Falls in inpatient rehabilitation facilities (IRFs) complicate patient recovery and generate a substantial financial burden. Identifying with patients are likely to fall is an important step to reducing falls. The Morse Fall Scale (MFS), a traditional acute care assessment tool, has been used in IRFs, but research suggests it is not predictively accurate in that setting. Retrospective studies indicate Activity Measure for Post-Acute Care (AM-PAC) subscales and Quality Indicators (QI) may be used to enhance fall prediction accuracy in rehabilitation facilities, but further prospective investigation is needed. Using QI codes to identify fall risk would reduce assessment burden as they are already part of required IRF documentation. Therefore, the purpose of this dissertation was to 1) analyze the associations between QI codes and falls, 2) calculate the predictive accuracy of a QI-based fall risk assessment called the IRF Scale, and 3) compare the accuracy of the IRF Scale with a 2-Item QI scale, the MFS, and AM-PAC in predicting which patients would fall in a prospective sample.
