Paper
Thursday, July 12, 2007
This presentation is part of : EBN Implementation
Developing, Exploring and Refining a Modified Whole Systems Based Model of Evidence-Informed Nursing
Robert McSherry, RGN, Dip, N, (Lon), BSc, (Hon's), MSc, PGCE, RT, School of Health and Social Care, University of Teesside, Middlesbrough, England
Learning Objective #1: describe a new Evidence-Informed Nursing (EIN) model and how it is designed to enable registered nurses to support their decisions and/or action with appropriate evidence.
Learning Objective #2: appreciate the value of systems theory and methodologies in highlighting the key elements and associated systems and processes that constitute getting evidence into practice.

 

In spite of a plethora of evidence-based nursing literature and numbers of models /frameworks designed to facilitate its cause registered nurses continue to struggle to use evidence to support their practice.

Aim

The research aimed to develop a new and alternative Evidence-Informed Nursing (EIN) model designed to facilitate evidence into practice.

Design

A Modified Whole Systems Theory (MWST) design using Soft System Methodology (SSM) combining quantitative and qualitative methods was the framework of choice for this research study.

Population, Sample

A probability sampling technique was used for the qualitative aspect of the study where all 239 registered nurses had an equal chance of participation by completing and returned the Research Awareness Questionnaire (RAQ) n = 149 (62%). A purposive sample of n=31 (30%) of all grades of nursing staff participated in the six qualitative Focus Group Interviews (FGI). 

Methods

Date from the RAQ was entered into a Statistical Package for Social Science (SPSS) database where both descriptive and inferential statistics were used for data analysis.  A thematic analysis was undertaken of the FGI transcripts. Ethical approval was granted to undertake the study.

Findings

The re-presented EIN model unlike the original theoretical EIN model clarified that evidence-based nursing is undoubtedly a complex system comprising of several important attributes contained within six elements. These are: professional accountability, informed decision-making, research awareness, application of knowledge, evaluation and conditions affecting research utilisation. The results confirmed that the EIN model is systems based by possessing a clearly defined input; to encourage nurses to use evidence in practice, throughput; facilitation about the processes associated with the six elements and an output; improved standards of professional practice.

Conclusions

The EIN model offers a new and alternative framework for nursing colleagues to use and apply when faced with a real problem of getting evidence into practice.