Practical Considerations for Developing Clinical Natural Language Processing Systems for Population Health Management and Measurement
Experts have noted a concerning gap between clinical natural language processing (NLP) research and real-world applications, such as clinical decision support. To help address this gap, in this viewpoint, we enumerate a set of practical considerations for developing an NLP system to suppo...
Main Authors: | , , , , , |
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Format: | Article |
Language: | English |
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JMIR Publications
2023-01-01
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Series: | JMIR Medical Informatics |
Online Access: | https://medinform.jmir.org/2023/1/e37805 |
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author | Suzanne Tamang Marie Humbert-Droz Milena Gianfrancesco Zara Izadi Gabriela Schmajuk Jinoos Yazdany |
author_facet | Suzanne Tamang Marie Humbert-Droz Milena Gianfrancesco Zara Izadi Gabriela Schmajuk Jinoos Yazdany |
author_sort | Suzanne Tamang |
collection | DOAJ |
description |
Experts have noted a concerning gap between clinical natural language processing (NLP) research and real-world applications, such as clinical decision support. To help address this gap, in this viewpoint, we enumerate a set of practical considerations for developing an NLP system to support real-world clinical needs and improve health outcomes. They include determining (1) the readiness of the data and compute resources for NLP, (2) the organizational incentives to use and maintain the NLP systems, and (3) the feasibility of implementation and continued monitoring. These considerations are intended to benefit the design of future clinical NLP projects and can be applied across a variety of settings, including large health systems or smaller clinical practices that have adopted electronic medical records in the United States and globally. |
first_indexed | 2024-03-12T12:46:00Z |
format | Article |
id | doaj.art-fba66a4e25344d32b639e37d7cce0169 |
institution | Directory Open Access Journal |
issn | 2291-9694 |
language | English |
last_indexed | 2024-03-12T12:46:00Z |
publishDate | 2023-01-01 |
publisher | JMIR Publications |
record_format | Article |
series | JMIR Medical Informatics |
spelling | doaj.art-fba66a4e25344d32b639e37d7cce01692023-08-28T23:22:53ZengJMIR PublicationsJMIR Medical Informatics2291-96942023-01-0111e3780510.2196/37805Practical Considerations for Developing Clinical Natural Language Processing Systems for Population Health Management and MeasurementSuzanne Tamanghttps://orcid.org/0000-0003-2077-4620Marie Humbert-Drozhttps://orcid.org/0000-0001-6814-544XMilena Gianfrancescohttps://orcid.org/0000-0002-8351-4626Zara Izadihttps://orcid.org/0000-0002-1867-0905Gabriela Schmajukhttps://orcid.org/0000-0003-2687-5043Jinoos Yazdanyhttps://orcid.org/0000-0002-3508-4094 Experts have noted a concerning gap between clinical natural language processing (NLP) research and real-world applications, such as clinical decision support. To help address this gap, in this viewpoint, we enumerate a set of practical considerations for developing an NLP system to support real-world clinical needs and improve health outcomes. They include determining (1) the readiness of the data and compute resources for NLP, (2) the organizational incentives to use and maintain the NLP systems, and (3) the feasibility of implementation and continued monitoring. These considerations are intended to benefit the design of future clinical NLP projects and can be applied across a variety of settings, including large health systems or smaller clinical practices that have adopted electronic medical records in the United States and globally.https://medinform.jmir.org/2023/1/e37805 |
spellingShingle | Suzanne Tamang Marie Humbert-Droz Milena Gianfrancesco Zara Izadi Gabriela Schmajuk Jinoos Yazdany Practical Considerations for Developing Clinical Natural Language Processing Systems for Population Health Management and Measurement JMIR Medical Informatics |
title | Practical Considerations for Developing Clinical Natural Language Processing Systems for Population Health Management and Measurement |
title_full | Practical Considerations for Developing Clinical Natural Language Processing Systems for Population Health Management and Measurement |
title_fullStr | Practical Considerations for Developing Clinical Natural Language Processing Systems for Population Health Management and Measurement |
title_full_unstemmed | Practical Considerations for Developing Clinical Natural Language Processing Systems for Population Health Management and Measurement |
title_short | Practical Considerations for Developing Clinical Natural Language Processing Systems for Population Health Management and Measurement |
title_sort | practical considerations for developing clinical natural language processing systems for population health management and measurement |
url | https://medinform.jmir.org/2023/1/e37805 |
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