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

Abstract

Background: Operations 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. Herein, 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.

Conclusion: Poor 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.

Keywords: Decision-making; Developing countries; Global health; Health equity; Health systems; Low-resource settings; Modelling; Operations research; Policy.

Fig. 1

Systematic search results and screening process

Fig. 2

Breakdown of operations research studies according to World Bank income classification of the country of focus – low-income (L), lower-middle-income (LM) or upper-middle-income (UM) – for (a) all studies (n = 1099) including studies about low- and middle-income countries in general or some combination of regions and/or L-, LM- and UM-income countries; and (b) studies focused on a single country only (n = 817)

Fig. 3

Number of operations research studies by country. Note that only studies that focused on a single country (n = 817) or multiple specific countries (n = 55) are represented in this figure. Studies that considered multiple countries are counted once for each country represented

Fig. 4

Proportion of operations research (OR) studies per year in different country income classifications (bars, left axis); low income (L), lower-middle income (LM), upper-middle income (UM) and Other (includes studies targeted at LMICs in general or some combination of L-, LM- and UM-income countries). Total number of OR papers per year also displayed (line, right axis). Note that 2014 was excluded as this review covers studies indexed up until August 2014 only

Fig. 5

Breakdown of operations research methodologies. The Stochastic category includes Markov models (e.g. state-transition and decision process models) and Monte Carlo methods. The Mathematical category includes deterministic models, epidemiological compartmental models, and other analytical models described by governing equations. The Other category includes all remaining smaller categories including artificial neural networks, inventory models, spreadsheet models with no analytical formulation, etc. See Box 2 Criterion (1) for additional details about the methodologies included. DEA data envelopment analysis

Fig. 6

Percentage of operations research studies (n = 1099) by application area of global health and by analysis target level (local, national, regional, global or general)

Fig. 7

Number of equity-themed OR papers by topic area. Note that some studies looked at equity across several categories; these were counted for each relevant category. Marginalised groups include people living with HIV or other stigmatised illnesses. High risk groups include men who have sex with men, commercial sex workers, or people considered to be in high risk age groups for certain diseases