The data analysis work of KU's Costas Tsatsoulis will look for ways to reduce errors in both the collection and transfusion of blood. Most error reporting looks at what happened, but near-miss reporting looks at why something almost happened. Near misses, says Tsatsoulis, are far more interesting and potentially more useful than errors. More numerous than critical errors, near misses provide more data and also reveal a wider variety of problems. Errors aren't only caused by humans.
Errors can come from the environment, such as bad lighting.
The data analysis will identify where the faults lie. Together these organizations handle a large percentage of the nation's blood supply. The error and near-miss data they gather will be forwarded to Tsatsoulis and his students for analysis. They need automated methods that show causality and a clustering of events around certain parameters. Once our computers identify a pattern, humans then will study it.