A case control study to improve accuracy of an electronic fall prevention toolkit

Patient falls are a serious and commonly report adverse event in hospitals. In 2009, our team conducted the first randomized control trial of a health information technology-based intervention that significantly reduced falls in acute care hospitals. However, some patients on intervention units with access to the electronic toolkit fell. The purpose of this case control study was to use data mining and modeling techniques to identify the factors associated with falls in hospitalized patients when the toolkit was in place. Our ultimate aim was to apply our findings to improve the toolkit logic and to generate practice recommendations. The results of our evaluation suggest that the fall prevention toolkit logic is accurate but strategies are needed to improve adherence with the fall prevention intervention recommendations generated by the electronic toolkit.