Positive Predictive Value of ICD-10-CM Codes for Myocarditis in Claims Data: A Multi-Institutional Study in Taiwan

Abstract

Purpose

The validity of the diagnosis codes to identify myocarditis cases in healthcare databases research remains unclear, and this study aimed to determine the coding accuracy of myocarditis in Taiwan.

Methods

We conducted a cross-sectional study based on Taiwan’s largest multi-institutional healthcare system to identify inpatients newly diagnosed with ICD-10-CM myocarditis codes at discharge between January 1st, 2017 and March 31st, 2022. We ascertained the myocarditis diagnosis by a gold standard biopsy or by review of electronic medical records, and the positive predictive values (PPV) with 95% confidence intervals (CI) of the ICD-10-CM codes for myocarditis were determined.

Results

We included a total of 498 inpatients (mean age: 33.8 years old; female: 38.8%) with new myocarditis diagnosis at discharge. Codes I409 (30.1%) and I514 (45.4%) constituted the majority of myocarditis diagnostic codes in any coding position, and the overall PPV of the myocarditis codes was 73.5% (95% CI: 69.6–77.4%). However, the highest PPV (96.6%) for myocarditis diagnosis was noted with code I409 as the primary diagnosis. We found 132 inpatients (26.5%) who were false-positive myocarditis cases, identified by the ICD-10-CM codes, and potential reasons for misclassification included other inflammation diseases (n=35, 26.5%), pre-existing heart failure (n= 25, 18.9%) and acute myocardial infarction (n=16, 12.1%).

Conclusion

The PPV of ICD-10-CM codes for myocarditis in Taiwan was acceptable, but some other inflammation diseases and pre-existing heart diseases may be falsely coded as myocarditis. Our results may serve future secondary database studies as a fundamental reference on the validity of myocarditis diagnosis codes.

Keywords:

• ICD-CM-10 codes
• positive predictive value
• myocarditis
• multi-institutional study
• Chang Gung Research Database

Data Sharing Statement

This study analyzed the electronic medical records data from the Chang Gung Memorial Hospitals (CGMF) in Taiwan. The access to the analyzed data needs the official approval from the CGMF. Also, all analyses should be conducted at the CGMF on site, and any individual-level data were not allowed to be taken out for data privacy and safety concerns. However, the analytical codes of SAS software in this study are available from corresponding author upon reasonable request.

Ethics Approval

This study has been approved by the Institutional Review Board of CGMF (IRB No: 202200229B0) and was conducted in accordance with the principles laid down in the Declaration of Helsinki. The requirement for informed consent was waived due to the retrospective design. All accessed data complied with relevant data protection and privacy regulations from CGMF.

Author Contributions

All authors made a significant contribution to the work reported, whether that is in the conception, study design, execution, acquisition of data, analysis and interpretation, or in all these areas; took part in drafting, revising or critically reviewing the article; gave final approval of the version to be published; have agreed on the journal to which the article has been submitted; and agree to be accountable for all aspects of the work.

Disclosure

The authors report no conflicts of interest in this work.

Additional information

Funding

This study was supported by grants from Keelung Chang Gung Memorial Hospital, Taiwan (CGRPG2M0011). The funder had no part in this study, including study design and conduct, data collection, management, analysis and interpretation, manuscript preparation, review and approval, and decision to publish.