Accurately identifying patients at risk for alcohol withdrawal on inpatient psychiatric units
Jessica Hayes, RN Heading link
Clinical Issue/Practice Problem: Identifying hospitalized patients at risk for alcohol withdrawal syndrome (AWS) is crucial for patient safety. Current treatment decisions at a suburban psychiatric hospital are made using the Alcohol Use Disorders Identification Test (AUDIT), a tool that is not validated for the inpatient population. This quality improvement project aimed to help inpatient psychiatric nurses more accurately identify patients at risk for AWS using evidence-based measurements.
Summary of Supporting Literature: Evidence supports measuring risk of AWS at admission using a standardized tool (Alvanzo et. al, 2020; Claus, 2020; Mezzadri, 2024). The AUDIT is not recommended for hospital use, and the Prediction of Alcohol Withdrawal Severity Scale (PAWSS) was identified as the only validated tool for hospitalized patients (Alvanzo et. al, 2020).
Project Implementation: Using the Six Sigma Method, trained staff implemented the PAWSS. Nurses continued to assess AWS risk using AUDIT and patients were reassessed by project staff using PAWSS. The number of patients identified as “at-risk” using AUDIT was compared to the number of patients identified as “at-risk” using the PAWSS.
Outcomes: 84 psychiatric inpatients were assessed, and the AUDIT tool significantly underestimated the number of patients at risk of developing AWS compared to the validated PAWSS tool (p=0.0002).
Clinical Implications for Practice: This project demonstrates the importance of using validated, evidence-based tools; providers using AUDIT misdiagnosed approximately half the inpatients who were at high risk of developing complicated AWS. Changing the admission process to use PAWSS instead of AUDIT will promote accurate assessments and improve patient safety.