Objective: Drugs increase fall risk and decrease performance on balance and mobility tests. Conversely, whether biofeedback training to reduce fall risk also decreases scores on a published drug-based fall risk index has not been documented. Forty-eight community-dwelling older adults underwent either treadmill gait training plus visual feedback (+VFB), or walked on a treadmill without feedback. The Quantitative Drug Index (QDI) was derived from each participant's drug list and is based upon all cause drug-associated fall risk. Analysis of covariance assessed changes in the QDI during the study, and data is presented as mean ± standard error of the mean. Results: The QDI scores decreased significantly (p = 0.031) for participants receiving treadmill gait training +VFB (- 0.259 ± 0.207), compared to participants who walked on the treadmill without VFB (0.463 ± 0.246). Changes in participants QDI scores were dependent in part upon their age, which was a significant covariate (p = 0.007). These preliminary results demonstrate that rehabilitation to reduce fall risk may also decrease use of drugs associated with falls. Determination of which drugs or drug classes that contribute to the reduction in QDI scores for participants receiving treadmill gait training +VFB, compared to treadmill walking only, will require a larger participant investigation. Trial Registration ISRNCT01690611, ClinicalTrials.gov #366151-1, initial 9/24/2012, completed 4/21/2016

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Background: The development of an objective and comprehensive drug-based index of physical function for older adults has the potential to more accurately predict fall risk. Design: the index was developed using 862 adults (ages 57–85) from the National Social Life, Health, and Aging Project (NSHAP) Wave 1 study. The index was evaluated in 70 adults (ages 51–88) from a rehabilitation study of dizziness and balance. Methods: The prevalence among 601 drugs for 1,694 side effects was used with fall history to determine the magnitude of each side effect's contribution towards physical function. This information was used to calculate a Medication-based Index of Physical function (MedIP) score for each individual based on his or her medication profile. The MedIP was compared to the timed up and go (TUG) test as well as drug counts using receiver operating characteristic (ROC) analysis. The associations between various indices of physical function and MedIP were calculated. Results: Within the NSHAP data set, the MedIP was better than drug counts or TUG at predicting falls based on ROC analysis. Using scores above and below the cutpoint, the MedIP was a significant predictor of falls (OR = 2.61 [95% CI 1.83, 3.64]; P < 0.001). Using an external data set, it was shown that the MedIP was significantly correlated with fall number (P = 0.044), composite physical function (P = 0.026) and preferred gait speed (P = 0.043).