Special issue on global health

Royston, Geoff

doi:10.1007/s10729-012-9205-z

Cited by 1 publication

(2 citation statements)

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“…Availability of reliable data is one of the challenges that sets low-income countries apart from middle-income countries with regards to modelling [32]. In this review, the studies in some middle-income countries (e.g.…”

Section: Resultsmentioning

confidence: 99%

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Operations research in global health: a scoping review with a focus on the themes of health equity and impact

Bradley

Jung

Tandon-Verma

et al. 2017

Health Res Policy Sys

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BackgroundOperations research (OR) is a discipline that uses advanced analytical methods (e.g. simulation, optimisation, decision analysis) to better understand complex systems and aid in decision-making.SummaryHerein, we present a scoping review of the use of OR to analyse issues in global health, with an emphasis on health equity and research impact. A systematic search of five databases was designed to identify relevant published literature. A global overview of 1099 studies highlights the geographic distribution of OR and common OR methods used. From this collection of literature, a narrative description of the use of OR across four main application areas of global health – health systems and operations, clinical medicine, public health and health innovation – is also presented. The theme of health equity is then explored in detail through a subset of 44 studies. Health equity is a critical element of global health that cuts across all four application areas, and is an issue particularly amenable to analysis through OR. Finally, we present seven select cases of OR analyses that have been implemented or have influenced decision-making in global health policy or practice. Based on these cases, we identify three key drivers for success in bridging the gap between OR and global health policy, namely international collaboration with stakeholders, use of contextually appropriate data, and varied communication outlets for research findings. Such cases, however, represent a very small proportion of the literature found.ConclusionPoor availability of representative and quality data, and a lack of collaboration between those who develop OR models and stakeholders in the contexts where OR analyses are intended to serve, were found to be common challenges for effective OR modelling in global health.Electronic supplementary materialThe online version of this article (doi:10.1186/s12961-017-0187-7) contains supplementary material, which is available to authorized users.

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Section: Resultsmentioning

confidence: 99%

“…We chose to focus on papers published in the year 2000 and later. As such, there is some overlap with the hand-searched literature [11, 16, 17, 23, 24, 26–28, 32], but not with the review of OR in global health by Datta [10], which at the time of our review was over 20 years old. To fill this gap would have been an onerous task.…”

Section: Discussionmentioning

confidence: 99%