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Computer-based clinical coding activity analysis for neurosurgical terms
BACKGROUND: It is not possible to measure how much activity is required to understand and code a medical data. We introduce an assessment method in clinical coding, and applied this method to neurosurgical terms. METHODS: Coding activity consists of two stages. At first, the coders need to understan...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Yeungnam University College of Medicine
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6784643/ https://www.ncbi.nlm.nih.gov/pubmed/31620637 http://dx.doi.org/10.12701/yujm.2019.00220 |
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author | Lee, Jong Hyuk Lee, Jung Hwan Ryu, Wooseok Choi, Byung Kwan Han, In Ho Lee, Chang Min |
author_facet | Lee, Jong Hyuk Lee, Jung Hwan Ryu, Wooseok Choi, Byung Kwan Han, In Ho Lee, Chang Min |
author_sort | Lee, Jong Hyuk |
collection | PubMed |
description | BACKGROUND: It is not possible to measure how much activity is required to understand and code a medical data. We introduce an assessment method in clinical coding, and applied this method to neurosurgical terms. METHODS: Coding activity consists of two stages. At first, the coders need to understand a presented medical term (informational activity). The second coding stage is about a navigating terminology browser to find a code that matches the concept (code-matching activity). Systematized Nomenclature of Medicine – Clinical Terms (SNOMED CT) was used for the coding system. A new computer application to record the trajectory of the computer mouse and record the usage time was programmed. Using this application, we measured the time that was spent. A senior neurosurgeon who has studied SNOMED CT has analyzed the accuracy of the input coding. This method was tested by five neurosurgical residents (NSRs) and five medical record administrators (MRAs), and 20 neurosurgical terms were used. RESULTS: The mean accuracy of the NSR group was 89.33%, and the mean accuracy of the MRA group was 80% (p=0.024). The mean duration for total coding of the NSR group was 158.47 seconds, and the mean duration for total coding of the MRA group was 271.75 seconds (p=0.003). CONCLUSION: We proposed a method to analyze the clinical coding process. Through this method, it was possible to accurately calculate the time required for the coding. In neurosurgical terms, NSRs had shorter time to complete the coding and higher accuracy than MRAs. |
format | Online Article Text |
id | pubmed-6784643 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Yeungnam University College of Medicine |
record_format | MEDLINE/PubMed |
spelling | pubmed-67846432019-10-16 Computer-based clinical coding activity analysis for neurosurgical terms Lee, Jong Hyuk Lee, Jung Hwan Ryu, Wooseok Choi, Byung Kwan Han, In Ho Lee, Chang Min Yeungnam Univ J Med Original Article BACKGROUND: It is not possible to measure how much activity is required to understand and code a medical data. We introduce an assessment method in clinical coding, and applied this method to neurosurgical terms. METHODS: Coding activity consists of two stages. At first, the coders need to understand a presented medical term (informational activity). The second coding stage is about a navigating terminology browser to find a code that matches the concept (code-matching activity). Systematized Nomenclature of Medicine – Clinical Terms (SNOMED CT) was used for the coding system. A new computer application to record the trajectory of the computer mouse and record the usage time was programmed. Using this application, we measured the time that was spent. A senior neurosurgeon who has studied SNOMED CT has analyzed the accuracy of the input coding. This method was tested by five neurosurgical residents (NSRs) and five medical record administrators (MRAs), and 20 neurosurgical terms were used. RESULTS: The mean accuracy of the NSR group was 89.33%, and the mean accuracy of the MRA group was 80% (p=0.024). The mean duration for total coding of the NSR group was 158.47 seconds, and the mean duration for total coding of the MRA group was 271.75 seconds (p=0.003). CONCLUSION: We proposed a method to analyze the clinical coding process. Through this method, it was possible to accurately calculate the time required for the coding. In neurosurgical terms, NSRs had shorter time to complete the coding and higher accuracy than MRAs. Yeungnam University College of Medicine 2019-06-04 /pmc/articles/PMC6784643/ /pubmed/31620637 http://dx.doi.org/10.12701/yujm.2019.00220 Text en Copyright © 2019 Yeungnam University College of Medicine This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Original Article Lee, Jong Hyuk Lee, Jung Hwan Ryu, Wooseok Choi, Byung Kwan Han, In Ho Lee, Chang Min Computer-based clinical coding activity analysis for neurosurgical terms |
title | Computer-based clinical coding activity analysis for neurosurgical terms |
title_full | Computer-based clinical coding activity analysis for neurosurgical terms |
title_fullStr | Computer-based clinical coding activity analysis for neurosurgical terms |
title_full_unstemmed | Computer-based clinical coding activity analysis for neurosurgical terms |
title_short | Computer-based clinical coding activity analysis for neurosurgical terms |
title_sort | computer-based clinical coding activity analysis for neurosurgical terms |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6784643/ https://www.ncbi.nlm.nih.gov/pubmed/31620637 http://dx.doi.org/10.12701/yujm.2019.00220 |
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