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A multivariate regression model predicted falls in residents living in intermediate hostel care
J S Chen1, L M March, J Schwarz
1Institute of Bone & Joint Research, Department of Medicine, Level 4, Block 4, Royal North Shore Hospital, University of Sydney, St Leonards, NSW 2065, Australia. jschen@med.usyd.edu.au
Background And Objective:
To evaluate whether individual falls risk could be predicted in a frail elderly population.
Study Design And Setting:
We developed and tested an assessment tool and falls risk score for predicting falls based on a multivariate regression model in a prospective cohort study of intermediate care residents.
Results:
During the follow-up period, 1,736 falls by 1,107 subjects were recorded with an average of 170 falls per 100 person-years. Fifty percent of the study population had at least one fall within a year. Significant independent risk factors were poor balance, cognitive impairment, incontinence, higher illness severity rating, and older age. Twenty-two percent of participants with a falls risk score > or =7 accounted for 42% of the total falls, with a falls rate of 317 per 100 person-years. This rate was a sixfold increase from the falls rate of 52 per 100 person-years observed in participants with a score < 3. A high score (> or =7) indicated almost a 2 in 3 chance of falling, while a low score (<3) indicated approximately a 1 in 7 chance of falling within 6 months.
Conclusion:
The assessment tool and falls risk score could identify individuals in this frail elderly population at high risk of falls.
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