Evidence map›Paper›PMID 26626873›Full record

ArticleInternational journal for equity in health2015

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

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

Abstract read
In one paragraph

Article in International journal for equity in health, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

August KuwawenaruwaIfakara Health Institute, Plot 463, Kiko Avenue Mikocheni, P.O. Box 78 373, Dar es Salaam, Tanzania. ajoachim@ihi.or.tz.
Jitihada BarakaIfakara Health Institute, Plot 463, Kiko Avenue Mikocheni, P.O. Box 78 373, Dar es Salaam, Tanzania. jbaraka@ihi.or.tz.
Kate RamseyColumbia University, Mailman School of Public Health, New York, NY, USA. kmr2006@cumc.columbia.edu.
Fatuma ManziIfakara Health Institute, Plot 463, Kiko Avenue Mikocheni, P.O. Box 78 373, Dar es Salaam, Tanzania. fmanzi@ihi.or.tz.
Ben BellowsPopulation Council, Lusaka, Zambia. bbellows@popcouncil.org.
Josephine BorghiIfakara Health Institute, Plot 463, Kiko Avenue Mikocheni, P.O. Box 78 373, Dar es Salaam, Tanzania. Josephine.Borghi@lshtm.ac.uk.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMany 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.

methodsWe 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.

findingsThe 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.

conclusionIn 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.

Indexed as

PerceptionAdultFemaleFocus GroupsHumansInsurance, HealthMaleMiddle AgedNational Health ProgramsPovertyReproducibility of ResultsResidence CharacteristicsTanzania

Identifiers

PMID26626873
PMCPMC4666058

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.