Matthew Tuson
Biographic Data
| ID | 5233637 |
|---|---|
| NAME | Matthew Tuson |
| GIVEN NAMES | Matthew |
| FAMILY NAME | Tuson |
| SIGNATURE | TUSON M |
| AFFILIATIONS | The University of Western Australia |
| ORCID | 0000-0002-3135-3672 |
| VERIFIED | Yes |
| TOTAL WORKS | 6 |
| TOTAL CITATIONS | 2 |
| WORKS AS AUTHOR | 6 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2021 |
| LATEST PUBLICATION YEAR | 2022 |
| H-INDEX | 1 |
Improving the Efficiency of Geographic Target Regions for Healthcare Interventions
Appropriate prioritisation of geographic target regions (TRs) for healthcare interventions is critical to ensure the efficient distribution of finite healthcare resources. In delineating TRs, both 'targeting efficiency', i.e., the return on intervention investment, and logistical factors, e.g., the number of TRs, are important. However, existing approaches to delineate TRs disproportionately prioritise targeting efficiency. To address this, we ex…
Analysing geographic variation in lower urgency emergency department presentations using readily – available administrative boundaries and a novel spatial smoothing technique
Misallocation of finite healthcare resources can occur when guided by maps that are produced using aggregate-level administrative units. Such maps are affected by the modifiable areal unit problem (MAUP), which describes how patterns may change depending on the particular choice of mapping unit. Smoothing can help avoid this unintended yet detrimental phenomenon. This paper compares the utility of aggregate-level administrative units and smoothin…
Impact of Australian Bureau of Statistics data perturbation techniques on the precision of Census population counts, and the propagation of this impact in a geospatial analysis of high-risk foot hospi…
Precise population counts facilitate reliable estimation of differences in disease risk between population sub-groups or geographic regions, which informs rational public health decision-making. In Australia, Census population counts obtainable via the Australian Bureau of Statistics’ (ABS’) TableBuilder tool, which are widely used, are routinely perturbed to protect privacy. We examine this perturbation’s impact on: the precision of TableBuilder…
Predicting Future Geographic Hotspots of Potentially Preventable Hospitalisations Using All Subset Model Selection and Repeated K-Fold Cross-Validation
Long-term future prediction of geographic areas with high rates of potentially preventable hospitalisations (PPHs) among residents, or "hotspots", is critical to ensure the effective location of place-based health service interventions. This is because such interventions are typically expensive and take time to develop, implement, and take effect, and hotspots often regress to the mean. Using spatially aggregated, longitudinal administrative heal…
Modelling the Relationship between Rainfall and Mental Health Using Different Spatial and Temporal Units
Drought is thought to impact upon the mental health of agricultural communities, but studies of this relationship have reported inconsistent results. A source of inconsistency could be the aggregation of data by a single spatiotemporal unit of analysis, which induces the modifiable areal and temporal unit problems. To investigate this, mental health-related emergency department (MHED) presentations among residents of the Wheat Belt region of West…
Multimorbidity among People Experiencing Homelessness—Insights from Primary Care Data
The study findings have substantial implications from both a health risk and healthcare treatment perspective for people experiencing homeless. The pervasiveness of preventable health conditions among people experiencing homelessness also highlights the imperative to improve the accessibility of public health programs and screening to reduce their morbidity and premature mortality
Impact of Australian Bureau of Statistics data perturbation techniques on the precision of Census population counts, and the propagation of this impact in a geospatial analysis of high-risk foot hospi…
Precise population counts facilitate reliable estimation of differences in disease risk between population sub-groups or geographic regions, which informs rational public health decision-making. In Australia, Census population counts obtainable via the Australian Bureau of Statistics’ (ABS’) TableBuilder tool, which are widely used, are routinely perturbed to protect privacy. We examine this perturbation’s impact on: the precision of TableBuilder…
Predicting Future Geographic Hotspots of Potentially Preventable Hospitalisations Using All Subset Model Selection and Repeated K-Fold Cross-Validation
Long-term future prediction of geographic areas with high rates of potentially preventable hospitalisations (PPHs) among residents, or "hotspots", is critical to ensure the effective location of place-based health service interventions. This is because such interventions are typically expensive and take time to develop, implement, and take effect, and hotspots often regress to the mean. Using spatially aggregated, longitudinal administrative heal…
Modelling the Relationship between Rainfall and Mental Health Using Different Spatial and Temporal Units
Drought is thought to impact upon the mental health of agricultural communities, but studies of this relationship have reported inconsistent results. A source of inconsistency could be the aggregation of data by a single spatiotemporal unit of analysis, which induces the modifiable areal and temporal unit problems. To investigate this, mental health-related emergency department (MHED) presentations among residents of the Wheat Belt region of West…
Multimorbidity among People Experiencing Homelessness—Insights from Primary Care Data
The study findings have substantial implications from both a health risk and healthcare treatment perspective for people experiencing homeless. The pervasiveness of preventable health conditions among people experiencing homelessness also highlights the imperative to improve the accessibility of public health programs and screening to reduce their morbidity and premature mortality
Improving the Efficiency of Geographic Target Regions for Healthcare Interventions
Appropriate prioritisation of geographic target regions (TRs) for healthcare interventions is critical to ensure the efficient distribution of finite healthcare resources. In delineating TRs, both 'targeting efficiency', i.e., the return on intervention investment, and logistical factors, e.g., the number of TRs, are important. However, existing approaches to delineate TRs disproportionately prioritise targeting efficiency. To address this, we ex…
Analysing geographic variation in lower urgency emergency department presentations using readily – available administrative boundaries and a novel spatial smoothing technique
Misallocation of finite healthcare resources can occur when guided by maps that are produced using aggregate-level administrative units. Such maps are affected by the modifiable areal unit problem (MAUP), which describes how patterns may change depending on the particular choice of mapping unit. Smoothing can help avoid this unintended yet detrimental phenomenon. This paper compares the utility of aggregate-level administrative units and smoothin…
Impact of Australian Bureau of Statistics data perturbation techniques on the precision of Census population counts, and the propagation of this impact in a geospatial analysis of high-risk foot hospi…
Precise population counts facilitate reliable estimation of differences in disease risk between population sub-groups or geographic regions, which informs rational public health decision-making. In Australia, Census population counts obtainable via the Australian Bureau of Statistics’ (ABS’) TableBuilder tool, which are widely used, are routinely perturbed to protect privacy. We examine this perturbation’s impact on: the precision of TableBuilder…
Geography (5 works) · Medicine (4 works) · Computer Science (3 works) · Demography (3 works) · Demography (3 works) · Health disparities and outcomes (3 works) · Mathematics (3 works) · Nursing (3 works) · Statistics (3 works) · Business (2 works)