Can Automated Retrieval of Data from Emergency Department Physician Notes Enhance the Imaging Order Entry Process?

Justin F. Rousseau, Ivan K. Ip, Ali S. Raja, Vladimir I. Valtchinov, Laila Cochon, Jeremiah D. Schuur, Ramin Khorasani

Research output: Contribution to journalArticle

Abstract

Background When a paucity of clinical information is communicated from ordering physicians to radiologists at the time of radiology order entry, suboptimal imaging interpretations and patient care may result. Objectives Compare documentation of relevant clinical information in electronic health record (EHR) provider note to computed tomography (CT) order requisition, prior to ordering of head CT for emergency department (ED) patients presenting with headache. Methods In this institutional review board-approved retrospective observational study performed between April 1, 2013 and September 30, 2014 at an adult quaternary academic hospital, we reviewed data from 666 consecutive ED encounters for patients with headaches who received head CT. The primary outcome was the number of concept unique identifiers (CUIs) relating to headache extracted via ontology-based natural language processing from the history of present illness (HPI) section in ED notes compared with the number of concepts obtained from the imaging order requisition. Results Our analysis was conducted on cases where the HPI note section was completed prior to image order entry, which occurred in 23.1% (154/666) of encounters. For these 154 encounters, the number of CUIs specific to headache per note extracted from the HPI (median = 3, interquartile range [IQR]: 2-4) was significantly greater than the number of CUIs per encounter obtained from the imaging order requisition (median = 1, IQR: 1-2; Wilcoxon signed rank p < 0.0001). Extracted concepts from notes were distinct from order requisition indications in 92.9% (143/154) of cases. Conclusion EHR provider notes are a valuable source of relevant clinical information at the time of imaging test ordering. Automated extraction of clinical information from notes to prepopulate imaging order requisitions may improve communication between ordering physicians and radiologists, enhance efficiency of ordering process by reducing redundant data entry, and may help improve clinical relevance of clinical decision support at the time of order entry, potentially reducing provider burnout from extraneous alerts.

Original languageEnglish (US)
Pages (from-to)189-198
Number of pages10
JournalApplied Clinical Informatics
Volume10
Issue number2
DOIs
StatePublished - Jan 1 2019

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Information Storage and Retrieval
Headache
Hospital Emergency Service
Physicians
Imaging techniques
Electronic Health Records
History
Tomography
Head
Clinical Decision Support Systems
Natural Language Processing
Health
Research Ethics Committees
Radiology
Documentation
Observational Studies
Patient Care
Retrospective Studies
Communication
Ontology

Keywords

  • computerized physician order entry
  • electronic health records
  • emergency medicine
  • natural language processing
  • radiology

ASJC Scopus subject areas

  • Health Informatics
  • Computer Science Applications
  • Health Information Management

Cite this

Can Automated Retrieval of Data from Emergency Department Physician Notes Enhance the Imaging Order Entry Process? / Rousseau, Justin F.; Ip, Ivan K.; Raja, Ali S.; Valtchinov, Vladimir I.; Cochon, Laila; Schuur, Jeremiah D.; Khorasani, Ramin.

In: Applied Clinical Informatics, Vol. 10, No. 2, 01.01.2019, p. 189-198.

Research output: Contribution to journalArticle

Rousseau, Justin F. ; Ip, Ivan K. ; Raja, Ali S. ; Valtchinov, Vladimir I. ; Cochon, Laila ; Schuur, Jeremiah D. ; Khorasani, Ramin. / Can Automated Retrieval of Data from Emergency Department Physician Notes Enhance the Imaging Order Entry Process?. In: Applied Clinical Informatics. 2019 ; Vol. 10, No. 2. pp. 189-198.
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abstract = "Background When a paucity of clinical information is communicated from ordering physicians to radiologists at the time of radiology order entry, suboptimal imaging interpretations and patient care may result. Objectives Compare documentation of relevant clinical information in electronic health record (EHR) provider note to computed tomography (CT) order requisition, prior to ordering of head CT for emergency department (ED) patients presenting with headache. Methods In this institutional review board-approved retrospective observational study performed between April 1, 2013 and September 30, 2014 at an adult quaternary academic hospital, we reviewed data from 666 consecutive ED encounters for patients with headaches who received head CT. The primary outcome was the number of concept unique identifiers (CUIs) relating to headache extracted via ontology-based natural language processing from the history of present illness (HPI) section in ED notes compared with the number of concepts obtained from the imaging order requisition. Results Our analysis was conducted on cases where the HPI note section was completed prior to image order entry, which occurred in 23.1{\%} (154/666) of encounters. For these 154 encounters, the number of CUIs specific to headache per note extracted from the HPI (median = 3, interquartile range [IQR]: 2-4) was significantly greater than the number of CUIs per encounter obtained from the imaging order requisition (median = 1, IQR: 1-2; Wilcoxon signed rank p < 0.0001). Extracted concepts from notes were distinct from order requisition indications in 92.9{\%} (143/154) of cases. Conclusion EHR provider notes are a valuable source of relevant clinical information at the time of imaging test ordering. Automated extraction of clinical information from notes to prepopulate imaging order requisitions may improve communication between ordering physicians and radiologists, enhance efficiency of ordering process by reducing redundant data entry, and may help improve clinical relevance of clinical decision support at the time of order entry, potentially reducing provider burnout from extraneous alerts.",
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AU - Schuur, Jeremiah D.

