Literature DB >> 28858955

Variability in Acuity in Acute Care.

Amy L Garcia1.   

Abstract

OBJECTIVE: This study was designed to describe variable acuity among 1 population of acute care patients.
BACKGROUND: Acuity, defined as the individual patient need for nursing care, can inform level of care, nurse staffing, and the nurse-to-patient assignment. Nurse-generated data in the electronic health record can be mined and analyzed for decision support.
METHODS: This study used a descriptive, retrospective analysis of repeated measures of acuity generated from 28 739 nursing assessments of 405 consecutive subjects treated for heart failure (HF) in a 455-bed southern hospital.
RESULTS: Patients treated for HF have variable care needs throughout the course of treatment. Univariate analysis of variance and post hoc analysis found that gender, age, type of unit, and length of stay (LOS) had a significant impact on acuity, P < .01, with a very small effect of less than 1%, indicating that acuity should be measured instead of assumed. Patients in medical-surgical and step-down units had highly variable acuity, ranging from ready to discharge to acuity levels consistent with critical care. Across the LOS, the mean acuity stabilized at 12 hours after admission, decreased until 88 hours, then increased steadily through discharge.
CONCLUSIONS: Understanding the variability in acuity within an individual patient, or a specific patient population, will contribute to decision support levels of patient care, staffing, nurse-patient assignments, and the cost of care. Frequent, sequential, and real-time measures of acuity may be valuable for tracking patient progress or measuring response to nursing interventions.

Entities:  

Mesh:

Year:  2017        PMID: 28858955     DOI: 10.1097/NNA.0000000000000518

Source DB:  PubMed          Journal:  J Nurs Adm        ISSN: 0002-0443            Impact factor:   1.737


  5 in total

1.  Nurses' Stress Associated with Nursing Activities and Electronic Health Records: Data Triangulation from Continuous Stress Monitoring, Perceived Workload, and a Time Motion Study.

Authors:  Po-Yin Yen; Nicole Pearl; Cierra Jethro; Emily Cooney; Brittany McNeil; Ling Chen; Marcelo Lopetegui; Thomas M Maddox; Marilyn Schallom
Journal:  AMIA Annu Symp Proc       Date:  2020-03-04

2.  Coincidence Analysis: A Novel Approach to Modeling Nurses' Workplace Experience.

Authors:  Dana M Womack; Edward J Miech; Nicholas J Fox; Linus C Silvey; Anna M Somerville; Deborah H Eldredge; Linsey M Steege
Journal:  Appl Clin Inform       Date:  2022-08-31       Impact factor: 2.762

3.  Evaluation of Electronic Health Record-Generated Work Intensity Scores and Nurse Perceptions of Workload Appropriateness.

Authors:  Dana Womack; Cheri Warren; Mariah Hayes; Sydnee Stoyles; Deborah Eldredge
Journal:  Comput Inform Nurs       Date:  2021-06       Impact factor: 2.146

4.  Acuity, nurse staffing and workforce, missed care and patient outcomes: A cluster-unit-level descriptive comparison.

Authors:  Maria-Eulàlia Juvé-Udina; Maribel González-Samartino; Maria Magdalena López-Jiménez; Maria Planas-Canals; Hugo Rodríguez-Fernández; Irene Joana Batuecas Duelt; Marta Tapia-Pérez; Mònica Pons Prats; Emilio Jiménez-Martínez; Miquel Àngel Barberà Llorca; Susana Asensio-Flores; Carme Berbis-Morelló; Esperanza Zuriguel-Pérez; Pilar Delgado-Hito; Óscar Rey Luque; Adelaida Zabalegui; Núria Fabrellas; Jordi Adamuz
Journal:  J Nurs Manag       Date:  2020-06-19       Impact factor: 3.325

5.  Predicting patient acuity according to their main problem.

Authors:  Maria-Eulàlia Juvé-Udina; Jordi Adamuz; Maria-Magdalena López-Jimenez; Marta Tapia-Pérez; Núria Fabrellas; Cristina Matud-Calvo; Maribel González-Samartino
Journal:  J Nurs Manag       Date:  2019-10-30       Impact factor: 3.325

  5 in total

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