Literature DB >> 19379112

Evaluation of clinical practice improvement programs for nurses for the management of alcohol withdrawal in hospitals.

Michelle Daly1, Stephen Kermode, David Reilly.   

Abstract

The most common alcohol-related chronic condition for hospitalisation is alcohol dependence which can lead to an alcohol withdrawal syndrome (AWS). The aim of this paper is to report on a quality improvement program in an Australian rural area health service for the screening and management of alcohol withdrawal and the effect of two types of nursing education and training approaches: a self-directed competency training package and a more traditional in-service program. The measure of improvement was compliance to nine clinical standards or core competencies for the assessment and treatment of the AWS derived from the Clinical Institute Withdrawal Assessment for Alcohol-Revised (CIWA-Ar) scale and the NSW drug and alcohol withdrawal clinical practice guidelines. An audit of medical records using a standardised protocol for the nine standards was conducted at baseline (n=100) and follow-up (n=340) across eleven hospitals in the area. Results indicated that in three hospitals, where 70 nurses completed the self-directed competency training, there was a higher total compliance score across the nine standards compared to eight hospitals where 238 nurses received the in-service program. The self-directed competency program was also rated highly by nurses who participated in the program. The benefits of self-directed competency training are discussed as well as future recommendations for improving nurse education strategies for managing alcohol withdrawal.

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Year:  2009        PMID: 19379112     DOI: 10.5172/conu.673.31.2.98

Source DB:  PubMed          Journal:  Contemp Nurse        ISSN: 1037-6178            Impact factor:   1.787


  1 in total

Review 1.  The effectiveness of knowledge translation interventions for promoting evidence-informed decision-making among nurses in tertiary care: a systematic review and meta-analysis.

Authors:  Jennifer Yost; Rebecca Ganann; David Thompson; Fazila Aloweni; Kristine Newman; Afeez Hazzan; Ann McKibbon; Maureen Dobbins; Donna Ciliska
Journal:  Implement Sci       Date:  2015-07-14       Impact factor: 7.327

  1 in total

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