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Preventing Overrides of Severe Drug Allergy Alerts Initiative: an Implemented System Upgrade
Laila Carolina Abu Esba1, Samar Al Moaiseib2, Norah Saud BinSabbar3
1King Abdulaziz Medical City, Ministry of National Guard, Health Affairs, Joint Appointment Lecturer of Pharmacy Practice, King Saud Bin Abdulaziz University for Health Sciences, King Abdullah International Medical Research Centre, PO Box 22490, Riyadh, 11426, Kingdom of Saudi Arabia. abuesbala@ngha.med.sa.
Abstract:
Administering medications to patients with documented drug hypersensitivity reactions (DHR) poses a significant risk for adverse events, ranging from mild reactions to life-threatening incidents. Electronic healthcare systems have revolutionized the modern clinical decision-making process, with built in warnings. However, as these alerts become a routine part of healthcare provider's workflow, alert fatigue becomes a challenge. This study was conducted within the Ministry of National Guard Health Affairs (MNGHA), a government healthcare system in Saudi Arabia. A taskforce of experts was formed to develop an electronic path that would prevent unintentional overrides of severe drug allergy alerts. The system underwent rigorous testing, and monitoring parameters were established. We outline the implementation of a system upgrade designed to trigger an alternative interruption in the computerized physician order entry (CPOE) process, distinct from the regular allergy pop-up alerts. The alternate path is activated upon a CPOE with a drug-to-drug match and a documented severe drug allergy symptom, necessitating co-signature form another prescriber before proceeding. The adopted upgrade is a proactive approach to enhance medication safety in electronic healthcare systems, ensuring that serious allergy-related warnings are not overridden, ultimately enhancing patient safety. Further monitoring will confirm the safety and effectiveness of this measure. This study provides a model for institutions seeking to prevent allergy-related harm within their patient population.
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