title: Series: Clinical Epidemiology in South Africa. Paper 3: Logic models help make sense of complexity in systematic reviews and health technology assessments.
abstract: OBJECTIVE
  To describe the development and application of logic model templates for systematic reviews and health technology assessments (HTAs) of complex interventions.
  
  
  METHODS
  This study demonstrates the development of a method to conceptualize complexity and make underlying assumptions transparent. Examples from systematic reviews with specific relevance to Sub-Saharan Africa (SSA) and other low- and middle-income countries (LMICs) illustrate its usefulness.
  
  
  RESULTS
  Two distinct templates are presented: the system-based logic model, describing the system in which the interaction between participants, intervention, and context takes place; and the process-orientated logic model, which displays the processes and causal pathways that lead from the intervention to multiple outcomes.
  
  
  CONCLUSIONS
  Logic models can help authors of systematic reviews and HTAs to explicitly address and make sense of complexity, adding value by achieving a better understanding of the interactions between the intervention, its implementation, and its multiple outcomes among a given population and context. They thus have the potential to help build systematic review capacity-in SSA and other LMICs-at an individual level, by equipping authors with a tool that facilitates the review process; and at a system-level, by improving communication between producers and potential users of research evidence.
authors: Institute for Medical Informatics, Biometry and Epidemiology, Ludwig-Maximilians-University, Marchioninistrasse 15, 81377 Munich, Germany; Centre for Evidence-Based Health Care, Faculty of Medicine and Health Sciences, Stellenbosch University, Francie Van Zijl Drive, 7500 Parow, South Africa. Electronic address: arohwer@sun.ac.za.
authors: Anke
authors: A
authors: Rohwer
authors: Institute for Medical Informatics, Biometry and Epidemiology, Ludwig-Maximilians-University, Marchioninistrasse 15, 81377 Munich, Germany.
authors: Lisa
authors: L
authors: Pfadenhauer
authors: Institute for Medical Informatics, Biometry and Epidemiology, Ludwig-Maximilians-University, Marchioninistrasse 15, 81377 Munich, Germany.
authors: Jacob
authors: J
authors: Burns
authors: School of Health and Related Research (ScHARR), University of Sheffield, 30 Regent Street, Sheffield S1 4DA, UK.
authors: Louise
authors: L
authors: Brereton
authors: Department of Health Services Research, Institute of Public Health and Nursing Research, University of Bremen, Grazer Street 4, D-28359 Bremen, Germany.
authors: Ansgar
authors: A
authors: Gerhardus
authors: School of Health and Related Research (ScHARR), University of Sheffield, 30 Regent Street, Sheffield S1 4DA, UK.
authors: Andrew
authors: A
authors: Booth
authors: Ecorys Nederland B.V., Watermanweg 44, 3067 GG Rotterdam, The Netherlands.
authors: Wija
authors: W
authors: Oortwijn
authors: Institute for Medical Informatics, Biometry and Epidemiology, Ludwig-Maximilians-University, Marchioninistrasse 15, 81377 Munich, Germany.
authors: Eva
authors: E
authors: Rehfuess
mesh_terms: D019317:Evidence-Based Medicine / Q000379:methods / Q000592:standards; D006801:Humans; D008962:Models, Theoretical; D012196:Review Literature as Topic; D013019:South Africa; D013673:Technology Assessment, Biomedical
keywords: Africa; Analytical framework; Complexity; Conceptual framework; Evidence synthesis; Systems-based thinking