University of Virginia

  School of Nursing

 

 

   COURSE OVERVIEW

 

 

COURSE NUMBER:                      GNUR 8660

 

COURSE NAME:                             Evidence Based Practice

 

CREDITS:                                         3 credit hours

 

COURSE PROFESSOR:               Mikel Gray, PhD, FNP, PNP, CUNP, CCCN, FAANP, FAAN

                                                            Department of Urology

                                                            Administrative Support: Gary Mawyer  

                                                            924-9554

                                                            Email: mg5k@virginia.edu

                                   

 

PRE AND CO-REQUISITES:       

 

Admission to Doctor of Nursing Practice (DNP) program with relevant clinical experience, updated knowledge of statistics is required for admission.

 

COURSE DESCRIPTION:

The course introduces DNP students to principles and processes of evidence-based practice. We will review processes for identifying current best evidence, including formulation of a clinical question using PICO taxonomy, systematic review of the literature, critical evaluation of individual studies, structured data extraction, and synthesis of pooled data to determine the level of evidence associated with specific clinical interventions. Various methods for analyzing and evaluating the level of evidence will be discussed including meta-analysis, ordinal scales for ranking the strength of evidence, and descriptive methods.  Resources for evidence based practice, including the Cochrane Library, Joanna Briggs Institute for Evidence Based Nursing, and the Essential Evidence Plus Collection will be presented. Discussion will focus on strengths and limitations of existing clinical evidence, and its application to clinical practice. Students will synthesize their advanced practice skills and prior clinical knowledge to the generation of evidence-based clinical practice guidelines, evaluation of clinical practice guidelines and best practice documents, and their application to clinical decision making in daily practice.

 

 

COURSE OBJECTIVES:

 

Upon the completion of the course, the student will be able to:

 

1. Define evidence-based practice and differentiate it from tradition-based practice or clinical decision making based on research-based rationales.
2. Describe methods for reviewing the literature in order to identify current best evidence.
3. Identify online and library-based resources for evidence based documents including systematic reviews, clinical practice guidelines and best-practice documents.
4.  Apply knowledge of research methods and clinical practice to the evaluation of levels of evidence.
5. Discuss methods for extracting data necessary for the generation of evidence-based practice recommendations.
6. Apply knowledge of statistical analysis to the evaluation of evidence from individual studies, the process of data extraction, and pooled data from meta-analyses.
7. Synthesize data from multiple studies into recommendations for clinical practice based on analysis of the strength of supporting data.

 

 

CONTENT OUTLINE

 

I. Introduction to Evidence Based Practice

 

1. Evidence: a concept analysis and philosophical underpinnings
2. Historical perspective
   1. McMaster’s University curriculum
   2. Contributions of Archibald Cochrane
3. Definitions
   1. Evidence Based Medicine
   2. Evidence Based Nursing
   3. Evidence Based Practice
4. Differentiation of EBP from tradition-based practice, research based practice, best practices, research utilization, etc
5. How much of nursing/ medical practice is evidence based?

 

Overview of EBP process

1. Searching for current best evidence
   1. Electronic databases
   2. Ancestry search
   3. Internet search engines
   4. Personal communication
2. Extracting data from individual studies
   1. Structured data extraction
   2. Peer review
3. Ranking the evidence using
   1. Qualitative
   2. Semi-quantitative
   3. Quantitative methods
4. Generating clinical recommendations via
   1. Systematic review
   2. Meta-analysis
   3. Clinical practice guideline
   4. Best practice document
5. Selecting a topic and designing a clinical question using PICO taxonomy
   1. Describing the population
   2. Identifying the intervention or assessment
   3. Identifying the primary clinical outcome indicating efficacy
   4. Managing clinically relevant secondary outcomes
6. Finding the Evidence: Search Strategies
   1. Electronic databases
   2. Evidence based resources
   3. Online search engines
   4. Ancestry searches
   5. Grey literature sources
   6. Personal communications with researchers, clinicians, colleagues
7. Extracting data
   1. Evaluation of individual studies
   2. Structured data extraction
   3. Grading systems 

 

