Implementing an Evidence-Based Fall Prevention Program in an Outpatient Clinical Setting
Published Date:Oct 28 2013
Source:J Am Geriatr Soc. 61(12):2142-2149.
Pubmed Central ID:PMC4707656
Funding:5R18CE001723/CE/NCIPC CDC HHS/United States
CC999999/Intramural CDC HHS/United States
Few evidence-based fall prevention programs have been evaluated for adoption in clinical settings. This study investigated the dissemination potential of a Tai Ji Quan-based program, previously shown efficacious for reducing risk of falls in older adults, through outpatient clinical settings.
A single-group pre-post design in which participants attended a twice weekly Tai Ji Quan training program for 24 weeks.
Communities in Lane County, Oregon.
Referral patients (N = 379) aged 65 and older living independently.
Using the RE-AIM framework, the primary outcome was the proportion of participating healthcare providers who made referrals. Secondary outcomes were the proportion of referred patients agreeing to participate and enrolling in the program, and measures of program implementation, maintenance, and effectiveness (on measures of falls, balance, gait, physical performance, and balance efficacy).
Of the 252 providers invited to participate, 157 made referrals (62% adoption rate). Of 564 patients referred, 379 (67% reach) enrolled in the program, which was successfully implemented in senior/community centers with good fidelity. Of the total number of participants, 283 completed the program (75% retention) and 212 of these attended ≥75% of the total (48) sessions. Participants reported a reduction in falls with an incidence rate of 0.13 falls per person-month and showed significant improvement from baseline in all outcome measures. A 3-month post-intervention follow-up indicated encouraging levels of program maintenance among providers, patients, and community centers.
A protocol to refer patients at increased risk of falling to a Tai Ji Quan-based program was successfully implemented among healthcare providers. The evidence-based program appears readily scalable and exportable with potential for substantial clinical and public health impact.
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