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Identification of Older Adults at Risk for Falls with Drug-Based IndicesHall, Courtney D., Grieshaber, Emily, Hendricks, Blaine, Lewis, Kammie A., McGrady, Seth A., Morton, Megan Lea, Odle, Brian L., Panus, Peter C. 13 February 2020 (has links)
Purpose/Hypothesis: Falls in the older adult population are the leading cause of fatal and non-fatal injuries in America. Polypharmacy, the use of multiple medications, has been identified as a major risk factor for falls in older adults. A variety of medication screens exist that identify adverse effects of medications which can directly impact fall risk; however, current screening measures have limitations. The Quantitative Drug Index (QDI) is a new, clinically anchored index to quantify all potential adverse effects associated with drug-mediated fall risk. The purpose of this study was to validate the QDI as a fall risk screening tool.
Number of Subjects: 138 adults were recruited from local senior centers and screened. Inclusion criteria: community-dwelling, age 60 to 89 years, and currently prescribed at least one medication. Exclusion criteria: progressive neurological disorders, unstable medical conditions, cognitive impairment, severe depression or anxiety, severe lower extremity impairment that would impact mobility, and severe vision impairment.
Materials and Methods: Mobility and balance outcome measures related to fall risk included: 30-second chair stand test, 10-meter walk test, Timed Up and Go (TUG) and Dynamic Gait Index (DGI). Self-report measures of fall risk included fall history, Fall Risk Questionnaire (FRQ) and Activity-specific Balance Confidence scale (ABC). The QDI was derived from each participant's medications. Participants were classified as either fallers or nonfallers based on self-report history of falls within the past year. Nonparametric Spearman’s Rho correlations were used to determine relationships between faller status and measures of fall risk. A receiver operating characteristic (ROC) curve analysis determined cutoff scores for outcome measures related to faller status.
Results: A fair to moderate relationship between the QDI and several physical performance and self-report measures was identified: FRQ (r=0.363), ABC (r=-0.401), DGI (r=-0.360). However, little to no relationship was found between faller status and QDI score (r=0.221). The ROC analysis determined the area under the curve for QDI was 0.63 with a cutoff score of 2.5 yielding sensitivity of 78% and specificity of 47%.
Conclusions: The development of the QDI was an interdisciplinary effort between pharmacists and physical therapists to screen for fall risk in older individuals. The QDI offers a better way to quantify the adverse effects of drugs on mobility compared with simple drug counts. The QDI alone does not identify individuals at fall risk; however, the QDI is significantly correlated to several measures of fall risk, including FRQ, ABC, and DGI. The ROC Curve Analysis identified a cutoff score for fall risk for the QDI which was found to have similar sensitivity and specificity to the TUG.
Clinical Relevance: The QDI could be incorporated into electronic medical records to identify patients who may be at fall risk and would be appropriate for further balance and mobility evaluation.
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