title: A framework for the economic analysis of data collection methods for vital statistics.
abstract: BACKGROUND
  Over recent years there has been a strong movement towards the improvement of vital statistics and other types of health data that inform evidence-based policies. Collecting such data is not cost free. To date there is no systematic framework to guide investment decisions on methods of data collection for vital statistics or health information in general. We developed a framework to systematically assess the comparative costs and outcomes/benefits of the various data methods for collecting vital statistics.
  
  
  METHODS
  The proposed framework is four-pronged and utilises two major economic approaches to systematically assess the available data collection methods: cost-effectiveness analysis and efficiency analysis. We built a stylised example of a hypothetical low-income country to perform a simulation exercise in order to illustrate an application of the framework.
  
  
  RESULTS
  Using simulated data, the results from the stylised example show that the rankings of the data collection methods are not affected by the use of either cost-effectiveness or efficiency analysis. However, the rankings are affected by how quantities are measured.
  
  
  CONCLUSIONS
  There have been several calls for global improvements in collecting useable data, including vital statistics, from health information systems to inform public health policies. Ours is the first study that proposes a systematic framework to assist countries undertake an economic evaluation of DCMs. Despite numerous challenges, we demonstrate that a systematic assessment of outputs and costs of DCMs is not only necessary, but also feasible. The proposed framework is general enough to be easily extended to other areas of health information.
authors.affiliation: School of Population Health, The University of Queensland, Australia.
authors.forename: Eliana
authors.initials: E
authors.lastname: Jimenez-Soto
authors.affiliation: School of Population Health, The University of Queensland, Australia.
authors.forename: Andrew
authors.initials: A
authors.lastname: Hodge
authors.affiliation: Centre for Applied Health Economics, School of Medicine, Griffith University, Australia.
authors.forename: Kim-Huong
authors.initials: KH
authors.lastname: Nguyen
authors.affiliation: School of Population Health, The University of Queensland, Australia.
authors.forename: Zoe
authors.initials: Z
authors.lastname: Dettrick
authors.affiliation: School of Population and Global Health, The University of Melbourne, Australia.
authors.forename: Alan D
authors.initials: AD
authors.lastname: Lopez
mesh_terms: D003365:Costs and Cost Analysis; D066264:Datasets as Topic / Q000191:economics* / Q000592:standards; D006801:Humans; D014798:Vital Statistics