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A Synoptic Electronic Order Set for Placental Pathology: A Framework Extensible to Nonneoplastic Pathology.
Cimic, Adela; Mironova, Maria; Karakash, Scarlett; Sirintrapun, Sahussapont Joseph.
Afiliación
  • Cimic A; Department of Pathology and Cell Biology, Columbia University Medical Center, New York, NY, USA.
  • Mironova M; Department of Medicine, Capital Health System, Trenton, NJ, USA.
  • Karakash S; Department of Obstetrics and Gynecology, Stanford University Medical Center, Stanford, CA, USA.
  • Sirintrapun SJ; Department of Pathology, Memorial Sloan-Kettering Cancer Center, New York, NY, USA.
J Pathol Inform ; 11: 25, 2020.
Article en En | MEDLINE | ID: mdl-33042604
ABSTRACT
Accurate pathologic assessment in placental pathology is mostly dependent on a complete clinical history provided by a clinical team. However, often, the necessary clinical information is lacking, and electronic order sets (EOSs), if implemented correctly, create an opportunity for entering consistent and accurate clinical data. In this viewpoint piece, we describe a framework for synoptic EOS in placental pathology. We outline the necessary data and create optional clinical data that get entered as a dropdown menu of free text. While EOSs are the best way to approach and diagnose placenta and other nonneoplastic pathologic specimens, the barriers for implementation include paper requisitions and a cultural mindset resistance. The aspiration for our synoptic EOS is to become an effective tool for communication between proceduralists and pathologists for proper diagnosis of placental specimens. Through our EOS, the appropriate and complete clinical context is conveyed from the clinical teams to the pathologist. The pathologist can easily and rapidly extract the necessary information to render an accurate and precise diagnosis. The captured data likewise become a valuable research resource.
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Idioma: En Revista: J Pathol Inform Año: 2020 Tipo del documento: Article País de afiliación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Idioma: En Revista: J Pathol Inform Año: 2020 Tipo del documento: Article País de afiliación: Estados Unidos