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Computational phenotyping with the All of Us Research Program: identifying underrepresented people with HIV or at risk of HIV
OBJECTIVE: This study aims to identify the people living with HIV (PWH) and pre-exposure prophylaxis (PrEP) users in the All of Us (AoU) database by integrating information from both electronic health record (EHR)- and self-reported survey data. METHODS: We identified PWH and PrEP users if they met...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10444028/ https://www.ncbi.nlm.nih.gov/pubmed/37614566 http://dx.doi.org/10.1093/jamiaopen/ooad071 |
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author | Yang, Xueying Zhang, Jiajia Cai, Ruilie Liang, Chen Olatosi, Bankole Weissman, Sharon Li, Xiaoming |
author_facet | Yang, Xueying Zhang, Jiajia Cai, Ruilie Liang, Chen Olatosi, Bankole Weissman, Sharon Li, Xiaoming |
author_sort | Yang, Xueying |
collection | PubMed |
description | OBJECTIVE: This study aims to identify the people living with HIV (PWH) and pre-exposure prophylaxis (PrEP) users in the All of Us (AoU) database by integrating information from both electronic health record (EHR)- and self-reported survey data. METHODS: We identified PWH and PrEP users if they met the inclusion criterion by conditions, lab measurements, or medications related to HIV in EHR data or confirmed questions in the Survey data. RESULTS: We evaluated the latest data release through July 1, 2022 in AoU. Through computational phenotyping, we identified 4575 confirmed and 3092 probable adult PWH and 564 PrEP users. PWH was most identified by a combination of medications and conditions (3324, 43.4%) and drug exposure alone (2191, 28.6%), then less commonly by survey data alone (608, 7.9%) and lab alone (81, 1.1%). DISCUSSION AND CONCLUSION: Our methods serve as an overall framework for other researchers using AoU data for conducting HIV-related research. |
format | Online Article Text |
id | pubmed-10444028 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-104440282023-08-23 Computational phenotyping with the All of Us Research Program: identifying underrepresented people with HIV or at risk of HIV Yang, Xueying Zhang, Jiajia Cai, Ruilie Liang, Chen Olatosi, Bankole Weissman, Sharon Li, Xiaoming JAMIA Open Brief Communications OBJECTIVE: This study aims to identify the people living with HIV (PWH) and pre-exposure prophylaxis (PrEP) users in the All of Us (AoU) database by integrating information from both electronic health record (EHR)- and self-reported survey data. METHODS: We identified PWH and PrEP users if they met the inclusion criterion by conditions, lab measurements, or medications related to HIV in EHR data or confirmed questions in the Survey data. RESULTS: We evaluated the latest data release through July 1, 2022 in AoU. Through computational phenotyping, we identified 4575 confirmed and 3092 probable adult PWH and 564 PrEP users. PWH was most identified by a combination of medications and conditions (3324, 43.4%) and drug exposure alone (2191, 28.6%), then less commonly by survey data alone (608, 7.9%) and lab alone (81, 1.1%). DISCUSSION AND CONCLUSION: Our methods serve as an overall framework for other researchers using AoU data for conducting HIV-related research. Oxford University Press 2023-08-22 /pmc/articles/PMC10444028/ /pubmed/37614566 http://dx.doi.org/10.1093/jamiaopen/ooad071 Text en © The Author(s) 2023. Published by Oxford University Press on behalf of the American Medical Informatics Association. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Brief Communications Yang, Xueying Zhang, Jiajia Cai, Ruilie Liang, Chen Olatosi, Bankole Weissman, Sharon Li, Xiaoming Computational phenotyping with the All of Us Research Program: identifying underrepresented people with HIV or at risk of HIV |
title | Computational phenotyping with the All of Us Research Program: identifying underrepresented people with HIV or at risk of HIV |
title_full | Computational phenotyping with the All of Us Research Program: identifying underrepresented people with HIV or at risk of HIV |
title_fullStr | Computational phenotyping with the All of Us Research Program: identifying underrepresented people with HIV or at risk of HIV |
title_full_unstemmed | Computational phenotyping with the All of Us Research Program: identifying underrepresented people with HIV or at risk of HIV |
title_short | Computational phenotyping with the All of Us Research Program: identifying underrepresented people with HIV or at risk of HIV |
title_sort | computational phenotyping with the all of us research program: identifying underrepresented people with hiv or at risk of hiv |
topic | Brief Communications |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10444028/ https://www.ncbi.nlm.nih.gov/pubmed/37614566 http://dx.doi.org/10.1093/jamiaopen/ooad071 |
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