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Building a Shared, Scalable, and Sustainable Source for the Problem-Oriented Medical Record: Developmental Study
BACKGROUND: Since the creation of the problem-oriented medical record, the building of problem lists has been the focus of many studies. To date, this issue is not well resolved, and building an appropriate contextualized problem list is still a challenge. OBJECTIVE: This paper aims to present the p...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
JMIR Publications
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8552094/ https://www.ncbi.nlm.nih.gov/pubmed/34643542 http://dx.doi.org/10.2196/29174 |
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author | Gaudet-Blavignac, Christophe Rudaz, Andrea Lovis, Christian |
author_facet | Gaudet-Blavignac, Christophe Rudaz, Andrea Lovis, Christian |
author_sort | Gaudet-Blavignac, Christophe |
collection | PubMed |
description | BACKGROUND: Since the creation of the problem-oriented medical record, the building of problem lists has been the focus of many studies. To date, this issue is not well resolved, and building an appropriate contextualized problem list is still a challenge. OBJECTIVE: This paper aims to present the process of building a shared multipurpose common problem list at the Geneva University Hospitals. This list aims to bridge the gap between clinicians’ language expressed in free text and secondary uses requiring structured information. METHODS: We focused on the needs of clinicians by building a list of uniquely identified expressions to support their daily activities. In the second stage, these expressions were connected to additional information to build a complex graph of information. A list of 45,946 expressions manually extracted from clinical documents was manually curated and encoded in multiple semantic dimensions, such as International Classification of Diseases, 10th revision; International Classification of Primary Care 2nd edition; Systematized Nomenclature of Medicine Clinical Terms; or dimensions dictated by specific usages, such as identifying expressions specific to a domain, a gender, or an intervention. The list was progressively deployed for clinicians with an iterative process of quality control, maintenance, and improvements, including the addition of new expressions or dimensions for specific needs. The problem management of the electronic health record allowed the measurement and correction of encoding based on real-world use. RESULTS: The list was deployed in production in January 2017 and was regularly updated and deployed in new divisions of the hospital. Over 4 years, 684,102 problems were created using the list. The proportion of free-text entries decreased progressively from 37.47% (8321/22,206) in December 2017 to 18.38% (4547/24,738) in December 2020. In the last version of the list, over 14 dimensions were mapped to expressions, among which 5 were international classifications and 8 were other classifications for specific uses. The list became a central axis in the electronic health record, being used for many different purposes linked to care, such as surgical planning or emergency wards, or in research, for various predictions using machine learning techniques. CONCLUSIONS: This study breaks with common approaches primarily by focusing on real clinicians’ language when expressing patients’ problems and secondarily by mapping whatever is required, including controlled vocabularies to answer specific needs. This approach improves the quality of the expression of patients’ problems while allowing the building of as many structured dimensions as needed to convey semantics according to specific contexts. The method is shown to be scalable, sustainable, and efficient at hiding the complexity of semantics or the burden of constraint-structured problem list entry for clinicians. Ongoing work is analyzing the impact of this approach on how clinicians express patients’ problems. |
format | Online Article Text |
id | pubmed-8552094 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | JMIR Publications |
record_format | MEDLINE/PubMed |
spelling | pubmed-85520942021-11-10 Building a Shared, Scalable, and Sustainable Source for the Problem-Oriented Medical Record: Developmental Study Gaudet-Blavignac, Christophe Rudaz, Andrea Lovis, Christian JMIR Med Inform Original Paper BACKGROUND: Since the creation of the problem-oriented medical record, the building of problem lists has been the focus of many studies. To date, this issue is not well resolved, and building an appropriate contextualized problem list is still a challenge. OBJECTIVE: This paper aims to present the process of building a shared multipurpose common problem list at the Geneva University Hospitals. This list aims to bridge the gap between clinicians’ language expressed in free text and secondary uses requiring structured information. METHODS: We focused on the needs of clinicians by building a list of uniquely identified expressions to support their daily activities. In the second stage, these expressions were connected to additional information to build a complex graph of information. A list of 45,946 expressions manually extracted from clinical documents was manually curated and encoded in multiple semantic dimensions, such as International Classification of Diseases, 10th revision; International Classification of Primary Care 2nd edition; Systematized Nomenclature of Medicine Clinical Terms; or dimensions dictated by specific usages, such as identifying expressions specific to a domain, a gender, or an intervention. The list was progressively deployed for clinicians with an iterative process of quality control, maintenance, and improvements, including the addition of new expressions or dimensions for specific needs. The problem management of the electronic health record allowed the measurement and correction of encoding based on real-world use. RESULTS: The list was deployed in production in January 2017 and was regularly updated and deployed in new divisions of the hospital. Over 4 years, 684,102 problems were created using the list. The proportion of free-text entries decreased progressively from 37.47% (8321/22,206) in December 2017 to 18.38% (4547/24,738) in December 2020. In the last version of the list, over 14 dimensions were mapped to expressions, among which 5 were international classifications and 8 were other classifications for specific uses. The list became a central axis in the electronic health record, being used for many different purposes linked to care, such as surgical planning or emergency wards, or in research, for various predictions using machine learning techniques. CONCLUSIONS: This study breaks with common approaches primarily by focusing on real clinicians’ language when expressing patients’ problems and secondarily by mapping whatever is required, including controlled vocabularies to answer specific needs. This approach improves the quality of the expression of patients’ problems while allowing the building of as many structured dimensions as needed to convey semantics according to specific contexts. The method is shown to be scalable, sustainable, and efficient at hiding the complexity of semantics or the burden of constraint-structured problem list entry for clinicians. Ongoing work is analyzing the impact of this approach on how clinicians express patients’ problems. JMIR Publications 2021-10-13 /pmc/articles/PMC8552094/ /pubmed/34643542 http://dx.doi.org/10.2196/29174 Text en ©Christophe Gaudet-Blavignac, Andrea Rudaz, Christian Lovis. Originally published in JMIR Medical Informatics (https://medinform.jmir.org), 13.10.2021. 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 use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Medical Informatics, is properly cited. The complete bibliographic information, a link to the original publication on https://medinform.jmir.org/, as well as this copyright and license information must be included. |
spellingShingle | Original Paper Gaudet-Blavignac, Christophe Rudaz, Andrea Lovis, Christian Building a Shared, Scalable, and Sustainable Source for the Problem-Oriented Medical Record: Developmental Study |
title | Building a Shared, Scalable, and Sustainable Source for the Problem-Oriented Medical Record: Developmental Study |
title_full | Building a Shared, Scalable, and Sustainable Source for the Problem-Oriented Medical Record: Developmental Study |
title_fullStr | Building a Shared, Scalable, and Sustainable Source for the Problem-Oriented Medical Record: Developmental Study |
title_full_unstemmed | Building a Shared, Scalable, and Sustainable Source for the Problem-Oriented Medical Record: Developmental Study |
title_short | Building a Shared, Scalable, and Sustainable Source for the Problem-Oriented Medical Record: Developmental Study |
title_sort | building a shared, scalable, and sustainable source for the problem-oriented medical record: developmental study |
topic | Original Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8552094/ https://www.ncbi.nlm.nih.gov/pubmed/34643542 http://dx.doi.org/10.2196/29174 |
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