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Follow-up Recommendation Detection on Radiology Reports with Incidental Pulmonary Nodules.
Oliveira, Lucas; Tellis, Ranjith; Qian, Yuechen; Trovato, Karen; Mankovich, Gabe.
Affiliation
  • Oliveira L; Clinical Informatics Solutions and Service, Philips Research North America, NY, USA.
  • Tellis R; Clinical Informatics Solutions and Service, Philips Research North America, NY, USA.
  • Qian Y; Clinical Informatics Solutions and Service, Philips Research North America, NY, USA.
  • Trovato K; Clinical Informatics Solutions and Service, Philips Research North America, NY, USA.
  • Mankovich G; Clinical Informatics Solutions and Service, Philips Research North America, NY, USA.
Stud Health Technol Inform ; 216: 1028, 2015.
Article in En | MEDLINE | ID: mdl-26262328
ABSTRACT
The management of follow-up recommendations is fundamental for the appropriate care of patients with incidental pulmonary findings. The lack of communication of these important findings can result in important actionable information being lost in healthcare provider electronic documents. This study aims to analyze follow-up recommendations in radiology reports containing pulmonary incidental findings by using Natural Language Processing and Regular Expressions. Our evaluation highlights the different follow-up recommendation rates for oncology and non-oncology patient cohorts. The results reveal the need for a context-sensitive approach to tracking different patient cohorts in an enterprise-wide assessment.
Subject(s)
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Collection: 01-internacional Database: MEDLINE Main subject: Referral and Consultation / Natural Language Processing / Radiography, Abdominal / Diagnosis, Computer-Assisted / Radiology Information Systems / Decision Support Systems, Clinical Type of study: Diagnostic_studies / Prognostic_studies Limits: Humans Country/Region as subject: America do norte Language: En Journal: Stud Health Technol Inform Journal subject: INFORMATICA MEDICA / PESQUISA EM SERVICOS DE SAUDE Year: 2015 Document type: Article Affiliation country: United States
Search on Google
Collection: 01-internacional Database: MEDLINE Main subject: Referral and Consultation / Natural Language Processing / Radiography, Abdominal / Diagnosis, Computer-Assisted / Radiology Information Systems / Decision Support Systems, Clinical Type of study: Diagnostic_studies / Prognostic_studies Limits: Humans Country/Region as subject: America do norte Language: En Journal: Stud Health Technol Inform Journal subject: INFORMATICA MEDICA / PESQUISA EM SERVICOS DE SAUDE Year: 2015 Document type: Article Affiliation country: United States