Abstract
Diagnostic networks are complex systems that include both laboratory-tested and community-based diagnostics, as well as a specimen referral system that links health tiers. Since diagnostics are the first step before accessing appropriate care, diagnostic network optimization (DNO) is crucial to improving the overall healthcare system. The aim of our review was to understand whether the field of DNO, and especially route optimization, has benefited from the recent advances in geospatial modeling, and notably physical accessibility modeling, that have been used in numerous health systems assessment and strengthening studies. All publications published in English between the journal’s inception and 12 August 2021 that dealt with DNO, geographical accessibility and optimization, were systematically searched for in Web of Science and PubMed, this search was complemented by a snowball search. Studies from any country were considered. Seven relevant publications were selected and charted, with a variety of geospatial approaches used for optimization. This paucity of publications calls for exploring the linkage of DNO procedures with realistic accessibility modeling framework. The potential benefits could be notably better-informed travel times of either the specimens or population, better estimates of the demand for diagnostics through realistic population catchments, and innovative ways of considering disease epidemiology to inform DNO.
Highlights
The importance of attaining Universal Health Coverage, a key target of the 2030Sustainable Development Goals no. 3, is no longer contested [1]
Make use of accessibility models informed by field- or expert-based information on speed and mode of transport of either samples or patients. This may impact on the realism of the model results and is at odds with the growing literature that uses this type of modeling approach for various other health services [10,40,41,42]. This seemingly sub-optimal use of the recent physical accessibility models may come from the recent consideration of the importance of data analytics in diagnostic network optimization (DNO) [6]
It may reflect a decoupling of the types of geospatial tools traditionally used for optimizing supply chains, with the category of tools that inform health systems strengthening and scaling up
Summary
The importance of attaining Universal Health Coverage, a key target of the 2030Sustainable Development Goals no. 3, is no longer contested [1]. By prescribing the appropriate treatment, diagnostics help reduce excessive drug use, thereby reducing the emergence of antimicrobial resistance and minimizing financial losses They are essential for the early detection of diseases, enabling the monitoring and control of the spread and emergence of infectious diseases [2,3]. A recent study [4] on 10 low- and middle-income countries (LMICs) showed that major gaps in diagnostic availability exist in some of these countries, at the primary care level Another recent publication on nine LMICs and two states in the USA shows that access to laboratory tests other than malaria and HIV are relatively low, with only 10–20%
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