ArticleBMJ open2022
Dynamic accessibility by car to tertiary care emergency services in Cali, Colombia, in 2020: cross-sectional equity analyses using travel time big data from a Google API.
Article in BMJ open, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.
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Who cites it
9 citing papers in PubMed, 1 synthesis or guideline pooled it.
- AI applications in disaster governance with health approach: A scoping review.Archives of public health = Archives belges de sante publique · 2025Pooled it
- Inter-facility travel time and referral for emergency obstetric care in the 15 most populated cities of Nigeria: a spatial analysis.BMC global and public health · 2026Article
- Big data in modelling geographical accessibility to healthcare: a scoping review protocol.BMJ open · 2025Article
- Improving accessibility to radiotherapy services in Cali, Colombia: cross-sectional equity analyses using open data and big data travel times from 2020.International journal for equity in health · 2024Article
- Dynamic measurements of geographical accessibility considering traffic congestion using open data: a cross-sectional assessment for haemodialysis services in Cali, Colombia.Lancet regional health. Americas · 2024Article
- Geospatial investigations in Colombia reveal variations in the distribution of mood and psychotic disorders.Communications medicine · 2024Article
- Improving spatial accessibility to health care services in Cali, Colombia: stakeholder assessment of an innovative platform.Revista panamericana de salud publica = Pan American journal of public health · 2024Article
- A geospatial database of close-to-reality travel times to obstetric emergency care in 15 Nigerian conurbations.Scientific data · 2023Article
- Dynamic geographical accessibility assessments to improve health equity: protocol for a test case in Cali, Colombia.F1000Research · 2022Article
Corrections and comments
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Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectivesTo test a new approach to characterise accessibility to tertiary care emergency health services in urban Cali and assess the links between accessibility and sociodemographic factors relevant to health equity.
designThe impact of traffic congestion on accessibility to tertiary care emergency departments was studied with an equity perspective, using a web-based digital platform that integrated publicly available digital data, including sociodemographic characteristics of the population and places of residence with travel times. SETTING AND
participantsCali, Colombia (population 2.258 million in 2020) using geographic and sociodemographic data. The study used predicted travel times downloaded for a week in July 2020 and a week in November 2020. PRIMARY AND SECONDARY OUTCOMES: The share of the population within a 15 min journey by car from the place of residence to the tertiary care emergency department with the shortest journey (ie, 15 min accessibility rate (15mAR)) at peak-traffic congestion hours. Sociodemographic characteristics were disaggregated for equity analyses. A time-series bivariate analysis explored accessibility rates versus housing stratification.
resultsTraffic congestion sharply reduces accessibility to tertiary emergency care (eg, 15mAR was 36.8% during peak-traffic hours vs 84.4% during free-flow hours for the week of 6-12 July 2020). Traffic congestion sharply reduces accessibility to tertiary emergency care. The greatest impact fell on specific ethnic groups, people with less educational attainment and those living in low-income households or on the periphery of Cali (15mAR: 8.1% peak traffic vs 51% free-flow traffic). These populations face longer average travel times to health services than the average population.
conclusionsThese findings suggest that health services and land use planning should prioritise travel times over travel distance and integrate them into urban planning. Existing technology and data can reveal inequities by integrating sociodemographic data with accurate travel times to health services estimates, providing the basis for valuable indicators.
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