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Understanding causal pathways within health systems policy evaluation through mediation analysis: an application to payment for performance (P4P) in Tanzania

Overview of attention for article published in Implementation Science, February 2017
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (83rd percentile)
  • Average Attention Score compared to outputs of the same age and source

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1 policy source
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12 X users
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1 Facebook page

Citations

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45 Dimensions

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196 Mendeley
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Title
Understanding causal pathways within health systems policy evaluation through mediation analysis: an application to payment for performance (P4P) in Tanzania
Published in
Implementation Science, February 2017
DOI 10.1186/s13012-016-0540-1
Pubmed ID
Authors

Laura Anselmi, Peter Binyaruka, Josephine Borghi

Abstract

The evaluation of payment for performance (P4P) programmes has focused mainly on understanding contributions to health service coverage, without unpacking causal mechanisms. The overall aim of the paper is to test the causal pathways through which P4P schemes may (or may not) influence maternal care outcomes. We used data from an evaluation of a P4P programme in Tanzania. Data were collected from a sample of 3000 women who delivered in the 12 months prior to interview and 200 health workers at 150 health facilities from seven intervention and four comparison districts in Tanzania in January 2012 and in February 2013. We applied causal mediation analysis using a linear structural equation model to identify direct and indirect effects of P4P on institutional delivery rates and on the uptake of two doses of an antimalarial drug during pregnancy. We first ran a series of linear difference-in-difference regression models to test the effect of P4P on potential mediators, which we then included in a linear difference-in-difference model evaluating the impact of P4P on the outcome. We tested the robustness of our results to unmeasured confounding using semi-parametric methods. P4P reduced the probability of women paying for delivery care (-4.5 percentage points) which mediates the total effect of P4P on institutional deliveries (by 48%) and on deliveries in a public health facility (by 78%). P4P reduced the stock-out rate for some essential drugs, specifically oxytocin (-36 percentage points), which mediated the total effect of P4P on institutional deliveries (by 22%) and deliveries in a public health facility (by 30%). P4P increased kindness at delivery (5 percentage points), which mediated the effect of P4P on institutional deliveries (by 48%) and on deliveries in a public health facility (by 49%). P4P increased the likelihood of supervision visits taking place within the last 90 days (18 percentage points), which mediated 15% of the total P4P effect on the uptake of two antimalarial doses during antenatal care (IPT2). Kindness during deliveries and the probability of paying out of pocket for delivery care were the mediators most robust to unmeasured confounding. The effect of P4P on institutional deliveries is mediated by financing and human resources factors, while uptake of antimalarials in pregnancy is mediated by governance factors. Further research is required to explore additional and more complex causal pathways.

X Demographics

X Demographics

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 196 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 196 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 35 18%
Student > Ph. D. Student 33 17%
Student > Master 33 17%
Other 9 5%
Student > Doctoral Student 8 4%
Other 31 16%
Unknown 47 24%
Readers by discipline Count As %
Social Sciences 34 17%
Medicine and Dentistry 33 17%
Economics, Econometrics and Finance 20 10%
Nursing and Health Professions 19 10%
Business, Management and Accounting 5 3%
Other 27 14%
Unknown 58 30%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 10. 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 15 November 2018.
All research outputs
#3,654,195
of 25,271,884 outputs
Outputs from Implementation Science
#723
of 1,795 outputs
Outputs of similar age
#71,816
of 432,002 outputs
Outputs of similar age from Implementation Science
#23
of 42 outputs
Altmetric has tracked 25,271,884 research outputs across all sources so far. Compared to these this one has done well and is in the 85th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,795 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 14.9. This one has gotten more attention than average, scoring higher than 59% 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 432,002 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 83% of its contemporaries.
We're also able to compare this research output to 42 others from the same source and published within six weeks on either side of this one. This one is in the 47th percentile – i.e., 47% of its contemporaries scored the same or lower than it.