Harms caused during healthcare encounters are pervasive and occur at an alarming rate; therefore, building a set of computational detection methodologies in the adverse event area is urgently needed to address this problem. To understand the entire range of adverse event detection methods currently in practice we have developed a computational adverse event detection matrix. This structure is made of methods used presently at US hospitals to detect patient safety events. It contains adverse event 1) concepts and 2) synthesized detection strategies as well as calculations of overlap of coded data in the subset of algorithms implemented completely computationally. Most importantly, this matrix provides a clear picture of coverage gaps in the detection of adverse events.
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