Extracting Evidence and Evaluating its Quality

A. Hierarchy of Evidence: Evaluating individual research studies   

1)   Randomized clinical trial

2)   Quasi-experimental study designs

3)   Non-experimental designs (including qualitative research and case studies)

4)   Use of appraisal matrices

B. Extracting, Organizing and Synthesizing the Evidence

1)   Systematic Review

2)   Descriptive analysis

3)   Semiquantitative analyses (ordinal scales for ranking the strength of evidence)

C. Meta-analyses

1. Pooling data
2. Determination or heterogeneity or homogeneity of data
3. Options for statistical analyses
4. Interpreting meta-analytic results
   1. Confidence intervals
   2. Number needed to treat
   3. Graphic presentations of data such as forest plots, etc.

 

6. Measurement of magnitude of effect
   1. Odds Ratio
   2. Relative risk ratios
   3. Hazard Ratios
7. Interpreting and presenting results
   1. Formulating clinical recommendations
   2. Identifying gaps in evidence
   3. Formats for presenting results: systematic review article, clinical practice guideline, best practice panel
8. Alternative forms of Evidence
   1. Extracting and synthesizing evidence from qualitative studies
   2. Comparative effectiveness research
   3. Extracting data from large electronic databases
   4. Real world trials
9. Expert Opinion/ Consensus Based Practice/ Best Practice
   1. Best Practice: definition and origins
   2. Expert opinion and Consensus Based Practice
   3.  Hybrid models

 

 

II. Evaluation of Individual Research Studies

 

 

1. Purpose of Study
   1. Research questions
   2. Study aims
2. Methods
   1. Subjects and setting
      1. Target population
      2. Sampling technique
      3. IRB/ Human Subjects Committee statement
   2. Instruments (validated?)
   3. Study procedures (reprodicuble?)
   4. Outcome (dependent) measures/ variables
   5. Predictor (independent) variables
3. Data analysis (Descriptive, Univariate/ Bivariate and Multivariate Statistics)
   1. Descriptive Statistics
      1. Defining measures of central tendency (mean, median, mode)
      2. Defining measures of variability (range, standard deviation, interquartile range)
   2. Univariate parametric statistical testing: the t-test
   3. Univariate non-parametric statistical analyses
      1. χ² analysis
      2. Fisher’s Exact test
      3. Mann-Whitney U
4. Multivariate statistical tests
   1. Analyses of Variance         
   2. Kruskall-Wallis test
   3. Wilcoxon sign rank
   4. Analysis of Covariance
5. Regression Analyses
   1. Parametric correlation (Spearman’s r)
   2. Spearman’s rank correlation (Spearman’s rho)
   3. Linear regression and multiple linear regression
   4. Logistic regression
6. Results
   1. Follow study purpose/ research questions/ aims
   2. Statistical significance/ clinical relevance
7. Discussion
   1. Compare findings to work of others
   2. Conclusions justified by results of this study
   3. Limitations

 

III. Application to Clinical Practice/ Influencing Facility-Wide/ Regional/ National/Global Practice

1. Formulating clinical recommendations
2. Identifying gaps in evidence
3. Formats for presenting results: systematic review article, clinical practice guideline, best practice panel
4. Use of clinical practice guidelines, practice protocols and algorithms
5. Does education alone change practice?

1. Theoretical paradigms for diffusing research findings into meaningful clinical practice changes such as Roger’s diffusion theory
2. Lag between research finding and adaptation into clinical practice

 

Syllabus

 

 

