ArticleInternational journal of health geographics2012
A validation of ground ambulance pre-hospital times modeled using geographic information systems.
Article in International journal of health geographics, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
15 citing papers in PubMed, 48 citations in OpenAlex.
- Modeling IN out-of-hospital emergency medical services-a scoping review of approaches and applications.Frontiers in public health · 2026Article
- Key challenges in prehospital and emergency care in Indonesia and Malaysia: a survey of frontline clinicians.BMC research notes · 2024Article
- Effect of urgency level on prehospital emergency transport times: a natural experiment.Internal and emergency medicine · 2024Article
- Identifying the vulnerable regions of emergency medical services based on the three-stage of accessibility: a case study in Xi'an, China.International journal for equity in health · 2022Article
- Geographic barriers to establishing a successful hospital referral system in rural Madagascar.BMJ global health · 2021Article
- How prepared is Mozambique to treat COVID-19 patients? A new approach for estimating oxygen service availability, oxygen treatment capacity, and population access to oxygen-ready treatment facilities.International journal for equity in health · 2021Article
- Article
- Validating the Global Surgery Geographical Accessibility Indicator: Differences in Modeled Versus Patient-Reported Travel Times.World journal of surgery · 2020Article
- Multi-Institutional Multidisciplinary Injury Mortality Investigation in the Civilian Pre-Hospital Environment (MIMIC): a methodology for reliably measuring prehospital time and distance to definitive care.Trauma surgery & acute care open · 2019Review
- Association Between Early Intravenous Fluids Provided by Paramedics and Subsequent In-Hospital Mortality Among Patients With Sepsis.JAMA network open · 2018Article
- Expanding the impact of a longstanding Canadian cardiac registry through data linkage: challenges and opportunities.International journal of population data science · 2018Article
- Geographic Information System (GIS) capabilities in traffic accident information management: a qualitative approach.Electronic physician · 2017Article
- Article
- Geographic information system data from ambulances applied in the emergency department: effects on patient reception.Scandinavian journal of trauma, resuscitation and emergency medicine · 2016Article
- Evolution of research in health geographics through the International Journal of Health Geographics (2002-2015).International journal of health geographics · 2016Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundEvaluating geographic access to health services often requires determining the patient travel time to a specified service. For urgent care, many research studies have modeled patient pre-hospital time by ground emergency medical services (EMS) using geographic information systems (GIS). The purpose of this study was to determine if the modeling assumptions proposed through prior United States (US) studies are valid in a non-US context, and to use the resulting information to provide revised recommendations for modeling travel time using GIS in the absence of actual EMS trip data.
methodsThe study sample contained all emergency adult patient trips within the Calgary area for 2006. Each record included four components of pre-hospital time (activation, response, on-scene and transport interval). The actual activation and on-scene intervals were compared with those used in published models. The transport interval was calculated within GIS using the Network Analyst extension of Esri ArcGIS 10.0 and the response interval was derived using previously established methods. These GIS derived transport and response intervals were compared with the actual times using descriptive methods. We used the information acquired through the analysis of the EMS trip data to create an updated model that could be used to estimate travel time in the absence of actual EMS trip records.
resultsThere were 29,765 complete EMS records for scene locations inside the city and 529 outside. The actual median on-scene intervals were longer than the average previously reported by 7-8 minutes. Actual EMS pre-hospital times across our study area were significantly higher than the estimated times modeled using GIS and the original travel time assumptions. Our updated model, although still underestimating the total pre-hospital time, more accurately represents the true pre-hospital time in our study area.
conclusionsThe widespread use of generalized EMS pre-hospital time assumptions based on US data may not be appropriate in a non-US context. The preference for researchers should be to use actual EMS trip records from the proposed research study area. In the absence of EMS trip data researchers should determine which modeling assumptions more accurately reflect the EMS protocols across their study area.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.