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Health Information Management: Implications of Artificial Intelligence on Healthcare Data and Information Management
Objective: This paper explores the implications of artificial intelligence (AI) on the management of healthcare data and information and how AI technologies will affect the responsibilities and work of health information management (HIM) professionals. Methods: A literature review was conducted of b...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Georg Thieme Verlag KG
2019
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6697524/ https://www.ncbi.nlm.nih.gov/pubmed/31419816 http://dx.doi.org/10.1055/s-0039-1677913 |
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author | Stanfill, Mary H. Marc, David T. |
author_facet | Stanfill, Mary H. Marc, David T. |
author_sort | Stanfill, Mary H. |
collection | PubMed |
description | Objective: This paper explores the implications of artificial intelligence (AI) on the management of healthcare data and information and how AI technologies will affect the responsibilities and work of health information management (HIM) professionals. Methods: A literature review was conducted of both peer-reviewed literature and published opinions on current and future use of AI technology to collect, store, and use healthcare data. The authors also sought insights from key HIM leaders via semi-structured interviews conducted both on the phone and by email. Results: The following HIM practices are impacted by AI technologies: 1) Automated medical coding and capturing AI-based information; 2) Healthcare data management and data governance; 3) Fbtient privacy and confidentiality; and 4) HIM workforce training and education. Discussion: HIM professionals must focus on improving the quality of coded data that is being used to develop AI applications. HIM professional’s ability to identify data patterns will be an important skill as automation advances, though additional skills in data analysis tools and techniques are needed. In addition, HIM professionals should consider how current patient privacy practices apply to AI application, development, and use. Conclusions: AI technology will continue to evolve as will the role of HIM professionals who are in a unique position to take on emerging roles with their depth of knowledge on the sources and origins of healthcare data. The challenge for HIM professionals is to identify leading practices for the management of healthcare data and information in an AI-enabled world. |
format | Online Article Text |
id | pubmed-6697524 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Georg Thieme Verlag KG |
record_format | MEDLINE/PubMed |
spelling | pubmed-66975242019-08-19 Health Information Management: Implications of Artificial Intelligence on Healthcare Data and Information Management Stanfill, Mary H. Marc, David T. Yearb Med Inform Objective: This paper explores the implications of artificial intelligence (AI) on the management of healthcare data and information and how AI technologies will affect the responsibilities and work of health information management (HIM) professionals. Methods: A literature review was conducted of both peer-reviewed literature and published opinions on current and future use of AI technology to collect, store, and use healthcare data. The authors also sought insights from key HIM leaders via semi-structured interviews conducted both on the phone and by email. Results: The following HIM practices are impacted by AI technologies: 1) Automated medical coding and capturing AI-based information; 2) Healthcare data management and data governance; 3) Fbtient privacy and confidentiality; and 4) HIM workforce training and education. Discussion: HIM professionals must focus on improving the quality of coded data that is being used to develop AI applications. HIM professional’s ability to identify data patterns will be an important skill as automation advances, though additional skills in data analysis tools and techniques are needed. In addition, HIM professionals should consider how current patient privacy practices apply to AI application, development, and use. Conclusions: AI technology will continue to evolve as will the role of HIM professionals who are in a unique position to take on emerging roles with their depth of knowledge on the sources and origins of healthcare data. The challenge for HIM professionals is to identify leading practices for the management of healthcare data and information in an AI-enabled world. Georg Thieme Verlag KG 2019-08 2019-08-16 /pmc/articles/PMC6697524/ /pubmed/31419816 http://dx.doi.org/10.1055/s-0039-1677913 Text en https://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License, which permits unrestricted reproduction and distribution, for non-commercial purposes only; and use and reproduction, but not distribution, of adapted material for non-commercial purposes only, provided the original work is properly cited. |
spellingShingle | Stanfill, Mary H. Marc, David T. Health Information Management: Implications of Artificial Intelligence on Healthcare Data and Information Management |
title | Health Information Management: Implications of Artificial Intelligence on Healthcare Data and Information Management |
title_full | Health Information Management: Implications of Artificial Intelligence on Healthcare Data and Information Management |
title_fullStr | Health Information Management: Implications of Artificial Intelligence on Healthcare Data and Information Management |
title_full_unstemmed | Health Information Management: Implications of Artificial Intelligence on Healthcare Data and Information Management |
title_short | Health Information Management: Implications of Artificial Intelligence on Healthcare Data and Information Management |
title_sort | health information management: implications of artificial intelligence on healthcare data and information management |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6697524/ https://www.ncbi.nlm.nih.gov/pubmed/31419816 http://dx.doi.org/10.1055/s-0039-1677913 |
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