very relevant, I have some concerns related to the theoretical background of the study. Specific major and minor comments are listed below.

    Specific Comments

    Major Comments
    1. What is the accuracy of the new method, the Shakespeare method, for identifying attributed and unattributed potential AEs? The previous study showed the process of this method in the literature [2]. This paper did not mention the accuracy of the new method.
    Minor Comments
    1. Too many keywords. I would suggest that the authors reduce some of the keywords.
    2. In the “Conclusions” subsection, I would suggest the paragraphs be reorganized to improve them.

    Conflicts of Interest

    None declared.

    1. Bright RA, Dowdy K, Rankin SK, Blok SV, Palmer LAM, Bright SJ. Finding Potential Adverse Events in the Unstructured Text of Electronic Health Care Records: Development of the Shakespeare Method. JMIRx Med 2021 Aug 11;2(3):e27017 [FREE Full text] [CrossRef]
    2. Bright RA, Rankin SK, Dowdy K, Blok SV, Bright SJ, Palmer LAM. Potential Blood Transfusion Adverse Events Can be Found in Unstructured Text in Electronic Health Records using the'Shakespeare Method. medRxiv Preprint published on January 6, 2021 [FREE Full text] [CrossRef]

    ‎
    AE: adverse event
    EHR: electronic health record

    Edited by E Meinert; This is a non–peer-reviewed article. submitted 24.06.21; accepted 24.06.21; published 11.08.21

    Copyright

    ©Haiyan Yu. Originally published in JMIRx Med (https://med.jmirx.org), 11.08.2021.

    This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIRx Med, is properly cited. The complete bibliographic information, a link to the original publication on https://med.jmirx.org/, as well as this copyright and license information must be included.