Evidence-Based Selection of a Fall Risk Assessment Tool: A Program Evaluation Review

Abstract

Fall prevention strategies are a consistent topic of discussion for healthcare regarding patient safety, as patient falls are costly to the patient and the organization. This project uses the CDC Framework for Program Evaluation to assess the fall prevention policy of a local hospital system, with particular emphasis on the fall risk assessment tool, Hester Davis. This project also explores the risks and benefits of adopting an alternative fall risk assessment tool, predictive analytics. Predictive analytics uses electronic health record (EHR) data analysis to provide a highly individualized patient fall risk score based on a large variety of patient and environmental factors. Comparative analysis of the two tools was performed in 104 chart reviews, which provided evidence for the use of predictive analytics. Recommendations are provided for a development of a new fall prevention policy that includes predictive analytics as the primary fall risk assessment tool. Based on these recommendations, this project also includes a competency-based orientation toolkit, which can be put into place should the organization choose to transition the policy to utilize predictive analytics as the primary fall risk assessment.