Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 32759
Visualizing Imaging Pathways after Anatomy-Specific Follow-Up Imaging Recommendations

Authors: Thusitha Mabotuwana, Christopher S. Hall

Abstract:

Radiologists routinely make follow-up imaging recommendations, usually based on established clinical practice guidelines, such as the Fleischner Society guidelines for managing lung nodules. In order to ensure optimal care, it is important to make guideline-compliant recommendations, and also for patients to follow-up on these imaging recommendations in a timely manner. However, determining such compliance rates after a specific finding has been observed usually requires many time-consuming manual steps. To address some of these limitations with current approaches, in this paper we discuss a methodology to automatically detect finding-specific follow-up recommendations from radiology reports and create a visualization for relevant subsequent exams showing the modality transitions. Nearly 5% of patients who had a lung related follow-up recommendation continued to have at least eight subsequent outpatient CT exams during a seven year period following the recommendation. Radiologist and section chiefs can use the proposed tool to better understand how a specific patient population is being managed, identify possible deviations from established guideline recommendations and have a patient-specific graphical representation of the imaging pathways for an abstract view of the overall treatment path thus far.

Keywords: Follow-up recommendations, care pathways, imaging pathway visualization, follow-up tracking.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.3607757

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 982

References:


[1] Harvey, H. B., et al., Correlation of the Strength of Recommendations for Additional Imaging to Adherence Rate and Diagnostic Yield. J Am Coll Radiol, 2015. 12(10): p. 1016-22.
[2] Fleischner Society – Society for Thoracic Imaging and Diagnosis. (cited 2017 Aug 10); Available from: https://fleischnersociety.org/.
[3] Eisenberg, R. L. and S. Fleischner, Ways to improve radiologists' adherence to Fleischner Society guidelines for management of pulmonary nodules. J Am Coll Radiol, 2013. 10(6): p. 439-41.
[4] Callen, J. L., et al., Failure to follow-up test results for ambulatory patients: a systematic review. J Gen Intern Med, 2012. 27(10): p. 1334-48.
[5] Dutta, S., et al., Automated detection using natural language processing of radiologists recommendations for additional imaging of incidental findings. Ann Emerg Med, 2013. 62(2): p. 162-9.
[6] Sloan, C. E., et al., Assessment of follow-up completeness and notification preferences for imaging findings of possible cancer: what happens after radiologists submit their reports? Acad Radiol, 2014. 21(12): p. 1579-86.
[7] Mabotuwana, T., et al. Extracting Follow-Up Recommendations and Associated Anatomy from Radiology Reports. in 16th World Congress on Medical and Health Informatics (MedInfo2017). Aug 2017. Hangzhou.
[8] Mabotuwana, T., et al., Determining Adherence to Follow-up Imaging Recommendations. J Am Coll Radiol, 2018. 15(3 Pt A): p. 422-428.
[9] Prinsen, P., et al., A Novel Approach for Improving the Recall of Concept Detection in Medical Documents Using Extended Ontologies, in Society for Imaging Informatics in Medicine Conference. 2017: Pittsburgh.
[10] Computing, N. C. f. B. NCBO Annotator. (cited 2017 Aug 11); Available from: https://bioportal.bioontology.org/annotator.
[11] Graphviz - Graph Visualization Software. (cited 2017 Aug 10); Available from: http://www.graphviz.org/.