Evaluation of a Machine Learning-Based Decision Support Intervention for Inpatient Falls

Inpatient falls are frequent adverse events, with various injuries occurring in one-third of falls. International practice guidelines recommend multifaceted risk assessment and risk-targeted interventions through multifactorial activities. However, the effectiveness is mixed for such recommendations implemented using traditional approaches. This study proposed a well-designed systemic and clinical decision support approach using machine learning techniques to leverage the implementation of preventive activities of nursing processes leading to outcome changes.