Original Research: Breaking Through the Bottleneck: Acuity Adaptability in Noncritical Trauma Care.

Am J Nurs

Jacob T. Higgins is an assistant professor at the University of Kentucky (UK) College of Nursing, Lexington, as well as a nurse scientist in trauma/surgical services at UK HealthCare, Lexington, where Rebecca D. Charles is a patient care manager and Lisa J. Fryman is the nursing operations director. Contact author: Jacob T. Higgins, The authors and planners have disclosed no potential conflicts of interest, financial or otherwise.

Published: April 2024

Background: Achieving efficient throughput of patients is a challenge faced by many hospital systems. Factors that can impede efficient throughput include increased ED use, high surgical volumes, lack of available beds, and the complexities of coordinating multiple patient transfers in response to changing care needs. Traditionally, many hospital inpatient units operate via a fixed acuity model, relying on multiple intrahospital transfers to move patients along the care continuum. In contrast, the acuity-adaptable model allows care to occur in the same room despite fluctuations in clinical condition, removing the need for transfer. This model has been shown to be a safe and cost-effective approach to improving throughput in populations with predictable courses of hospitalization, but has been minimally evaluated in other populations, such as patients hospitalized for traumatic injury.

Purpose: This quality improvement project aimed to evaluate implementation of an acuity-adaptable model on a 20-bed noncritical trauma unit. Specifically, we sought to examine and compare the pre- and postimplementation metrics for throughput efficiency, resource utilization, and nursing quality indicators; and to determine the model's impact on patient transfers for changes in level of care.

Methods: This was a retrospective, comparative analysis of 1,371 noncritical trauma patients admitted to a level 1 trauma center before and after the implementation of an acuity-adaptable model. Outcomes of interest included throughput efficiency, resource utilization, and quality of nursing care. Inferential statistics were used to compare patients pre- and postimplementation, and logistic regression analyses were performed to determine the impact of the acuity-adaptable model on patient transfers.

Results: Postimplementation, the median ED boarding time was reduced by 6.2 hours, patients more often remained in their assigned room following a change in level of care, more progressive care patient days occurred, fall and hospital-acquired pressure injury index rates decreased respectively by 0.9 and 0.3 occurrences per 1,000 patient days, and patients were more often discharged to home. Logistic regression analyses revealed that under the new model, patients were more than nine times more likely to remain in the same room for care after a change in acuity and 81.6% less likely to change rooms after a change in acuity. An increase of over $11,000 in average daily bed charges occurred postimplementation as a result of increased progressive care-level bed capacity.

Conclusions: The implementation of an acuity-adaptable model on a dedicated noncritical trauma unit improved throughput efficiency and resource utilization without sacrificing quality of care. As hospitals continue to face increasing demand for services as well as numerous barriers to meeting such demand, leaders remain challenged to find innovative ways to optimize operational efficiency and resource utilization while ensuring delivery of high-quality care. The findings of this study demonstrate the value of the acuity-adaptable model in achieving these goals in a noncritical trauma care population.

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http://dx.doi.org/10.1097/01.NAJ.0001010176.21591.80DOI Listing

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