An Evolving Ecosystem for Natural Language Processing in Department of Veterans Affairs.
In an ideal clinical Natural Language Processing (NLP) ecosystem, researchers and developers would be able to collaborate with others, undertake validation of NLP systems, components, and related resources, and disseminate them. We captured requirements and formative evaluation data from the Veteran...
| Publicado en: | Journal of Medical Systems Vol. 41; no. 2; pp. 1 - 10 |
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| Autores principales: | , , , , , , , , , , |
| Formato: | research tables/charts Journal Article |
| Publicado: |
Springer Nature
Feb2017
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=120895355&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 120895355 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 01485598 4N0 jtl: Journal of Medical Systems issn: 01485598 maglogo: N pubinfo: dt: Feb2017 vid: 41 iid: 2 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 120895355 120895355 120895355 10.1007/s10916-016-0681-4 120895355 ppf: 1 ppct: 9 formats: fmt: @attributes: type: P tig: atl: An Evolving Ecosystem for Natural Language Processing in Department of Veterans Affairs. aug: au: Garvin, Jennifer Kalsy, Megha Brandt, Cynthia Luther, Stephen Divita, Guy Coronado, Gregory Redd, Doug Christensen, Carrie Hill, Brent Kelly, Natalie Treitler, Qing affil: James A Haley Veterans Hospital , 13000 Bruce B. Downs Blvd Tampa USA sug: subj: United States Department of Veterans Affairs Natural Language Processing Systems Design Human Semi-Structured Interview Coding Convenience Sample kappa Statistic Funding Source ab: In an ideal clinical Natural Language Processing (NLP) ecosystem, researchers and developers would be able to collaborate with others, undertake validation of NLP systems, components, and related resources, and disseminate them. We captured requirements and formative evaluation data from the Veterans Affairs (VA) Clinical NLP Ecosystem stakeholders using semi-structured interviews and meeting discussions. We developed a coding rubric to code interviews. We assessed inter-coder reliability using percent agreement and the kappa statistic. We undertook 15 interviews and held two workshop discussions. The main areas of requirements related to; design and functionality, resources, and information. Stakeholders also confirmed the vision of the second generation of the Ecosystem and recommendations included; adding mechanisms to better understand terms, measuring collaboration to demonstrate value, and datasets/tools to navigate spelling errors with consumer language, among others. Stakeholders also recommended capability to: communicate with developers working on the next version of the VA electronic health record (VistA Evolution), provide a mechanism to automatically monitor download of tools and to automatically provide a summary of the downloads to Ecosystem contributors and funders. After three rounds of coding and discussion, we determined the percent agreement of two coders to be 97.2% and the kappa to be 0.7851. The vision of the VA Clinical NLP Ecosystem met stakeholder needs. Interviews and discussion provided key requirements that inform the design of the VA Clinical NLP Ecosystem. pubtype: Academic Journal doctype: research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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