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Moving from medical to health systems classifications of deaths: extending verbal autopsy to collect information on the circumstances of mortality

Overview of attention for article published in Global Health Research and Policy, June 2016
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  • Good Attention Score compared to outputs of the same age (72nd percentile)
  • Good Attention Score compared to outputs of the same age and source (71st percentile)

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Title
Moving from medical to health systems classifications of deaths: extending verbal autopsy to collect information on the circumstances of mortality
Published in
Global Health Research and Policy, June 2016
DOI 10.1186/s41256-016-0002-y
Pubmed ID
Authors

Lucia D’Ambruoso, Kathleen Kahn, Ryan G. Wagner, Rhian Twine, Barry Spies, Maria van der Merwe, F. Xavier Gómez-Olivé, Stephen Tollman, Peter Byass

Abstract

Verbal autopsy (VA) is a health surveillance technique used in low and middle-income countries to establish medical causes of death (CODs) for people who die outside hospitals and/or without registration. By virtue of the deaths it investigates, VA is also an opportunity to examine social exclusion from access to health systems. The aims were to develop a system to collect and interpret information on social and health systems determinants of deaths investigated in VA. A short set of questions on care pathways, circumstances and events at and around the time of death were developed and integrated into the WHO 2012 short form VA (SF-VA). Data were subsequently analysed from two census rounds in the Agincourt Health and Socio-Demographic Surveillance Site (HDSS), South Africa in 2012 and 2013 where the SF-VA had been applied. InterVA and descriptive analysis were used to calculate cause-specific mortality fractions (CSMFs), and to examine responses to the new indicators and whether and how they varied by medical CODs and age/sex sub-groups. One thousand two hundred forty-nine deaths were recorded in the Agincourt HDSS censuses in 2012-13 of which 1,196 (96 %) had complete VA data. Infectious and non-communicable conditions accounted for the majority of deaths (47 % and 39 % respectively) with smaller proportions attributed to external, neonatal and maternal causes (5 %, 2 % and 1 % respectively). 5 % of deaths were of indeterminable cause. The new indicators revealed multiple problems with access to care at the time of death: 39 % of deaths did not call for help, 36 % found care unaffordable overall, and 33 % did not go to a facility. These problems were reported consistently across age and sex sub-groups. Acute conditions and younger age groups had fewer problems with overall costs but more with not calling for help or going to a facility. An illustrative health systems interpretation suggests extending and promoting existing provisions for transport and financial access in this setting. Supplementing VA with questions on the circumstances of mortality provides complementary information to CSMFs relevant for health planning. Further contextualisation of the method and results are underway with health systems stakeholders to develop the interpretation sequence as part of a health policy and systems research approach.

X Demographics

X Demographics

The data shown below were collected from the profiles of 7 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 64 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 64 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 13 20%
Student > Master 12 19%
Student > Ph. D. Student 6 9%
Lecturer 5 8%
Student > Doctoral Student 3 5%
Other 9 14%
Unknown 16 25%
Readers by discipline Count As %
Medicine and Dentistry 24 38%
Social Sciences 10 16%
Nursing and Health Professions 7 11%
Business, Management and Accounting 2 3%
Agricultural and Biological Sciences 1 2%
Other 5 8%
Unknown 15 23%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 6. 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 12 July 2016.
All research outputs
#5,738,787
of 22,877,793 outputs
Outputs from Global Health Research and Policy
#79
of 200 outputs
Outputs of similar age
#94,735
of 352,336 outputs
Outputs of similar age from Global Health Research and Policy
#2
of 7 outputs
Altmetric has tracked 22,877,793 research outputs across all sources so far. This one has received more attention than most of these and is in the 74th percentile.
So far Altmetric has tracked 200 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 15.6. This one has gotten more attention than average, scoring higher than 60% 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 352,336 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 72% of its contemporaries.
We're also able to compare this research output to 7 others from the same source and published within six weeks on either side of this one. This one has scored higher than 5 of them.