Falls risk factors in an acute-care setting: a retrospective study.

Research findings have been contradictory regarding risk factors for falls in the acute-care setting. Identification of factors that place individuals at risk of falling in this setting are a priority because falls result in high morbidity and mortality and thus increased healthcare costs. The purpose of this study was to extend knowledge beyond the known risk factors of age and medical diagnosis by comparing the characteristics of 301 adults who fell while hospitalized with a matched sample of adults who did not fall while hospitalized. A descriptive, retrospective, comparative design was used. The fall and non-fall group were matched on age and primary medical diagnosis at the time of discharge. Data were collected from hospital incident reports and medical records. Logistic regression for matched groups identified 5 risk factors, as follows. Incontinence. The odds of falling were 11.3 (CI = 3.85, 33.05) times greater for those who were incontinent than for those who were not incontinent. Long hospital stay. The odds of falling were 9.9 (CI = 4.89, 19.88) times greater for those hospitalized 19 days or longer than for those hospitalized less than 19 days. Dependency for ambulation. The odds of falling were 6 (CI = 2.83, 12.84) times greater for those who were dependent for ambulation than for those who were independent. Independency for hygiene. The odds of falling were 2.5 (CI = 1.23, 4.88) times greater for those who were independent for hygiene than for those who were dependent. Lack of regular exercise. The odds of falling were twice as high (CI = 1.00, 3.82) for those who did not exercise regularly as for those who exercised regularly. These findings suggest that ongoing assessment may be more important than the admission assessment in identifying risk factors for falls in the acute-care setting. No 2 studies have found exactly the same set of risk factors, although some findings are consistent across studies. This suggests that those risk factors that are consistent across studies may identify persons who are at the greatest risk for falls and that other risk factors for falls are specific to a patient population.