Risperdal® CONSTA® Needle Detachment - Incidence Rates Before and After Kit Redesign: A Retrospective Study using Electronic Health Records and Natural Language Processing in the Department of Veterans Affairs

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Hauptverfasser: Wilcox, Marsha A., Coppola, Danielle, Bailey, Nicole, Wilson, Andrew, Kamauu, Aaron W. C., Alba, Patrick R., Patterson, Olga V., Viernes, Benjamin, Denhalter, Daniel W., Solomon, Ira D., DuVall, Scott L.
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creator Wilcox, Marsha A.
Coppola, Danielle
Bailey, Nicole
Wilson, Andrew
Kamauu, Aaron W. C.
Alba, Patrick R.
Patterson, Olga V.
Viernes, Benjamin
Denhalter, Daniel W.
Solomon, Ira D.
DuVall, Scott L.
description Full copyright for enhanced digital features is owned by the authors. Article full text The full text of this article can be found here. Provide enhanced digital features for this article If you are an author of this publication and would like to provide additional enhanced digital features for your article then please contact adisrapidplus@springer.com. The journal offers a range of additional features designed to increase visibility and readership. All features will be thoroughly peer reviewed to ensure the content is of the highest scientific standard and all features are marked as ‘peer reviewed’ to ensure readers are aware that the content has been reviewed to the same level as the articles they are being presented alongside. Moreover, all sponsorship and disclosure information is included to provide complete transparency and adherence to good publication practices. This ensures that however the content is reached the reader has a full understanding of its origin. No fees are charged for hosting additional open access content. Other enhanced features include, but are not limited to: • Slide decks • Videos and animations • Audio abstracts • Audio slides
doi_str_mv 10.6084/m9.figshare.7706636
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subjects FOS: Clinical medicine
Medicine
Neurology and Neuromuscular Diseases
title Risperdal® CONSTA® Needle Detachment - Incidence Rates Before and After Kit Redesign: A Retrospective Study using Electronic Health Records and Natural Language Processing in the Department of Veterans Affairs
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