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\textbf{Discussion}    Systematic reviews operate based on protocols which aim to aid researchers to minimize bias, perform literature searches, and evaluate data in a manner which limits spurious results. One important aspect of these protocols is analysis of heterogeneity in its origin and effects on meta-analysis. Although some studies assess heterogeneity, it is still underutilized as only half of the available studies utilized one or more of the common heterogeneity tests evaluated in this study (X2, I2, Tau2, and Cochranes Q) with 19\% 20\%  of available studies mentioning heterogeneity without further assessment (Figure 2). With inter-study variance always present on some level, heterogeneity evaluation in systematic reviews becomes necessary. The paltry use of meta-regression and/or subgroup analysis (8\% (9\%  and 22\% 21\%  respectively) limits studies from assessing heterogeneities impact on meta-analysis. Another interesting note is the reporting of whether there was too much heterogeneity to perform a meta-analysis, with 37\% 35\%  reporting an unknown level of heterogeneity. Finally the use of random-effect meta-analysis model was underutilized with 23\% 25\%  using this model and 18\% 21\%  using both random/fixed effects models. The random-effects model adds in a factor for heterogeneity as an attempt to stem misleading results which might come from the sole use of a fixed-effect meta-analysis. Lastly, the Institute of Medicine’s Standards for Systematic Reviews states that, “although the committee does not believe that any single statistical technique should be a methodological standard, it is essential that the SR [systematic review] team clearly explain and justify the reasons why it chose the technique actually used.”(Morton 2011). From this study 12\% review only 15\%  of available studies used the random-effects model with justification for the use of that meta-analysis model.   Quantitative assessments of heterogeneity like the evidence-based mapping method from Althuis et al. are powerful tools which help present heterogeneity before a meta-analysis is performed. The evidence-based mapping method can be used to justify inclusion of statistical tests which illuminate the origins and effects heterogeneity has on meta-analysis results. The real strength of this method is how effortlessly this study can be applied to a systematic review. This study applied this method to a systematic review studying palliative sedative use in end-of-life cancer patients. The resulting figures from this trial compared patient population statistics as well as the study design features. Information from these figures can be used by researchers to direct their efforts in understanding the effects of heterogeneity on their results and deciding whether meta-analysis can be conducted. 
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