↓ Skip to main content

Poverty identification for a pro-poor health insurance scheme in Tanzania: reliability and multi-level stakeholder perceptions

Overview of attention for article published in International Journal for Equity in Health, December 2015
Altmetric Badge

About this Attention Score

  • Good Attention Score compared to outputs of the same age (72nd percentile)
  • Above-average Attention Score compared to outputs of the same age and source (55th percentile)

Mentioned by

twitter
5 X users

Citations

dimensions_citation
8 Dimensions

Readers on

mendeley
118 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Poverty identification for a pro-poor health insurance scheme in Tanzania: reliability and multi-level stakeholder perceptions
Published in
International Journal for Equity in Health, December 2015
DOI 10.1186/s12939-015-0273-9
Pubmed ID
Authors

August Kuwawenaruwa, Jitihada Baraka, Kate Ramsey, Fatuma Manzi, Ben Bellows, Josephine Borghi

Abstract

Many low income countries have policies to exempt the poor from user charges in public facilities. Reliably identifying the poor is a challenge when implementing such policies. In Tanzania, a scorecard system was established in 2011, within a programme providing free national health insurance fund (NHIF) cards, to identify poor pregnant women and their families, based on eight components. Using a series of reliability tests on a 2012 dataset of 2,621 households in two districts, this study compares household poverty levels using the scorecard, a wealth index, and monthly consumption expenditures. We compared the distributions of the three wealth measures, and the consistency of household poverty classification using cross-tabulations and the Kappa statistic. We measured errors of inclusion and exclusion of the scorecard relative to the other methods. We also gathered perceptions of the scorecard criteria through qualitative interviews with stakeholders at multiple levels of the health system. The distribution of the scorecard was less skewed than other wealth measures and not truncated, but demonstrated clumping. There was a higher level of agreement between the scorecard and the wealth index than consumption expenditure. The scorecard identified a similar number of poor households as the "basic needs" poverty line based on monthly consumption expenditure, with only 45 % errors of inclusion. However, it failed to pick up half of those living below the "basic needs" poverty line as being poor. Stakeholders supported the inclusion of water sources, income, food security and disability measures but had reservations about other items on the scorecard. In choosing poverty identification strategies for programmes seeking to enhance health equity it's necessary to balance between community acceptability, local relevance and the need for such a strategy. It is important to ensure the strategy is efficient and less costly than alternatives in order to effectively reduce health disparities.

X Demographics

X Demographics

The data shown below were collected from the profiles of 5 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 118 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 <1%
Unknown 117 99%

Demographic breakdown

Readers by professional status Count As %
Student > Master 18 15%
Researcher 16 14%
Student > Ph. D. Student 16 14%
Student > Bachelor 7 6%
Student > Postgraduate 5 4%
Other 19 16%
Unknown 37 31%
Readers by discipline Count As %
Social Sciences 22 19%
Medicine and Dentistry 16 14%
Nursing and Health Professions 11 9%
Business, Management and Accounting 7 6%
Psychology 5 4%
Other 18 15%
Unknown 39 33%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 4. 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 29 April 2016.
All research outputs
#6,427,128
of 22,834,308 outputs
Outputs from International Journal for Equity in Health
#1,004
of 1,906 outputs
Outputs of similar age
#101,196
of 387,566 outputs
Outputs of similar age from International Journal for Equity in Health
#20
of 47 outputs
Altmetric has tracked 22,834,308 research outputs across all sources so far. This one has received more attention than most of these and is in the 70th percentile.
So far Altmetric has tracked 1,906 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 11.2. This one is in the 45th percentile – i.e., 45% of its peers scored the same or lower than it.
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 387,566 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 47 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 55% of its contemporaries.