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Computer-based clinical coding activity analysis for neurosurgical terms

Authors :
Jong Hyuk Lee
Jung Hwan Lee
Wooseok Ryu
Byung Kwan Choi
In Ho Han
Chang Min Lee
Source :
Yeungnam University Journal of Medicine, Vol 36, Iss 3, Pp 225-230 (2019)
Publication Year :
2019
Publisher :
Yeungnam University College of Medicine, 2019.

Abstract

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.

Details

Language :
English, Korean
ISSN :
23840293
Volume :
36
Issue :
3
Database :
Directory of Open Access Journals
Journal :
Yeungnam University Journal of Medicine
Publication Type :
Academic Journal
Accession number :
edsdoj.7d17cf215e4b41018f649eca0e036628
Document Type :
article
Full Text :
https://doi.org/10.12701/yujm.2019.00220