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A Korean field trial of ICD-11 classification under practical clinical coding rules to clarify the reasons for
1Department of Health and Medical Administration, Jaeneung University, Incheon, Korea.
Insights
Improving International Classification of Diseases (ICD)-11 clinical coding accuracy requires clear rules. Variance in coding methods, especially post-coordination, impacts case scenario consistency.
Area of Science:
- Health Informatics
- Medical Coding Standards
Background:
- The World Health Organization released the International Classification of Diseases (ICD)-11 in 2019.
- Previous studies on ICD-11 clinical coding by Statistics Korea showed high variance and lack of agreement on gold standards for case scenarios.
Purpose of the Study:
- To enhance clinical coding accuracy and consistency for ICD-11.
- To identify and clarify reasons for inconsistencies in clinical coding through the development of clear coding rules.
Main Methods:
- A pre-experimental design was employed, involving two clinical coding field trials (FTs) using ICD-11 for Mortality and Morbidity Statistics.
- The first FT focused on deriving clinical coding rules from analyzed results, while the second FT applied these established rules.
Main Results:
- Accuracy rates for diagnostic terms were higher (75.8%, 71.8%) than for case scenarios (62.5%, 71.9%) across the two field trials.
- Post-coordination was identified as the primary reason for lower accuracy levels in case scenario coding.
Conclusions:
- Low accuracy in ICD-11 case scenario coding is attributed to variance in participants' clustering methods.
- Implementing a clear coding guide to reduce clustering method variance can improve ICD-11 coding accuracy.
- Developing institutional guides for ambiguous cases and providing a post-coordination list in stem codes may further enhance accuracy.
Abstract:
Background: The World Health Organization (WHO) announced the release of the 11th edition of the International Classification of Diseases (ICD) in May 2019. Although Statistics Korea has been involved in the ongoing research on ICD-11 since 2017, we have been unable to achieve agreement on the gold standards for case scenario clinical coding in previous studies due to high levels of variance in the coding results of participants. Objective: The purpose of this study was to enhance clinical coding accuracy and consistency in ICD-11 by identifying and clarifying the reasons for these inconsistencies through the use of clear clinical coding rules. Method: A pre-experimental design was applied. Two clinical coding field trials (FTs) were conducted in 'ICD-11 for Mortality and Morbidity Statistics (2022 Mar)' targeting diagnostic terms and case scenarios. In the first FT, clinical coding rules were derived by analysing the results, while the second FT was performed under the clinical coding rules set by the first FT. Results: Across the two FTs, accuracy rates for diagnostic terms (75.8% and 71.8%, respectively) were higher than for case scenarios (62.5% and 71.9%). The main reason for the low accuracy levels was post-coordination. Conclusion: For case scenario clinical coding, low accuracy could be explained by variance in clustering methods between participants. This suggests that the accuracy of ICD-11 clinical coding could be increased if the variance between clustering methods can be reduced through the use of a clear coding guide. A guide for various ambiguous cases in each institution and the provision of a proper post-coordination list in the stem code could also be effective.
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