The geography of inequalities in access to healthcare across England: the role of bus travel time variability

TL;DR

This study introduces a dynamic travel time variability (TTV) measure for healthcare access in England, revealing spatial inequalities and emphasizing the importance of real-time data for equitable healthcare accessibility analysis.

Contribution

It develops a novel TTV metric using bus timetable data, highlighting spatial-temporal patterns and limitations of static measures, and advocates for real-time data integration.

Findings

Significant urban-rural divide in TTV and travel times.

Clustering of high and low TTV regions across England.

Limitations of timetable-based TTV and potential of real-time data.

Abstract

Fair access to healthcare facilities is fundamental to achieving social equity. Traditional travel time-based accessibility measures often overlook the dynamic nature of travel times resulting from different departure times, which compromises the accuracy of these measures in reflecting the true accessibility experienced by individuals. This study examines public transport-based accessibility to healthcare facilities across England from the perspective of travel time variability (TTV). Using comprehensive bus timetable data from the Bus Open Data Service (BODS), we calculated hourly travel times from each Lower Layer Super Output Area (LSOA) to the nearest hospitals and general practices and developed a TTV metric for each LSOA and analysed its geographical inequalities across various spatial scales. Our analysis reveals notable spatial-temporal patterns of TTV and average travel times, including an urban-rural divide, clustering of high and low TTV regions, and distinct outliers. Furthermore, we explored the relationship between TTV and deprivation, categorising LSOAs into four groups based on their unique characteristics, which provides valuable insights for designing targeted interventions. Our study also highlights the limitations of using theoretical TTV derived from timetable data and emphasises the potential of using real-time operational data to capture more realistic accessibility measures. By offering a more dynamic perspective on accessibility, our findings complement existing travel time-based metrics and pave way for future research on TTV-based accessibility using real-time data. This evidence-based approach can inform efforts to "level up" public transport services, addressing geographical inequalities and promoting equitable access to essential healthcare services.