Hua Xu, Jon Duke, George Hripcsak, Anupama Gururaj, Min Jiang, Alexandre Yahi, Noemie Elhadad, Olga Patterson, Scott DuVall, Lian Hu, Thomas Ginter

nlp_wg_meeting_03092016.pdf

1. Discussion of NLP_TERM_TABLE – Hua/Noemie
2. Share existing ontologies Regenstrief (Jon)
3. Share strategies for combining data from different searches – Jon
4. Improvements to search engine set up using MT samples – Min

1. Note-type mapping Presentation – Karthik
   1. INYP terminology services provides clinical document browser based on LOINC ontology for clinical notes. The paper describing the system is published and the pdf is attached. loinc_note_mapping_paper.pdf
   2. the system allows for comparison of configs across different sites.
   3. Vojtech also has looked into using LOINC ontology for note types. loinc_note_types_marshall_clinic.pdf
   4. With reference to standard note types, one of the suggestions was to use it in the database for the output of the NLP system.
   5. The note table in the OMOP CDM has a note type field with about 10 or so note types
   7. Next steps:
      1. Comparison of what aspects of LOINC is being used across different institutions.
      2. One of the deliverable is to build a system that can map the institutional note type to the LOINC note types.
      3. Update the note type field of the note table in OMOP CDM. Should a subset of LOINC document types be used for this purpose? this would depend on the real-world data from various institutions.
      4. Ontologies such as CP, ICD-9 etc. that include more clinical terminologies should also be explored.
2. existing ontologies from Vanderbilt - Hua - document-types.zip

1. Suggestion for OMOP model regarding NLP output - Hua/Noemie
2. 2016 OHDSI symposium - plan is to present the search engine, medical record viewer (a chart review tool) from Scott; any other suggestions?
3. Share strategies for combining data from different searches - Jon
4. Wrappers for cTAKES and Metamap - Min
5. Improvements to search engine set up using MT samples - Min
6. Textual Data Representation - Discussion
7. NLP system evaluation across different sites - Discussion