A multivariate fall risk assessment model for VHA nursing homes using the Minimum Data Set

作者：French Dustin D^*; Werner Dennis C; Campbell Robert R; Powell Cope Gail M; Nelson Audrey L; Rubenstein Laurence Z; Bulat Tatjana; Spehar Andrea M

来源：Journal of the American Medical Directors Association, 2007, 8(2): 115-122.

DOI：10.1016/j.jamda.2006.08.005

• accidental falls
• falls
• patient safety
• nursing homes
• long-term care
• minimum data set
• risk factors
• risk assessment
• multivariate analysis
• veterans

Objectives: The purpose of this study was to develop a multivariate fall risk assessment model beyond the current fall Resident Assessment Protocol (RAP) triggers for nursing home residents using the Minimum Data Set (MDS).
Design: Retrospective, clustered secondary data analysis. Setting: National Veterans Health Administration (VHA) long-term care nursing homes (N = 136).
Participants: The study population consisted of 6577 national VHA nursing home residents who had an annual assessment during FY 2005, identified from the MDS, as well as an earlier annual or admission assessment within a 1-year look-back period.
Measurement. A dichotomous multivariate model of nursing home residents coded with a fall on selected fall risk characteristics from the MDS, estimated with general estimation equations (GEE).
Results: There were 17 170 assessments corresponding to 6577 long-term care nursing home residents. The increased odds ratio (OR) of being classified as a faller relative to the omitted "dependent" category of activities of daily living (ADL) ranged from OR = 1.35 for "limited" ADL category up to OR = 1.57 for "extensive-2" ADL (P < .0001). Unsteady gait more than doubles the odds of being a faller (OR = 2.63, P < .0001). The use of assistive devices such as canes, walkers, or crutches, or the use of wheelchairs increases the odds of being a faller (OR = 1.17, P < .0005) or (OR = 1.19, P < .0002), respectively. Foot problems may also increase the odds of being a faller (OR = 1.26, P < .0016). Alzheimer's or other dementias also increase the odds of being classified as a faller (OR = 1.18, P < .0219) or (OR = 1.22, P < .0001), respectively. In addition, anger (OR = 1.19, P < .0065); wandering (OR = 1.53, P < .0001); or use of antipsychotic medications (OR = 1.15, P < .0039), antianxiety medications (OR = 1.13, P < .0323), or antidepressant medications (OR = 1.39, P < .0001) was also associated with the odds of being a faller.
Conclusions: This national study in one of the largest managed healthcare systems in the United States has empirically confirmed the relative importance of certain risk factors for falls in long-term care settings. The model incorporated an ADL index and adjusted for case mix by including only long-term care nursing home residents. The study offers clinicians practical estimates by combining multiple univariate MDS elements in an empirically based, multivariate fall risk assessment model.

• 出版日期2007-2