澳大利亚医疗保健道路可达性数据集:基于服务的分组和住宅可达性。

IF 1.4 Q3 MULTIDISCIPLINARY SCIENCES
Data in Brief Pub Date : 2025-09-12 eCollection Date: 2025-10-01 DOI:10.1016/j.dib.2025.112068
Kiki Adhinugraha, Thanh Phan, Richard Beare, Albert Phan, Shiyang Lyu, David Taniar
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引用次数: 0

摘要

该数据集提供了澳大利亚全国医疗保健道路可达性的覆盖范围,重点关注五种类型的设施:基于临床服务可用性的四个医院组和一组救护站。根据医院提供的临床服务数量,将医院分为四组:蓝色(16项服务)、绿色(11-15项)、橙色(5-10项)和红色(10项)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

A dataset of healthcare road accessibility in Australia: service-based grouping and residential reachability.

A dataset of healthcare road accessibility in Australia: service-based grouping and residential reachability.

A dataset of healthcare road accessibility in Australia: service-based grouping and residential reachability.

A dataset of healthcare road accessibility in Australia: service-based grouping and residential reachability.

This dataset provides national coverage of healthcare road accessibility in Australia, focusing on five types of facilities: four hospital groups based on clinical service availability and one group of ambulance stations. Hospitals are classified into four groups based on the number of clinical services they offer: Blue (>16 services), Green (11-15), Orange (5-10), and Red (<5). Ambulance stations are treated as a distinct group to support emergency access analysis. For each group, the dataset presents travel distance and estimated driving time from major road points, enabling a consistent and structured view of spatial access to healthcare services across the country. Road accessibility is calculated using shortest-path routing across OpenStreetMap road networks. Estimated travel times are adjusted based on road speed limits and regional driving conditions (urban, regional, or remote). Two accessibility layers are provided: (1) a comprehensive set of road nodes showing distance (in kilometres) and travel time (in hours) to the nearest hospital in each group, and (2) a set of sampled residential address points, representing population perspectives, with linked nearest-healthcare metrics for each group, and aggregated summaries by SA2, LGA, and remoteness levels. Travel time accuracy was validated against Google Maps API, with average discrepancies of 3 min in urban areas, 10 min in regional areas, and 90 min in remote areas. Summary statistics are also available at the Local Government Area (LGA), Statistical Area Level 2 (SA2), and remoteness levels, allowing high-level regional comparisons. The dataset includes vector-based geospatial files representing hospitals, ambulance stations, road nodes, and residential samples. All layers use the GDA2020 datum (EPSG:7844) and are derived from the Australian Institute of Health and Welfare (hospital services), Digital Atlas Australia (ambulance locations), OpenStreetMap (road networks), Australian Bureau of Statistics (boundaries), and Geoscape G-NAF (residential addresses). The dataset supports public health planning by illustrating which facilities are reachable by road, the estimated distance and travel time to reach them, and how hospital service capacity influences spatial accessibility.

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来源期刊
Data in Brief
Data in Brief MULTIDISCIPLINARY SCIENCES-
CiteScore
3.10
自引率
0.00%
发文量
996
审稿时长
70 days
期刊介绍: Data in Brief provides a way for researchers to easily share and reuse each other''s datasets by publishing data articles that: -Thoroughly describe your data, facilitating reproducibility. -Make your data, which is often buried in supplementary material, easier to find. -Increase traffic towards associated research articles and data, leading to more citations. -Open up doors for new collaborations. Because you never know what data will be useful to someone else, Data in Brief welcomes submissions that describe data from all research areas.
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