Literature DB >> 29766622

Evaluating the implementation of confusion assessment method-intensive care unit using a quality improvement approach.

C Stewart1, S Bench2.   

Abstract

Quality improvement (QI) is a way through which health care delivery can be made safer and more effective. Various models of quality improvement methods exist in health care today. These models can help guide and manage the process of introducing changes into clinical practice. The aim of this project was to implement the use of a delirium assessment tool into three adult critical care units within the same hospital using a QI approach. The objective was to improve the identification and management of delirium. Using the Model for Improvement framework, a multidisciplinary working group was established. A delirium assessment tool was introduced via a series of educational initiatives. New local guidelines regarding the use of delirium assessment and management for the multidisciplinary team were also produced. Audit data were collected at 6 weeks and 5 months post-implementation to evaluate compliance with the use of the tool across three critical care units within a single hospital in London. At 6 weeks, in 134 assessment points out of a possible 202, the tool was deemed to be used appropriately, meaning that 60% of patients received timely assessment; 18% of patients were identified as delirious in audit one. Five months later, only 95 assessment points out of a possible 199 were being appropriately assessed (47%); however, a greater number (32%) were identified as delirious. This project emphasizes the complexity of changing practice in a large busy critical care centre. Despite an initial increase in delirium assessment, this was not sustained over time. The use of a QI model highlights the continuous process of embedding changes into clinical practice and the need to use a QI method that can address the challenging nature of modern health care. QI models guide changes in practice. Consideration should be given to the type of QI model used.
© 2018 British Association of Critical Care Nurses.

Entities:  

Keywords:  Clinical audit; Critical care nursing; Quality improvement

Mesh:

Year:  2018        PMID: 29766622     DOI: 10.1111/nicc.12354

Source DB:  PubMed          Journal:  Nurs Crit Care        ISSN: 1362-1017            Impact factor:   2.325


  2 in total

1.  A machine learning approach to identifying delirium from electronic health records.

Authors:  Jae Hyun Kim; May Hua; Robert A Whittington; Junghwan Lee; Cong Liu; Casey N Ta; Edward R Marcantonio; Terry E Goldberg; Chunhua Weng
Journal:  JAMIA Open       Date:  2022-05-24

2.  Understanding how and why audits work in improving the quality of hospital care: A systematic realist review.

Authors:  Lisanne Hut-Mossel; Kees Ahaus; Gera Welker; Rijk Gans
Journal:  PLoS One       Date:  2021-03-31       Impact factor: 3.240

  2 in total

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