Topics to be covered
Class Dates (all dates 2015): Topics will be covered in order presented in lecture/ class discussion format   August 28 0800-1600   Strongly Suggested Readings: Gray M. Evidence-based practice. In: Hamric AB, Hanson CM, Tracy MF, O’Grady ET. Advanced Practice Nursing. Philadelphia PA: St. Louis: Elsevier, 2013, pp. 241-62.    * I strongly suggest reading my chapter in Hamric by first class. I will provide 2 articles for review for day 2 of our very intense first 2 days. You will find them in the resources section of the GNUR 8660 Collab site, under the folder named RCT for individual critique.  They will be labelled articles 1 and 2 followed by author and journal.	Introduction and Philosophical Perspective: What is evidence and how do we interpret it in clinical practice?   Introduction to Evidence Based Practice/ Historical Perspective/ Philosophical Underpinnings   Differentiation of EBP from tradition-based practice, research based practice, best practices, research utilization, etc   Overview of EBP process Searching for current best evidence Extracting data from individual studies Evidence Ranking using: Qualitative Semi-quantitative Quantitative methods   Generating clinical recommendations via Systematic review Meta-analysis Clinical practice guideline Best practice document Selecting a topic and designing a clinical question Defining the scope of the problem Identifying the intervention or assessment Describing the population Identifying the primary clinical outcome indicating efficacy Identifying clinical relevant secondary outcomes Finding the Evidence: Search Strategies Electronic databases Evidence based resources Online search engines Ancestry searches Grey literature sources Personal communications Extracting Data Evaluation of individual studies Grading systems Organizing and Synthesizing the Evidence Systematic Review Descriptive analysis Semiquantitative analyses (ordinal scales for ranking the strength of evidence)
August 29,  0800-1300 Critiquing the individual research study: looking beyond the literature review and discussion   Recommended statistics desktop reference:   Norman GR, Streiner DL. PDQ Statistics, 3rd edition. Becker: Hamilton ON, 2003. Chapters 1-4, 10 [Confirmed as latest edition August 1, 2013]	Subjects and setting Target population Sampling technique IRB/ Human Subjects Committee statement Instruments (validated?) Study procedures (reprodicuble?) Outcome (dependent) measures/ variables Predictor (independent) variables Data analysis (Descriptive, Univariate/ Bivariate and Multivariate Statistics) Descriptive Statistics Defining measures of central tendency (mean, median, mode) Defining measures of variability (range, standard deviation, interquartile range) Univariate parametric statistical testing: the t-test Univariate non-parametric statistical analyses χ2 analysis Fisher’s Exact test Mann-Whitney U Multivariate statistical tests Analyses of Variance  Kruskall-Wallis test Wilcoxon sign rank Analysis of Covariance Regression Analyses Parametric correlation (Spearman’s r) Spearman’s rank correlation (Spearman’s rho) Linear regression and multiple linear regression Logistic regression Results Follow study purpose/ research questions/ aims Statistical significance/ clinical relevance Discussion Compare findings to work of others Conclusions justified by results of this study Limitations
September 11, 1500-1730   Meta-analysis   Suggested Readings:   Eggar M, Smith GD. Meta-analysis: potential and promise. BMJ 1997; 315 (7119).   Eggar M, Smith DG, Phillips AN. Meta-analysis: principles and procedures.  BMJ 1997; 315 (7121).   Smith DG, Eggar M, Phillips AN. Meta-analysis: beyond the grand mean? BMJ 1997; 315 (7122).	Review of 2 Individual Research Studies (selected by Gray)   Analysis of Pooled Data (Meta-analysis) Pooling data Determining its heterogeneity Options for statistical analyses Interpreting meta-analytic results Confidence intervals Number needed to treat Graphic presentations of data such as forest plots, etc.   Measurement of magnitude of effect Odds Ratio Relative risk ratios
October 16, 1500-1730   Alternative means of generating evidence	Review 2 research articles (selected by Gray) Comparative effectiveness research Evaluation of large electronic databases and real world trials Evidence from qualitative research studies/ Metasynthesis Evidence from historical studies
November 13, 1500-1730	Data Extraction Exercise Due
December 11, 0800-1200	Impacting Clinical Practice Formulating clinical recommendations Identifying gaps in evidence Formats for presenting results: systematic review article, clinical practice guideline, best practice panel   Influencing Clinical Practice Lag between research finding and adaptation into clinical practice   Research findings Use of clinical practice guidelines, practice protocols and algorithms Does education alone change practice? Theoretical paradigms for diffusing research findings into meaningful clinical practice changes such as Roger’s diffusion theory

 

           

 

GRADING SCALE:

The grading scale for this course is:

A+	97-100
A A-	94-96 90-93
B+	87-89
B	84-86
B-	80-83

 

A minimum grade of "B-" is required in all courses for any graduate degree. If a student receives a "C" grade in any School of Nursing course, the course must be repeated.