title: Poverty identification for a pro-poor health insurance scheme in Tanzania: reliability and multi-level stakeholder perceptions.
abstract: BACKGROUND
  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.
  
  
  METHODS
  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.
  
  
  RESULTS
  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.
  
  
  CONCLUSIONS
  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.
authors.affiliation: Ifakara Health Institute, Plot 463, Kiko Avenue Mikocheni, P.O. Box 78 373, Dar es Salaam, Tanzania. ajoachim@ihi.or.tz.
authors.forename: August
authors.initials: A
authors.lastname: Kuwawenaruwa
authors.affiliation: Ifakara Health Institute, Plot 463, Kiko Avenue Mikocheni, P.O. Box 78 373, Dar es Salaam, Tanzania. jbaraka@ihi.or.tz.
authors.forename: Jitihada
authors.initials: J
authors.lastname: Baraka
authors.affiliation: Columbia University, Mailman School of Public Health, New York, NY, USA. kmr2006@cumc.columbia.edu.
authors.forename: Kate
authors.initials: K
authors.lastname: Ramsey
authors.affiliation: Ifakara Health Institute, Plot 463, Kiko Avenue Mikocheni, P.O. Box 78 373, Dar es Salaam, Tanzania. fmanzi@ihi.or.tz.
authors.forename: Fatuma
authors.initials: F
authors.lastname: Manzi
authors.affiliation: Population Council, Lusaka, Zambia. bbellows@popcouncil.org.
authors.forename: Ben
authors.initials: B
authors.lastname: Bellows
authors.affiliation: Ifakara Health Institute, Plot 463, Kiko Avenue Mikocheni, P.O. Box 78 373, Dar es Salaam, Tanzania. Josephine.Borghi@lshtm.ac.uk.|Department of Global Health and Development, London School of Hygiene & Tropical Medicine, London, UK. Josephine.Borghi@lshtm.ac.uk.
authors.forename: Josephine
authors.initials: J
authors.lastname: Borghi
mesh_terms: D000328:Adult; D005260:Female; D017144:Focus Groups; D006801:Humans; D007348:Insurance, Health / Q000191:economics / Q000706:statistics & numerical data*; D008297:Male; D008875:Middle Aged; D009313:National Health Programs / Q000191:economics / Q000706:statistics & numerical data*; D010465:Perception; D011203:Poverty / Q000145:classification*; D015203:Reproducibility of Results; D012111:Residence Characteristics; D013636:Tanzania