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 understand...

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Main Authors: Jong Hyuk Lee, Jung Hwan Lee, Wooseok Ryu, Byung Kwan Choi, In Ho Han, Chang Min Lee
Format: Article
Language:English
Published: Yeungnam University College of Medicine 2019-09-01
Series:Yeungnam University Journal of Medicine
Subjects:
Online Access:http://yujm.yu.ac.kr/upload/pdf/yujm-2019-00220.pdf
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spelling doaj-7d17cf215e4b41018f649eca0e0366282020-11-25T02:13:36ZengYeungnam University College of MedicineYeungnam University Journal of Medicine2384-02932019-09-0136322523010.12701/yujm.2019.002202436Computer-based clinical coding activity analysis for neurosurgical termsJong Hyuk Lee0Jung Hwan Lee1Wooseok Ryu2Byung Kwan Choi3In Ho Han4Chang Min Lee5 Convergence Medical Institute of Technology, Pusan National University Hospital, Busan, Korea Department of Neurosurgery, Pusan National University Hospital, Busan, Korea Department of Healthcare Information Management, Catholic University of Pusan, Busan, Korea Department of Neurosurgery, Pusan National University Hospital, Busan, Korea Department of Neurosurgery, Pusan National University Hospital, Busan, Korea Convergence Medical Institute of Technology, Pusan National University Hospital, Busan, KoreaBackground 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.http://yujm.yu.ac.kr/upload/pdf/yujm-2019-00220.pdfClinical codingMedical informaticsSystematized nomenclature of medicine
collection DOAJ
language English
format Article
sources DOAJ
author Jong Hyuk Lee
Jung Hwan Lee
Wooseok Ryu
Byung Kwan Choi
In Ho Han
Chang Min Lee
spellingShingle Jong Hyuk Lee
Jung Hwan Lee
Wooseok Ryu
Byung Kwan Choi
In Ho Han
Chang Min Lee
Computer-based clinical coding activity analysis for neurosurgical terms
Yeungnam University Journal of Medicine
Clinical coding
Medical informatics
Systematized nomenclature of medicine
author_facet Jong Hyuk Lee
Jung Hwan Lee
Wooseok Ryu
Byung Kwan Choi
In Ho Han
Chang Min Lee
author_sort Jong Hyuk Lee
title Computer-based clinical coding activity analysis for neurosurgical terms
title_short 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_sort computer-based clinical coding activity analysis for neurosurgical terms
publisher Yeungnam University College of Medicine
series Yeungnam University Journal of Medicine
issn 2384-0293
publishDate 2019-09-01
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.
topic Clinical coding
Medical informatics
Systematized nomenclature of medicine
url http://yujm.yu.ac.kr/upload/pdf/yujm-2019-00220.pdf
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AT inhohan computerbasedclinicalcodingactivityanalysisforneurosurgicalterms
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