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Identifying implementation bottlenecks for maternal and newborn health interventions in rural districts of the United Republic of Tanzania

Overview of attention for article published in Bulletin of the World Health Organization, April 2015
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (56th percentile)

Mentioned by

policy
1 policy source

Citations

dimensions_citation
56 Dimensions

Readers on

mendeley
224 Mendeley
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Title
Identifying implementation bottlenecks for maternal and newborn health interventions in rural districts of the United Republic of Tanzania
Published in
Bulletin of the World Health Organization, April 2015
DOI 10.2471/blt.14.141879
Pubmed ID
Authors

Ulrika Baker, Stefan Peterson, Tanya Marchant, Godfrey Mbaruku, Silas Temu, Fatuma Manzi, Claudia Hanson

Abstract

To estimate effective coverage of maternal and newborn health interventions and to identify bottlenecks in their implementation in rural districts of the United Republic of Tanzania. Cross-sectional data from households and health facilities in Tandahimba and Newala districts were used in the analysis. We adapted Tanahashi's model to estimate intervention coverage in conditional stages and to identify implementation bottlenecks in access, health facility readiness and clinical practice. The interventions studied were syphilis and pre-eclampsia screening, partograph use, active management of the third stage of labour and postpartum care. Effective coverage was low in both districts, ranging from only 3% for postpartum care in Tandahimba to 49% for active management of the third stage of labour in Newala. In Tandahimba, health facility readiness was the largest bottleneck for most interventions, whereas in Newala, it was access. Clinical practice was another large bottleneck for syphilis screening in both districts. The poor effective coverage of maternal and newborn health interventions in rural districts of the United Republic of Tanzania reinforces the need to prioritize health service quality. Access to high-quality local data by decision-makers would assist planning and prioritization. The approach of estimating effective coverage and identifying bottlenecks described here could facilitate progress towards universal health coverage for any area of care and in any context.

Mendeley readers

The data shown below were compiled from readership statistics for 224 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 2 <1%
Rwanda 1 <1%
Belgium 1 <1%
Unknown 220 98%

Demographic breakdown

Readers by professional status Count As %
Student > Master 45 20%
Researcher 37 17%
Student > Ph. D. Student 23 10%
Student > Postgraduate 17 8%
Student > Bachelor 15 7%
Other 47 21%
Unknown 40 18%
Readers by discipline Count As %
Medicine and Dentistry 70 31%
Nursing and Health Professions 33 15%
Social Sciences 29 13%
Agricultural and Biological Sciences 7 3%
Psychology 6 3%
Other 25 11%
Unknown 54 24%

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 01 January 2021.
All research outputs
#6,442,451
of 19,862,278 outputs
Outputs from Bulletin of the World Health Organization
#2,043
of 4,144 outputs
Outputs of similar age
#115,602
of 294,220 outputs
Outputs of similar age from Bulletin of the World Health Organization
#42
of 52 outputs
Altmetric has tracked 19,862,278 research outputs across all sources so far. This one is in the 45th percentile – i.e., 45% of other outputs scored the same or lower than it.
So far Altmetric has tracked 4,144 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 13.5. This one is in the 8th percentile – i.e., 8% 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 294,220 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 56% of its contemporaries.
We're also able to compare this research output to 52 others from the same source and published within six weeks on either side of this one. This one is in the 13th percentile – i.e., 13% of its contemporaries scored the same or lower than it.