Early Warning Escalation System for Care Aides in Long-Term Patient Monitoring

• Author(s): Akonasu Qudus Hungbo ; Christiana Adeyemi ; Opeoluwa Oluwanifemi Ajayi
• Paper ID: 1709971
• Page: 321-345
• Published Date: 31-01-2020
• Published In: Iconic Research And Engineering Journals
• Publisher: IRE Journals
• e-ISSN: 2456-8880
• Volume/Issue: Volume 3 Issue 7 January-2020

Abstract

Timely recognition and response to patient deterioration in long-term care facilities remain critical challenges, especially as frontline care aides often serve as the first point of observation. This paper introduces an Early Warning Escalation System (EWES) specifically designed to empower care aides in long-term patient monitoring. The proposed system integrates observational cues, structured reporting protocols, and digital escalation pathways to ensure rapid clinical intervention. By leveraging simplified early warning indicators such as changes in mobility, behavior, appetite, and respiratory effort EWES equips non-licensed care staff with the tools and confidence to identify and communicate potential health declines effectively. The system utilizes a tiered escalation model where initial observations trigger a standardized response, including documentation through a mobile interface and immediate alerts to registered nurses or supervising clinicians. The model is informed by elements of the Modified Early Warning Score (MEWS) but is adapted for long-term care environments where continuous vital sign monitoring may not be feasible. A mixed-methods pilot study involving training workshops, workflow integration, and post-implementation evaluation demonstrated improved communication efficiency, earlier clinical response, and reduced incidences of avoidable hospital transfers. Care aides reported increased confidence and clarity in escalation roles, while nursing staff observed improved patient surveillance and response timelines. Additionally, the digital tool’s embedded audit trail supports quality assurance and regulatory compliance. By formalizing the observational role of care aides within a validated clinical framework, EWES bridges the gap between daily caregiving and medical intervention, contributing to safer and more responsive long-term care. This study highlights the importance of workforce inclusivity in patient safety models and underscores the potential of tailored early warning systems to enhance multidisciplinary coordination in non-acute care settings. The EWES model offers a scalable and adaptable approach to improving patient outcomes and institutional readiness in the face of rising long-term care demands.

Keywords

early warning system, care aides, long-term care, patient deterioration, escalation protocols, monitoring, clinical communication, MEWS adaptation, digital health, patient safety.

Citations

IRE Journals:
Akonasu Qudus Hungbo , Christiana Adeyemi , Opeoluwa Oluwanifemi Ajayi "Early Warning Escalation System for Care Aides in Long-Term Patient Monitoring" Iconic Research And Engineering Journals Volume 3 Issue 7 2020 Page 321-345

IEEE:
Akonasu Qudus Hungbo , Christiana Adeyemi , Opeoluwa Oluwanifemi Ajayi "Early Warning Escalation System for Care Aides in Long-Term Patient Monitoring" Iconic Research And Engineering Journals, 3(7)