The construction of a patient record-based risk model for recurrent falls among elderly people living in the community

Background. Predictive models of fall risk in the elderly living in the com munity may contribute to the identification of elderly at risk for recurren t falling. Objectives. Our aim was to investigate occurrence, determinants and health consequences of falls in a community-dwelling elderly population and the co ntribution of data from patient records to a risk model of recurrent falls. Methods. A population survey was carried out using a postal questionnaire. The questionnaire on occurrence, determinants and health consequences of fa lls was sent to 2744 elderly persons of 70 years and over, registered in fo ur general practices (n = 27 000). Data were analysed by bivariate techniqu es and logistic regression. Results. A total of 1660 (60%) responded. Falls (greater than or equal to1 fall) in the previous year were reported by 44%: one-off falls by 25% and r ecurrent falls (greater than or equal to2 falls) by 19%. Women had signific antly more falls than men. Major injury was reported by 8% of the fallers; minor injury by 49%. Treatment of injuries was by the GP in 67% of cases. F rom logistic regression, a risk model for recurrent falls, consisting of th e risk factors female gender, age 80 years or over, presence of a chronic n eurological disorder, use of antidepressants, problems of balance and sense organs and complaints of muscles and joints was developed. The model predi cted recurrent falls with a sensitivity of 64%, a specificity of 71%, a pos itive predictive value of 42% and a negative predictive value of 86%. Conclusion. A risk model consisting of six variables usually known to the G P from the patient records may be a useful tool in the identification of el derly people living in the community at risk for recurrent falls.