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Collecting verbal autopsies: improving and streamlining data collection processes using electronic tablets

Overview of attention for article published in Population Health Metrics, February 2018
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (88th percentile)
  • High Attention Score compared to outputs of the same age and source (80th percentile)

Mentioned by

blogs
1 blog
policy
1 policy source
twitter
8 X users

Citations

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16 Dimensions

Readers on

mendeley
49 Mendeley
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Title
Collecting verbal autopsies: improving and streamlining data collection processes using electronic tablets
Published in
Population Health Metrics, February 2018
DOI 10.1186/s12963-018-0161-9
Pubmed ID
Authors

Abraham D. Flaxman, Andrea Stewart, Jonathan C. Joseph, Nurul Alam, Sayed Saidul Alam, Hafizur Chowdhury, Meghan D. Mooney, Rasika Rampatige, Hazel Remolador, Diozele Sanvictores, Peter T. Serina, Peter Kim Streatfield, Veronica Tallo, Christopher J. L. Murray, Bernardo Hernandez, Alan D. Lopez, Ian Douglas Riley

Abstract

There is increasing interest in using verbal autopsy to produce nationally representative population-level estimates of causes of death. However, the burden of processing a large quantity of surveys collected with paper and pencil has been a barrier to scaling up verbal autopsy surveillance. Direct electronic data capture has been used in other large-scale surveys and can be used in verbal autopsy as well, to reduce time and cost of going from collected data to actionable information. We collected verbal autopsy interviews using paper and pencil and using electronic tablets at two sites, and measured the cost and time required to process the surveys for analysis. From these cost and time data, we extrapolated costs associated with conducting large-scale surveillance with verbal autopsy. We found that the median time between data collection and data entry for surveys collected on paper and pencil was approximately 3 months. For surveys collected on electronic tablets, this was less than 2 days. For small-scale surveys, we found that the upfront costs of purchasing electronic tablets was the primary cost and resulted in a higher total cost. For large-scale surveys, the costs associated with data entry exceeded the cost of the tablets, so electronic data capture provides both a quicker and cheaper method of data collection. As countries increase verbal autopsy surveillance, it is important to consider the best way to design sustainable systems for data collection. Electronic data capture has the potential to greatly reduce the time and costs associated with data collection. For long-term, large-scale surveillance required by national vital statistical systems, electronic data capture reduces costs and allows data to be available sooner.

X Demographics

X Demographics

The data shown below were collected from the profiles of 8 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 49 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 49 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 10 20%
Student > Master 7 14%
Student > Postgraduate 5 10%
Student > Ph. D. Student 4 8%
Student > Bachelor 2 4%
Other 3 6%
Unknown 18 37%
Readers by discipline Count As %
Medicine and Dentistry 11 22%
Nursing and Health Professions 6 12%
Social Sciences 3 6%
Biochemistry, Genetics and Molecular Biology 2 4%
Unspecified 1 2%
Other 7 14%
Unknown 19 39%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 15. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 08 September 2019.
All research outputs
#2,296,242
of 24,348,815 outputs
Outputs from Population Health Metrics
#56
of 401 outputs
Outputs of similar age
#53,512
of 448,179 outputs
Outputs of similar age from Population Health Metrics
#2
of 5 outputs
Altmetric has tracked 24,348,815 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 90th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 401 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 14.2. This one has done well, scoring higher than 86% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 448,179 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 88% of its contemporaries.
We're also able to compare this research output to 5 others from the same source and published within six weeks on either side of this one. This one has scored higher than 3 of them.