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N2 - Background When a paucity of clinical information is communicated from ordering physicians to radiologists at the time of radiology order entry, suboptimal imaging interpretations and patient care may result. Objectives Compare documentation of relevant clinical information in electronic health record (EHR) provider note to computed tomography (CT) order requisition, prior to ordering of head CT for emergency department (ED) patients presenting with headache. Methods In this institutional review board-approved retrospective observational study performed between April 1, 2013 and September 30, 2014 at an adult quaternary academic hospital, we reviewed data from 666 consecutive ED encounters for patients with headaches who received head CT. The primary outcome was the number of concept unique identifiers (CUIs) relating to headache extracted via ontology-based natural language processing from the history of present illness (HPI) section in ED notes compared with the number of concepts obtained from the imaging order requisition. Results Our analysis was conducted on cases where the HPI note section was completed prior to image order entry, which occurred in 23.1% (154/666) of encounters. For these 154 encounters, the number of CUIs specific to headache per note extracted from the HPI (median = 3, interquartile range [IQR]: 2-4) was significantly greater than the number of CUIs per encounter obtained from the imaging order requisition (median = 1, IQR: 1-2; Wilcoxon signed rank p < 0.0001). Extracted concepts from notes were distinct from order requisition indications in 92.9% (143/154) of cases. Conclusion EHR provider notes are a valuable source of relevant clinical information at the time of imaging test ordering. Automated extraction of clinical information from notes to prepopulate imaging order requisitions may improve communication between ordering physicians and radiologists, enhance efficiency of ordering process by reducing redundant data entry, and may help improve clinical relevance of clinical decision support at the time of order entry, potentially reducing provider burnout from extraneous alerts.

AB - Background When a paucity of clinical information is communicated from ordering physicians to radiologists at the time of radiology order entry, suboptimal imaging interpretations and patient care may result. Objectives Compare documentation of relevant clinical information in electronic health record (EHR) provider note to computed tomography (CT) order requisition, prior to ordering of head CT for emergency department (ED) patients presenting with headache. Methods In this institutional review board-approved retrospective observational study performed between April 1, 2013 and September 30, 2014 at an adult quaternary academic hospital, we reviewed data from 666 consecutive ED encounters for patients with headaches who received head CT. The primary outcome was the number of concept unique identifiers (CUIs) relating to headache extracted via ontology-based natural language processing from the history of present illness (HPI) section in ED notes compared with the number of concepts obtained from the imaging order requisition. Results Our analysis was conducted on cases where the HPI note section was completed prior to image order entry, which occurred in 23.1% (154/666) of encounters. For these 154 encounters, the number of CUIs specific to headache per note extracted from the HPI (median = 3, interquartile range [IQR]: 2-4) was significantly greater than the number of CUIs per encounter obtained from the imaging order requisition (median = 1, IQR: 1-2; Wilcoxon signed rank p < 0.0001). Extracted concepts from notes were distinct from order requisition indications in 92.9% (143/154) of cases. Conclusion EHR provider notes are a valuable source of relevant clinical information at the time of imaging test ordering. Automated extraction of clinical information from notes to prepopulate imaging order requisitions may improve communication between ordering physicians and radiologists, enhance efficiency of ordering process by reducing redundant data entry, and may help improve clinical relevance of clinical decision support at the time of order entry, potentially reducing provider burnout from extraneous alerts.

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