Speakers - WNSC 2024

Mackwell Cristen

  • Designation: Atlantic Health Systems- Hackettstown and Newton Medical Centers
  • Country: USA
  • Title: Predictive Models: A New Age in Patient Care

Abstract

Early recognition of the deteriorating patient is important for preventing cardiopulmonary arrest and reducing mortality. Early Warning Scores (EWS) are a composite evaluation of a patient's basic physiology, changes in the score are the first indicators of clinical decline and are used to prompt further patient assessment. Predictive models are an evidence-based approach to increasing patient safety, that identifies patients who are most at-risk for clinical decompensation. A midsize integrated hospital system implemented a predictive model with a proactive approach for managing decline. A community hospital within the system hypothesized that the predictive model would reduce rapid responses within six hours of admission. The primary outcome of the quality improvement project was to ascertain the impact of a predictive model on rapid responses within six hours of admission.

This was a quantitative, quasi-experimental quality improvement project with retrospective data review. Data were collected at baseline in 2019 and post-implementation from January 2020 to December 2023 for the total number of rapid responses within six hours of admission. The EHR tool was designed to include guidelines for the nurses to consider when completing a focused assessment before calling a provider. Each shift, the primary nurse reviews the scores and assesses their patients. The clinical specialist or charge nurse also reviews the scores, completes a chart review, assesses the patient, and coordinates a discussion with the primary nurse and provider to prevent patient decline.

The number of rapid responses within six hours of admission decreased from 25% to 3.5%, yielding an 86% reduction in RRTs within six hours of admission from 2019 through December of 2023. Utilizing an interdisciplinary, evidence-based approach to decreasing in-hospital events is crucial in reducing mortality. The data yielded both clinical and statistical significance. This quality improvement project could easily be replicated and was fiscally responsible. Limitations to this project include one community hospital, retrospective review, and team member turnover. Nursing implications for the study include additional studies implementing EWS to improve patient safety. 

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