Introducing the Evidence Synthesis Taxonomy Initiative

The Evidence Synthesis Taxonomy Initiative (ESTI) is a global collaborative initiativeled by Associate Professor Zachary Munn and supported by an executive and Advisory Group which has over 100 members all over the world, consisting of researchers, guideline developers, methodologists, health professionals, policy-makers, patient partners and information scientists with an interest in methodology and evidence synthesis across various fields/disciplines.

The field of evidence synthesis is growing and has undergone profound transformationsince its inception. There is a vital need for  for policy makers, practitioners, and the general public to have access to trustworthy, summarised evidence to guide decision-making and inform policy and practice. There currently exists many approaches and methodologies to synthesise evidence which often leads to confusion over what approach is the right one. It is imperative that researchers use the appropriate evidence synthesis approach as it can impact on the care patients receive from their health care provider.

The ESTI project aims to establish a free, online, interactive evidence synthesis taxonomy, which will help guide knowledge users across many scientific fields in determining the appropriate evidence synthesis to undertake. Typologies and taxonomies are types of classification systems that classify items or ideas into categories, based on theoretical or conceptual distinctions. Such a taxonomy will potentially add some much-needed clarification and structure to the evidence synthesis field, as well as ensure that evidence syntheses are conducted to a higher standard by reducing the need for evidence synthesisers to scope and navigate through a plethora of conflicting resources.

This initiative is currently at the stage of conducting a scoping review. Scoping reviews aim to map the body of literature on a specific topic, providing a descriptive overview of the current literature. The objective of the current scoping review is to identify evidence synthesis types and previously proposed classification systems, typologies or taxonomies that have guided evidence synthesis. This scoping review will identify what, if any, taxonomies, typologies, compendia, groupings, or classification systems have been proposed for evidence synthesis methods. It is currently at the stage of data extraction. Over 300 articles have been included from full-text screening.

We hope that this initiative proves to be a valuable asset to evidence synthesisers worldwide.