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Dialogue Analysis for Clinical Data Query Mediation

Efficient access to clinical data by investigators is critical for data-driven biomedical research. Mediated query is commonly adopted to facilitate data access for investigators. However, the query mediation process remains a black-box. This study analyzed the email-based dialogues between investig...

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Detalles Bibliográficos
Autores principales: Weng, Chunhua, Mir, Amy K., Hanauer, David, Cimino, James
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6874882/
https://www.ncbi.nlm.nih.gov/pubmed/31438156
http://dx.doi.org/10.3233/SHTI190457
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author Weng, Chunhua
Mir, Amy K.
Hanauer, David
Cimino, James
author_facet Weng, Chunhua
Mir, Amy K.
Hanauer, David
Cimino, James
author_sort Weng, Chunhua
collection PubMed
description Efficient access to clinical data by investigators is critical for data-driven biomedical research. Mediated query is commonly adopted to facilitate data access for investigators. However, the query mediation process remains a black-box. This study analyzed the email-based dialogues between investigators and clinical data query mediators from three institutions. We identify discussion topics and their frequencies, model task flows, and analyze user needs for query mediation support revealed from the dialogues. While the datasets between different institutions are distinct in some notable respects, we find that together they provide common insights for streamlining data access. From our findings, we conclude an intelligent dialogue-based query support model is feasible to automate human-mediated clinical data access for investigators and stakeholders.
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spelling pubmed-68748822019-11-24 Dialogue Analysis for Clinical Data Query Mediation Weng, Chunhua Mir, Amy K. Hanauer, David Cimino, James Stud Health Technol Inform Article Efficient access to clinical data by investigators is critical for data-driven biomedical research. Mediated query is commonly adopted to facilitate data access for investigators. However, the query mediation process remains a black-box. This study analyzed the email-based dialogues between investigators and clinical data query mediators from three institutions. We identify discussion topics and their frequencies, model task flows, and analyze user needs for query mediation support revealed from the dialogues. While the datasets between different institutions are distinct in some notable respects, we find that together they provide common insights for streamlining data access. From our findings, we conclude an intelligent dialogue-based query support model is feasible to automate human-mediated clinical data access for investigators and stakeholders. 2019-08-21 /pmc/articles/PMC6874882/ /pubmed/31438156 http://dx.doi.org/10.3233/SHTI190457 Text en http://creativecommons.org/licenses/by-nc/4.0/ This article is published online with Open Access by IOS Press and distributed under the terms of the Creative Commons Attribution Non-Commercial License 4.0 (CC BY-NC 4.0).
spellingShingle Article
Weng, Chunhua
Mir, Amy K.
Hanauer, David
Cimino, James
Dialogue Analysis for Clinical Data Query Mediation
title Dialogue Analysis for Clinical Data Query Mediation
title_full Dialogue Analysis for Clinical Data Query Mediation
title_fullStr Dialogue Analysis for Clinical Data Query Mediation
title_full_unstemmed Dialogue Analysis for Clinical Data Query Mediation
title_short Dialogue Analysis for Clinical Data Query Mediation
title_sort dialogue analysis for clinical data query mediation
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6874882/
https://www.ncbi.nlm.nih.gov/pubmed/31438156
http://dx.doi.org/10.3233/SHTI190457
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