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Potential uses of Bayesian networks as tools for synthesis of systematic reviews of complex interventions
Author(s) -
Stewart G. B.,
Mengersen K.,
Meader N.
Publication year - 2014
Publication title -
research synthesis methods
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.376
H-Index - 35
eISSN - 1759-2887
pISSN - 1759-2879
DOI - 10.1002/jrsm.1087
Subject(s) - bayesian network , expert elicitation , computer science , psychological intervention , management science , framing (construction) , systematic review , context (archaeology) , intervention (counseling) , data science , knowledge management , risk analysis (engineering) , artificial intelligence , psychology , medline , engineering , medicine , biology , paleontology , statistics , mathematics , structural engineering , psychiatry , law , political science
Bayesian networks (BNs) are tools for representing expert knowledge or evidence. They are especially useful for synthesising evidence or belief concerning a complex intervention, assessing the sensitivity of outcomes to different situations or contextual frameworks and framing decision problems that involve alternative types of intervention. Bayesian networks are useful extensions to logic maps when initiating a review or to facilitate synthesis and bridge the gap between evidence acquisition and decision‐making. Formal elicitation techniques allow development of BNs on the basis of expert opinion. Such applications are useful alternatives to ‘empty’ reviews, which identify knowledge gaps but fail to support decision‐making. Where review evidence exists, it can inform the development of a BN. We illustrate the construction of a BN using a motivating example that demonstrates how BNs can ensure coherence, transparently structure the problem addressed by a complex intervention and assess sensitivity to context, all of which are critical components of robust reviews of complex interventions. We suggest that BNs should be utilised to routinely synthesise reviews of complex interventions or empty reviews where decisions must be made despite poor evidence. Copyright © 2013 John Wiley & Sons, Ltd.