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Applying a system dynamics modelling approach to explore policy options for improving neonatal health in Uganda

Overview of attention for article published in Health Research Policy and Systems, May 2016
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  • Good Attention Score compared to outputs of the same age (68th percentile)

Mentioned by

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1 policy source
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3 X users

Citations

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34 Dimensions

Readers on

mendeley
281 Mendeley
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Title
Applying a system dynamics modelling approach to explore policy options for improving neonatal health in Uganda
Published in
Health Research Policy and Systems, May 2016
DOI 10.1186/s12961-016-0101-8
Pubmed ID
Authors

Agnes Rwashana Semwanga, Sarah Nakubulwa, Taghreed Adam

Abstract

The most recent reports on global trends in neonatal mortality continue to show alarmingly slow progress on improvements in neonatal mortality rates, with sub-Saharan Africa still lagging behind. This emphasised the urgent need to innovatively employ alternative solutions that take into account the intricate complexities of neonatal health and the health systems in which the various strategies operate. In our first paper, we empirically explored the causes of the stagnating neonatal mortality in Uganda using a dynamic synthesis methodology (DSM) approach. In this paper, we completed the last three stages of DSM, which involved the development of a quantitative (simulation) model, using STELLA modelling software. We used statistical data to populate the model. Through brainstorming sessions with stakeholders, iterations to test and validate the model were undertaken. The different strategies and policy interventions that could possibly lower neonatal mortality rates were tested using what-if analysis. Sensitivity analysis was used to determine the strategies that could have a great impact on neonatal mortality. We developed a neonatal health simulation model (NEOSIM) to explore potential interventions that could possibly improve neonatal health within a health system context. The model has four sectors, namely population, demand for services, health of the mothers and choices of clinical care. It tests the effects of various interventions validated by a number of Ugandan health practitioners, including health education campaigns, free delivery kits, motorcycle coupons, kangaroo mother care, improving neonatal resuscitation and labour management skills, and interventions to improve the mothers health, i.e. targeting malaria, anaemia and tetanus. Among the tested interventions, the package with the highest impact on reducing neonatal mortality rates was a combination of the free delivery kits in a setting where delivery services were free and motorcycle coupons to take women to hospital during emergencies. This study presents a System Dynamics model with a broad and integrated view of the neonatal health system facilitating a deeper understanding of its current state and constraints and how these can be mitigated. A tool with a user friendly interface presents the dynamic nature of the model using 'what-if' scenarios, thus enabling health practitioners to discuss the consequences or effects of various decisions. Key findings of the research show that proposed interventions and their impact can be tested through simulation experiments thereby generating policies and interventions with the highest impact for improved healthcare service delivery.

X Demographics

X Demographics

The data shown below were collected from the profiles of 3 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 281 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 2 <1%
Unknown 279 99%

Demographic breakdown

Readers by professional status Count As %
Student > Master 53 19%
Researcher 41 15%
Student > Ph. D. Student 34 12%
Student > Bachelor 20 7%
Other 18 6%
Other 42 15%
Unknown 73 26%
Readers by discipline Count As %
Medicine and Dentistry 63 22%
Nursing and Health Professions 33 12%
Social Sciences 21 7%
Engineering 20 7%
Computer Science 9 3%
Other 49 17%
Unknown 86 31%
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 07 November 2021.
All research outputs
#6,437,117
of 22,867,327 outputs
Outputs from Health Research Policy and Systems
#763
of 1,216 outputs
Outputs of similar age
#91,815
of 298,972 outputs
Outputs of similar age from Health Research Policy and Systems
#19
of 26 outputs
Altmetric has tracked 22,867,327 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 1,216 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 13.1. This one is in the 36th percentile – i.e., 36% 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 298,972 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 68% of its contemporaries.
We're also able to compare this research output to 26 others from the same source and published within six weeks on either side of this one. This one is in the 26th percentile – i.e., 26% of its contemporaries scored the same or lower than it.