Fall Risk During Inpatient Rehabilitation: Factors Associated with Risk and Limitations with Admission Fall Risk Scoring
Methods: Patient discharges from 01/01-12/31/2014 at a single IRF were reviewed and Functional Independence Measures (FIM) was collected for each patient. Quality data on falls identified “fallers” vs. “non-fallers.” Bivariate and logistic regression (LR) analyses were conducted to identify factors associated with inpatient falls. A random sub-sample of 50 fallers and 50 non-fallers was used to establish the sensitivity/specificity of the risk assessment score utilized by the IRF upon admission.
Results: N=2706. Fallers=207 (7.6%). Gender, diagnosis, age, FIM scores, comorbidity score, onset days, and aphasia were associated with falls. Significant variables from LR: FIM [problem solving] (OR=0.77, CI=0.66-0.88), brain injury (OR=1.9, CI=1.2-3.2), spinal cord injury (OR=1.8, CI=1.02-3), stroke (OR=2.4, CI=1.6-3.8), and male gender (OR=1.5, CI=1.1-2.0). Sensitivity was 0.80 (CI=0.68-0.91) and specificity was 0.28 (0.16-0.40).
Conclusion: Low specificity may be leading to prevention efforts that are too wide-spread and therefore ineffective. A tool which incorporated factors that are associated with falls, including clinical features and patient demographics, may better identify truly high-risk patients, concentrate resources more effectively, and facilitate towards more specific policies and procedures for better outcomes.
Learning Areas:Other professions or practice related to public health
Public health or related nursing
List factors associated with increased risk for falls in the inpatient rehabilitation facility setting. Compare existing risk-assessment tools and their sensitivity and specificity for the identification of patients at risk for falls.
Keyword(s): Quality Improvement, Risk Factors/Assesment
Qualified on the content I am responsible for because: I have a backgroud in both nursing and epidemiology and can use both disciplines to bring together data and ideas for the betterment of injury prevention. I have experience in injury epidemiology research from the New Jersey trauma center and in quality data analysis from the Kessler Institute for Rehabilitation. My interests include the merging of clinical and public health data for injury prevention.
Any relevant financial relationships? No