Speakers - WNSC 2024

Patrick Dwyer

  • Designation: Atlantic Health Systems- Hackettstown Medical Center
  • Country: USA
  • Title: CAM We Talk about Advancing Geriatric Nursing Management by Optimizing the Electronic Health Record

Abstract

Delirium is a potentially life-threatening geriatric emergency.  When a patient is admitted, the Confusion Assessment Method (CAM) can be utilized to detect and potentially prevent a patient from developing delirium while admitted in an acute care setting. A progressive care unit at a community hospital was noted to have a delirium rate lower than the national average. The author’s hypothesized education and observation of the CAM on admission would impact identification rates of delirious patients.

This was a quantitative quasi-experimental quality improvement (QI) project with a sample of 1,506. Baseline data were obtained from 1,488 charts of patients admitted in the previous eight months. The percentage of patients that were identified as delirious was 2%.  The team members from the progressive care unit all received one-on-one education regarding the CAM with embedded case studies. Subsequently, trained nurses were observed for accurate CAM assessments on admission. During the project period, zero patients were identified as delirious on admission. Three patients were noted to have disorientation on day two of admission.  On day three, one additional patient was identified to be disoriented in some manner. The post-implementation data yielded a delirium rate of 22% and aligned with the national average. The data was clinically significant as delirium identification rates improved.

Accurate CAM assessments on admission to obtain a baseline score is essential for early identification of delirium. The subsequent CAM assessments were not observed; however, based on the chart audits accurate CAMs were conducted. Further recommendations include observing subsequent assessments and implementing the project on other units. Additionally, the electronic health record was optimized to trigger the delirium care plan when signs or symptoms of confusion were charted. Predictive Delirium Models (PDM) are in development which may better assist with identifying those patients at risk and minimizing or preventing adverse outcomes. Limitations to this project include one unit, study design, and retrospective data review.   

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