title: Model-driven meta-analyses for informing health care: a diabetes meta-analysis as an exemplar.
abstract: A relatively novel type of meta-analysis, a model-driven meta-analysis, involves the quantitative synthesis of descriptive, correlational data and is useful for identifying key predictors of health outcomes and informing clinical guidelines. Few such meta-analyses have been conducted and thus, large bodies of research remain unsynthesized and uninterpreted for application in health care. We describe the unique challenges of conducting a model-driven meta-analysis, focusing primarily on issues related to locating a sample of published and unpublished primary studies, extracting and verifying descriptive and correlational data, and conducting analyses. A current meta-analysis of the research on predictors of key health outcomes in diabetes is used to illustrate our main points.
authors.affiliation: The University of Texas at Austin, TX, USA sabrown@mail.utexas.edu.
authors.forename: Sharon A
authors.initials: SA
authors.lastname: Brown
authors.affiliation: Florida State University, Tallahassee, FL, USA.
authors.forename: Betsy Jane
authors.initials: BJ
authors.lastname: Becker
authors.affiliation: The University of Texas at Austin, TX, USA.
authors.forename: Alexandra A
authors.initials: AA
authors.lastname: García
authors.affiliation: The University of Texas at Austin, TX, USA.
authors.forename: Adama
authors.initials: A
authors.lastname: Brown
authors.affiliation: Texas A&M University, College Station, TX, USA.
authors.forename: Gilbert
authors.initials: G
authors.lastname: Ramírez
mesh_terms: D003924:Diabetes Mellitus, Type 2 / Q000628:therapy*; D006801:Humans; D008962:Models, Theoretical; D017063:Outcome Assessment, Health Care / Q000379:methods*
keywords: meta-analysis; model testing; type 2 diabetes