Pooled testing is an established strategy for efficient surveillance testing of infectious diseases with low-prevalence. Pooled testing works by combining clinical samples from multiple individuals into one test, where a negative result indicates the whole pool is disease free and a positive result indicates that individual testing is needed. Here we present a straightforward and simple method for pooled testing that uses the properties of Hadamard matrices to design optimal pooling strategies. We show that this method can be used to efficiently identify positive specimens in large sample sizes by simple pattern matching, without the requirement of complex algorithms.