Validation of insurance claims data on aetiology, surgical type and prosthesis for isolated valve surgery: A retrospective observational surgery

OBJECTIVES: Administrative database research is pivotal for developing guidelines in cardiovascular surgery and valvular heart disease. However, validation studies specific to Asia are lacking. This study validated the coding of valvular heart repair and replacement surgeries in Taiwan's National Health Insurance (NHI) Research Database using International Classification of Diseases, Clinical Modification (ICD-CM) codes.

METHODS: This retrospective observational study used data from the Chang Gung Research Database between 2015 and 2018, identifying 1171 patients using Taiwanese NHI reimbursement codes. The gold standard was defined as a blinded retrospective review of operation notes. Claims data, including ICD diagnostic codes, ICD procedural codes and NHI supply codes for surgical materials, were validated. Positive predictive values (PPVs) were calculated as the number of true positives divided by the total claims data.

RESULTS: The PPVs (95% CI) for aortic valve (AV) surgery aetiologies were as follows: infectious endocarditis (IE), 94.1% (87.6%-97.7%); rheumatic heart disease (RHD), 88.2% (67.3%-97.5%); bicuspid AV, 93.3% (83.3%-98.1%); and degeneration, 91.7% (85.3%-95.8%). For mitral valve surgery, the surgery aetiologies and PPVs were IE, 93.2% (87.9%-96.6%); RHD, 94.9% (88.3%-98.2%); ischaemic mitral regurgitation, 87.5% (73.0%-95.6%); and degeneration, 88.4% (83.9%-92.0%). Surgical types generally exhibited higher PPVs, except for mechanical prostheses (<90%). The accuracy of mechanical prosthesis identification improved with the inclusion of supply codes along with ICD procedural codes.

CONCLUSIONS: The PPVs for both aetiologies and surgical types of valvular heart disease were generally satisfactory. The inclusion of supply codes for mechanical valve replacements enhanced accuracy but led to fewer eligible patients being included in the sample. This study provides a potentially optimal framework for future research on valve diseases and surgeries using claims databases.