Background: International Classification of Diseases codes for rheumatic heart disease (RHD) (ICD-10 I05-I08) include valvular heart disease of unspecified origin, limiting their usefulness for estimating RHD burden. An expert opinion-based algorithm was developed to increase their accuracy for epidemiological case ascertainment. The algorithm included codes not defaulting to RHD (‘probable’) plus selected codes pertaining to mitral valve involvement in patients <60 years (‘possible’). We aimed to determine the positive predictive value (PPV) for RHD of algorithm-selected hospital admissions. Methods: Chart reviews of RHD-coded admissions (n=368) to Western Australian tertiary hospitals (2009–2016) authenticated RHD diagnosis. We selected all cases with algorithm-positive codes from populations at high-risk of RHD and an age-stratified random sample from low-risk groups. RHD status was determined from echocardiographic reports or clinical diagnosis in charts. PPVs were compared by population risk status (high-risk/low-risk), age group, gender, principal/secondary diagnosis and probable/possible codes. Results: High-risk patients had higher PPVs than low-risk patients (83.8% vs 54.9%, p<0.0001). PPVs were 91.5% and 51.5% respectively for algorithm-defined ‘probable RHD’ and ‘possible’ codes (p<0.0001). The PPVs in low-risk patients were higher for principal diagnoses than secondary diagnoses (84.5% vs 44.8%, weighted p<0.0001) but were similar in high-risk patients (92.5% vs 81.7%, p=0.096). Conclusion: The algorithm performs well for RHD coded as a principal diagnosis, ‘probable’ codes or in populations at high risk of RHD. Refinement is needed for identifying true RHD in low-risk groups.