Implementation of the EPIC Deterioration Index Tool on a Medical/Surgical Unit

Purpose: Early detection is crucial for preventing clinical deterioration. This quality improvement project aimed to investigate the application of a machine-based learning tool in the medical/surgical setting. Description: This quality improvement project assesses the implementation and performance of the Epic Deterioration Index tool on a 32-bed medical/surgical unit at an academic medical center. During the trial period, the tool was operationalized in conjunction with the organization’s rapid response criteria to enhance the early identification of deterioration and to evaluate nurses’ competency in activating a rapid response for high-risk patients. Outcome: Results demonstrate a 72% responsiveness rate among nurses in recognizing patients at risk of deterioration. While the number of rapid responses increased during the trial period, the number of patients upgraded to the intensive care unit decreased significantly. Conclusion: The EPIC Deterioration Index tool, when used in conjunction with rapid response criteria, facilitates early identification of patient deterioration. In addition, it has great potential to prevent the need for upgrading a patient to the intensive care unit. This offers a promising future in detecting risk and enhancing the quality of care.