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Use of Physical Accessibility Modelling in Diagnostic Network Optimization: A Review
Camille Chênes1, Heidi Albert2, Kekeletso Kao3
1Institute for Environmental Sciences, University of Geneva, 1205 Geneva, Switzerland.
Diagnostics (Basel, Switzerland)
|January 21, 2022
Summary
Diagnostic network optimization (DNO) is vital for healthcare. This review found limited use of advanced geospatial modeling in DNO, highlighting potential for improved efficiency and accessibility in diagnostic services.
Area of Science:
- Public Health
- Health Systems Research
- Geospatial Health Informatics
Background:
- Diagnostic networks are complex systems essential for timely healthcare access.
- Optimization of these networks (DNO) is critical for improving overall healthcare system performance.
- Geospatial modeling, particularly physical accessibility, has advanced health system assessments.
Purpose of the Study:
- To review the application of geospatial modeling, specifically physical accessibility, in diagnostic network optimization (DNO).
- To assess the extent to which DNO has benefited from recent advances in geospatial modeling techniques.
- To identify research gaps and future directions for integrating advanced geospatial methods into DNO.
Main Methods:
- Systematic literature search of Web of Science and PubMed for publications on DNO, geographical accessibility, and optimization (up to August 12, 2021).
- Complementary snowball search to identify additional relevant studies.
- Selection and charting of seven relevant publications utilizing various geospatial approaches.
Main Results:
- A paucity of publications was identified concerning the integration of advanced geospatial modeling in DNO.
- The reviewed studies employed a variety of geospatial approaches for optimization within diagnostic networks.
- Existing research indicates a missed opportunity to leverage sophisticated accessibility modeling in DNO.
Conclusions:
- There is a significant need to explore the linkage between DNO procedures and realistic accessibility modeling frameworks.
- Integrating advanced geospatial modeling can lead to better estimations of travel times for specimens and populations.
- This integration offers potential for improved demand forecasting and innovative approaches to disease epidemiology in DNO.
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