David Whyatt
Biographic Data
| ID | 5233640 |
|---|---|
| NAME | David Whyatt |
| GIVEN NAMES | David |
| FAMILY NAME | Whyatt |
| SIGNATURE | WHYATT D |
| AFFILIATIONS | The University of Western Australia |
| ORCID | 0000-0002-6905-1979 |
| VERIFIED | Yes |
| TOTAL WORKS | 7 |
| TOTAL CITATIONS | 2 |
| AUTHOR COUNT | 7 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2014 |
| 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…
The Ecological Fallacy of the Role of Age in Chronic Disease and Hospital Demand
OBJECTIVE: To examine the relationship between age and all-cause hospital utilization in the years preceding and following a diagnosis in hospital of heart failure, type 2 diabetes, or chronic obstructive pulmonary disease (COPD). RESEARCH DESIGN: A cohort study of all patients in Western Australia who have had a principal diagnosis of heart failure, type 2 diabetes, or COPD, upon admission to hospital. All-cause hospital utilization 6 years prec…
The Ratchet Effect
OBJECTIVE: To describe the previously unexamined association between admissions to hospital with chronic disease and changes in all-cause health service utilization over time. RESEARCH DESIGN: A cohort study examining the population of Western Australia with hospitalizations for chronic disease from 2002 to 2010. A "rolling" clearance period is used to define "cardinal events," that is, a disease-specific diagnosis upon hospital admission, where …
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…
The Ecological Fallacy of the Role of Age in Chronic Disease and Hospital Demand
OBJECTIVE: To examine the relationship between age and all-cause hospital utilization in the years preceding and following a diagnosis in hospital of heart failure, type 2 diabetes, or chronic obstructive pulmonary disease (COPD). RESEARCH DESIGN: A cohort study of all patients in Western Australia who have had a principal diagnosis of heart failure, type 2 diabetes, or COPD, upon admission to hospital. All-cause hospital utilization 6 years prec…
The Ratchet Effect
OBJECTIVE: To describe the previously unexamined association between admissions to hospital with chronic disease and changes in all-cause health service utilization over time. RESEARCH DESIGN: A cohort study examining the population of Western Australia with hospitalizations for chronic disease from 2002 to 2010. A "rolling" clearance period is used to define "cardinal events," that is, a disease-specific diagnosis upon hospital admission, where …
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…
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…
Medicine (5 works) · Demography (4 works) · Geography (4 works) · Computer Science (3 works) · Demography (3 works) · Emergency department (3 works) · Health disparities and outcomes (3 works) · Healthcare Policy and Management (3 works) · Mathematics (3 works) · Statistics (3 works)