RESUMO
BACKGROUND: Administrative claims for aortic stenosis (AS) regurgitation may be useful, but their accuracy and ability to identify individuals at risk for valve-related outcomes have not been well characterized. METHODS: Using echocardiographic (transthoracic echocardiogram [TTE]) reports linked to US Medicare claims, 2017 to 2018, the performance of candidate International Classification of Diseases, Tenth Revision claims to ascertain AS/aortic regurgitation was evaluated. The optimal performing algorithm was tested against outcomes at 1-year after TTE in a separate 100% sample of US Medicare claims, 2017 to 2019. RESULTS: Of those included in the derivation (N=5497, mean age 74.4±11.0 years, 49.7% female), any AS or aortic regurgitation was present in 24% and 38.8%, respectively. The sensitivity and specificity of International Classification of Diseases, Tenth Revision code I35.0 for identification of any AS was 53.1% and 94.8%, respectively. Among those with an I35.0 code, 40.3% had severe AS. Claims were unable to distinguish disease severity (ie, severe versus nonsevere) or subtype (eg, bicuspid or rheumatic AS), and were insensitive and nonspecific for aortic regurgitation of any severity. Among all beneficiaries who received a TTE (N=4 033 844), adjusting for age, sex, and 27 comorbidities, those with an I35.0 code had a higher adjusted risk of all-cause mortality (adjusted hazard ratio, 1.33 [95% CI, 1.31-1.34]), heart failure hospitalization (adjusted hazard ratio, 1.37 [95% CI, 1.34-1.41]), and aortic valve replacement (adjusted hazard ratio, 34.96 [95% CI, 33.74-36.22]). CONCLUSIONS: Among US Medicare beneficiaries receiving a TTE, International Classification of Diseases, Tenth Revision claims, though identifying a population at significant greater risk of valve-related outcomes, failed to identify nearly half of individuals with AS and were unable to distinguish disease severity or subtype. These results argue against the widespread use of International Classification of Diseases, Tenth Revision claims to screen for patients with AS and suggests the need for improved coding algorithms and alternative systems to extract TTE data for quality improvement and hospital benchmarking.
