Primary-care falls prevention: fewer falls and lower costs in rural older adults

Design

Within-trial economic evaluation of a cluster randomised controlled trial

Population

2,610 community-dwelling older adults in rural China

Primary outcome

Incremental cost, falls prevented and QALYs

Effect

Falls absolute risk −8.6%; +0.024 QALYs; mean saving ¥293 (−¥145 to ¥727)

FAMILY was a 12-month cluster randomised trial of 2,610 community-dwelling older adults in rural China, which had already shown that a balance and functional exercise programme integrated into primary healthcare reduced falls. This Age and Ageing paper, published in September, reports the within-trial economic evaluation from a health-system perspective.

The intervention reduced the absolute risk of falls by 8.6% and added 0.024 quality-adjusted life years per person over about a year. It was dominant: healthcare use costs were lower (¥1,517 vs ¥1,831), more than offsetting a delivery cost of ¥20 per participant, for a mean saving of ¥293 (95% CI −¥145 to ¥727). The probability of saving money was 90% and of being cost-effective 96%.

The lesson is plausible for other rural primary care systems, including India's: a low-cost exercise programme delivered through existing primary healthcare workers reduced falls and paid for itself. Health systems and costs differ, and the cost-saving interval crosses zero, but the case for implementation does not depend on savings when falls are reduced so cheaply.

• Offer a structured balance and functional exercise programme to community-dwelling older adults at risk of falls.
• Deliver it through existing primary care or community health workers rather than specialist clinics.
• Target people with previous falls, fear of falling or slow gait first.
• Track falls and emergency visits to show local benefit.

Why it matters

It shows falls prevention can be delivered cheaply at scale in low-resource primary care.

Don't overread it

Costs are from rural China; the saving's confidence interval crosses zero, so the dominance result is probable rather than certain.

The statistics, in plain English

Dominant means cheaper and more effective. The probability of saving money (90%) comes from resampling the data many times. An 8.6% absolute reduction means about 9 fewer people in every 100 fell over the year.

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