Helping pharmacists to reduce fall risk in long-term care: A clinical tool to facilitate the medication review process.

Background: One-third to one-half of adults older than 65 fall at least once per year. Fall prevention through medication management requires little effort and has consistently been shown to reduce risk of falls. The objective of this study was to further develop and perform preliminary pilot testing of an algorithm designed to assist consultant pharmacists in systematically identifying medications that might be modifiable, in order to reduce the risk of falls in older adults. We hypothesized that algorithm use would increase the number of fall-related medication change recommendations made to physicians.

Methods: Four consultant pharmacists were trained to use the algorithm during their routine medication reviews over a 3-week period. An informal survey was administered at the end of the study period to assess the algorithm.

Results: Overall, 51% of residents of long-term facilities had 1 or more recommendations for medication changes related to reducing fall risk (range 0-3 recommendations per resident), with an average 0.675 recommendations made per resident. There were more recommendations for men compared with women and for residents receiving more medications, but the number of recommendations did not correspond with age. All 4 pharmacists agreed that the algorithm was useful and worthwhile.

Discussion: The absolute 20% increase in recommendations related to falls supports the study hypothesis. Time was cited as a barrier to using the algorithm, but this should decrease with continued use of this tool.

Conclusion: This preliminary study furthered the development of and confirmed the possible utility and acceptability of a fall risk-reducing algorithm that may be used in practice.