A framework for the economic analysis of data collection methods for vital statistics

Jimenez-Soto, Eliana, Hodge, Andrew, Nguyen, Kim-Huong, Dettrick, Zoe and Lopez, Alan D. (2014) A framework for the economic analysis of data collection methods for vital statistics. PLoS One, 9 8: e106234.1-e106234.12. doi:10.1371/journal.pone.0106234

Author Jimenez-Soto, Eliana
Hodge, Andrew
Nguyen, Kim-Huong
Dettrick, Zoe
Lopez, Alan D.
Title A framework for the economic analysis of data collection methods for vital statistics
Journal name PLoS One   Check publisher's open access policy
ISSN 1932-6203
Publication date 2014-08-29
Sub-type Article (original research)
DOI 10.1371/journal.pone.0106234
Open Access Status DOI
Volume 9
Issue 8
Start page e106234.1
End page e106234.12
Total pages 12
Place of publication San Francisco, CA, United States
Publisher Public Library of Science
Collection year 2015
Language eng
Formatted 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.

Methodology: 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.

Findings: 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.

Conclusion: 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.
Q-Index Code C1
Q-Index Status Confirmed Code
Institutional Status UQ

Document type: Journal Article
Sub-type: Article (original research)
Collections: Official 2015 Collection
School of Public Health Publications
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Citation counts: TR Web of Science Citation Count  Cited 2 times in Thomson Reuters Web of Science Article | Citations
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Created: Mon, 01 Sep 2014, 09:27:42 EST by Dr Andrew Hodge on behalf of School of Public Health