A J Lane1. 1. College of Nursing, University of Cincinnati Medical Center, Ohio, USA.
Abstract
PURPOSE: To evaluate the effectiveness of a Falls Prevention Program (FPP) in reducing patient fall rate and to examine predictors of falls. SAMPLE: A nonrandom, stratified convenience sample of 292 subjects was selected from medical-surgical/critical care patients at a large community hospital system. The sample included 101 patients who fell prior to the FPP, 98 patients who fell after FPP, and 93 patients who did not fall after FPP. METHODS: A retrospective, preimplementation/long-term, postimplementation, comparative, descriptive design was used to address differences in patients who fell before and after FPP. Prediction factors associated with incidence of falls were assessed using a sample that included patients who fell and patients who did not fall in 1995. Data were collected about the patients and the fall incidents via a retrospective chart and incident report review. FINDINGS: No decrease in patient fall rate was found between patients who fell before and after implementation of the FPP. Patients tended to fall attempting to get out of the bed, suffering no injury. Model testing of the linear results of patients who fell and patients who did not fall after the implementation of the FPP demonstrated that fall prediction factors included age 60 or over, impaired memory, muscle weakness, and need of ambulatory assistance (Log linear chi-square: 6.048, df 4, p = 0.811 (p > .05). CONCLUSION: Identification of patients who exhibit characteristics of the fall prediction model may be useful in reducing falls in medical-surgical/critical care patients. Further testing of the four-factor model with subsequent inclusion of focused interventions may impact the incidence of falls.
PURPOSE: To evaluate the effectiveness of a Falls Prevention Program (FPP) in reducing patient fall rate and to examine predictors of falls. SAMPLE: A nonrandom, stratified convenience sample of 292 subjects was selected from medical-surgical/critical care patients at a large community hospital system. The sample included 101 patients who fell prior to the FPP, 98 patients who fell after FPP, and 93 patients who did not fall after FPP. METHODS: A retrospective, preimplementation/long-term, postimplementation, comparative, descriptive design was used to address differences in patients who fell before and after FPP. Prediction factors associated with incidence of falls were assessed using a sample that included patients who fell and patients who did not fall in 1995. Data were collected about the patients and the fall incidents via a retrospective chart and incident report review. FINDINGS: No decrease in patient fall rate was found between patients who fell before and after implementation of the FPP. Patients tended to fall attempting to get out of the bed, suffering no injury. Model testing of the linear results of patients who fell and patients who did not fall after the implementation of the FPP demonstrated that fall prediction factors included age 60 or over, impaired memory, muscle weakness, and need of ambulatory assistance (Log linear chi-square: 6.048, df 4, p = 0.811 (p > .05). CONCLUSION: Identification of patients who exhibit characteristics of the fall prediction model may be useful in reducing falls in medical-surgical/critical care patients. Further testing of the four-factor model with subsequent inclusion of focused interventions may impact the incidence of falls.
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