We examine a key task in biomedical text processing, normalization of disorder mentions. We present a multi-pass sieve approach to this task, which has the advantage of simplicity and modularity. Our approach is evaluated on two datasets, one comprising clinical reports and the other comprising biomedical abstracts, achieving state-of-the-art results.