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Physician Assistant Systematic Review

Data Extraction

As you read through you articles for te critical appraisal portion of your review, pay attention to the type of data in each study. You may also want to look at other systematic reviews published on similar topics to see what type of data they compared. Always error on the side of collecting too much data rather than not enough. 

You will need to create your own form based on your own data needs, but you can follow the general format found in these templates:

Cochrane Data Extraction Template

Section 1.3.3.2 in York University's Undertaking the Review

Meta-Analysis

M-A comprises statistical methods to contrast and combines results from different studies in the hope of identifying patterns among
study results, sources of disagreement among those results, or other interesting relationships that may come to light in the context of multiple studies.
  • M-A can be thought of as ‘conducting research about previous research’.
    • In its simplest form, meta-analysis is done by identifying a common statistical measure that is shared between studies
      • such as effect size or p-value, and calculating a weighted average of that common measure.
      • This weighting is usually related to the sample sizes of the individual studies,  although it can also include other factors, such as study quality.

You can run meta-analyses through software packages like the Metafor Package. The package consists of a collection of functions that allow the user to calculate various effect size or outcome measures, fit fixed-, random-, and mixed-effects models to such data, carry out moderator and meta-regression analysis and create various types of meta-analytical plots.

Forest Plot

  • A forest plot is a graphical representation of a Meta-analysis. Left table listing references (author and date) of the studies included in the meta-analysis.
  •  The table lists the mean scores and standard deviations of these scores from each of the included  studies, and it lists the number of participants in each study (under Total’).

 

 

Generate a Forest Plot

Once you have all of the data points needed for a Forest plot, wight, Odds Ratio, Lower Confidence, Upper Confidence, and Patient Population. You can use a Forest Plot generator from Evidence Partners to create the actual plot.