Baltimore-based Johns Hopkins' Armstrong Institute for Patient Safety and Quality developed SPADE (Symptom-Disease Pair Analysis of Diagnostic Error), an approach that allows providers to use databases instead of having staff go over medical records for more information to reduce diagnostic errors. The strategy uses big data to accelerate the monitoring process to reduce errors and uses statistical analyses to identify patterns that can predict diagnostic errors. It mines available databases for common symptoms that lead patients to visit a doctor and compares the data with diseases that are often misdiagnosed. Johns Hopkins says the approach is likely to be most effective with acute or subacute conditions for which a misdiagnosis could have serious consequences - hospitalization, disability or death within six months. The "big three" conditions that lead to death or disability after a diagnostic error are infections, cancer or vascular events.
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