Journal of Pathology Informatics Journal of Pathology Informatics
Contact us | Home | Login   |  Users Online: 400  Print this pageEmail this pageSmall font sizeDefault font sizeIncrease font size 


ORIGINAL ARTICLE
Year : 2019  |  Volume : 10  |  Issue : 1  |  Page : 20

Computational algorithms that effectively reduce report defects in surgical pathology


Dahl-Chase Pathology Associates, Bangor, Maine, USA

Correspondence Address:
Dr. Jay J Ye
417 State Street, Suite 540, Bangor, Maine 04401
USA
Login to access the Email id

Source of Support: None, Conflict of Interest: None


DOI: 10.4103/jpi.jpi_17_19

Rights and Permissions

Background: Pathology report defects refer to errors in the pathology reports, such as transcription/voice recognition errors and incorrect nondiagnostic information. Examples of the latter include incorrect gender, incorrect submitting physician, incorrect description of tissue blocks submitted, report formatting issues, and so on. Over the past 5 years, we have implemented computational algorithms to identify and correct these report defects. Materials and Methods: Report texts, tissue blocks submitted, and other relevant information are retrieved from the pathology information system database. Two complementary algorithms are used to identify the voice recognition errors by parsing the gross description texts to either (i) identify previously encountered error patterns or (ii) flag sentences containing previously-unused two-word sequences (bigrams). A third algorithm based on identifying conflicting information from two different sources is used to identify tissue block designation errors in the gross description; the information on actual block submission is compared with the block designation information parsed from the gross description text. Results: The computational algorithms identify voice recognition errors in approximately 8%–10% of the cases and block designation errors in approximately 0.5%–1% of all the cases. Conclusions: The algorithms described here have been effective in reducing pathology report defects. In addition to detecting voice recognition and block designation errors, these algorithms have also be used to detect other report defects, such as wrong gender, wrong provider, special stains or immunostains performed but not reported, and so on.


[FULL TEXT] [PDF]*
Print this article     Email this article
 Next article
 Previous article
 Table of Contents

 Similar in PUBMED
   Search Pubmed for
   Search in Google Scholar for
 Related articles
 Citation Manager
 Access Statistics
 Reader Comments
 Email Alert *
 Add to My List *
 * Requires registration (Free)
 

 Article Access Statistics
    Viewed436    
    Printed15    
    Emailed0    
    PDF Downloaded83    
    Comments [Add]    

Recommend this journal