ACORN SDOH survey: Terminological representation for use with NLP and CDS
Abstract Objective: Social Determinants of Health (SDOH) greatly influence health outcomes. SDOH surveys, such as the Assessing Circumstances & Offering Resources for Needs (ACORN) survey, have been developed to screen for SDOH in Veterans. The purpose of this study is to determine the termino...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Cambridge University Press
2024-01-01
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| Series: | Journal of Clinical and Translational Science |
| Subjects: | |
| Online Access: | https://www.cambridge.org/core/product/identifier/S2059866124000244/type/journal_article |
| _version_ | 1797277176830099456 |
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| author | Melissa P. Resnick Diane Montella Steven H. Brown Peter Elkin |
| author_facet | Melissa P. Resnick Diane Montella Steven H. Brown Peter Elkin |
| author_sort | Melissa P. Resnick |
| collection | DOAJ |
| description |
Abstract
Objective:
Social Determinants of Health (SDOH) greatly influence health outcomes. SDOH surveys, such as the Assessing Circumstances & Offering Resources for Needs (ACORN) survey, have been developed to screen for SDOH in Veterans. The purpose of this study is to determine the terminological representation of the ACORN survey, to aid in natural language processing (NLP).
Methods:
Each ACORN survey question was read to determine its concepts. Next, Solor was searched for each of the concepts and for the appropriate attributes. If no attributes or concepts existed, they were proposed. Then, each question’s concepts and attributes were arranged into subject-relation-object triples.
Results:
Eleven unique attributes and 18 unique concepts were proposed. These results demonstrate a gap in representing SDOH with terminologies. We believe that using these new concepts and relations will improve NLP, and thus, the care provided to Veterans.
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| first_indexed | 2024-03-07T15:43:53Z |
| format | Article |
| id | doaj.art-b4ba7bb157f049558fe0a1e0ad5b9c2c |
| institution | Directory Open Access Journal |
| issn | 2059-8661 |
| language | English |
| last_indexed | 2024-03-07T15:43:53Z |
| publishDate | 2024-01-01 |
| publisher | Cambridge University Press |
| record_format | Article |
| series | Journal of Clinical and Translational Science |
| spelling | doaj.art-b4ba7bb157f049558fe0a1e0ad5b9c2c2024-03-05T05:18:55ZengCambridge University PressJournal of Clinical and Translational Science2059-86612024-01-01810.1017/cts.2024.24ACORN SDOH survey: Terminological representation for use with NLP and CDSMelissa P. Resnick0https://orcid.org/0000-0001-9699-852XDiane Montella1Steven H. Brown2Peter Elkin3https://orcid.org/0000-0001-9616-6811Department of Biomedical Informatics, University at Buffalo, Buffalo, NY, USA U.S. Department of Veteran Affairs, WNY VA, Buffalo, NY, USAU.S. Department of Veteran Affairs, Office of Health Informatics, Washington, DC, USAU.S. Department of Veteran Affairs, Office of Health Informatics, Washington, DC, USADepartment of Biomedical Informatics, University at Buffalo, Buffalo, NY, USA U.S. Department of Veteran Affairs, WNY VA, Buffalo, NY, USA U.S. Department of Veteran Affairs, Office of Health Informatics, Washington, DC, USA Faculty of Engineering, University of Southern Denmark, Odense, Denmark Abstract Objective: Social Determinants of Health (SDOH) greatly influence health outcomes. SDOH surveys, such as the Assessing Circumstances & Offering Resources for Needs (ACORN) survey, have been developed to screen for SDOH in Veterans. The purpose of this study is to determine the terminological representation of the ACORN survey, to aid in natural language processing (NLP). Methods: Each ACORN survey question was read to determine its concepts. Next, Solor was searched for each of the concepts and for the appropriate attributes. If no attributes or concepts existed, they were proposed. Then, each question’s concepts and attributes were arranged into subject-relation-object triples. Results: Eleven unique attributes and 18 unique concepts were proposed. These results demonstrate a gap in representing SDOH with terminologies. We believe that using these new concepts and relations will improve NLP, and thus, the care provided to Veterans. https://www.cambridge.org/core/product/identifier/S2059866124000244/type/journal_articleBiomedical informaticsclinical caresocial determinants of healthACORN survey |
| spellingShingle | Melissa P. Resnick Diane Montella Steven H. Brown Peter Elkin ACORN SDOH survey: Terminological representation for use with NLP and CDS Journal of Clinical and Translational Science Biomedical informatics clinical care social determinants of health ACORN survey |
| title | ACORN SDOH survey: Terminological representation for use with NLP and CDS |
| title_full | ACORN SDOH survey: Terminological representation for use with NLP and CDS |
| title_fullStr | ACORN SDOH survey: Terminological representation for use with NLP and CDS |
| title_full_unstemmed | ACORN SDOH survey: Terminological representation for use with NLP and CDS |
| title_short | ACORN SDOH survey: Terminological representation for use with NLP and CDS |
| title_sort | acorn sdoh survey terminological representation for use with nlp and cds |
| topic | Biomedical informatics clinical care social determinants of health ACORN survey |
| url | https://www.cambridge.org/core/product/identifier/S2059866124000244/type/journal_article |
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