Evaluation of inter-facility medical transport journey times in Southeastern British Columbia
(2016) In Master Thesis in Geographical Information Science GISM01 20161Dept of Physical Geography and Ecosystem Science
- Abstract
- Very sick patients who need specialized health services often require transport from their community to a regional facility that is appropriately resourced to provide definitive care for their condition. This is particularly important for people living in rural and remote areas but can be challenging due to long distances, mountainous terrain and inclement weather.
The purpose of this research was to improve health service delivery to rural communities within the study area by identifying whether or not there were inter-facility medical transport routes within the study area with highly variable or unexpectedly long journey times. Select transport characteristics were examined to further inform decision making related to acute... (More) - Very sick patients who need specialized health services often require transport from their community to a regional facility that is appropriately resourced to provide definitive care for their condition. This is particularly important for people living in rural and remote areas but can be challenging due to long distances, mountainous terrain and inclement weather.
The purpose of this research was to improve health service delivery to rural communities within the study area by identifying whether or not there were inter-facility medical transport routes within the study area with highly variable or unexpectedly long journey times. Select transport characteristics were examined to further inform decision making related to acute inter-facility transport within the study area.
The medical records of 418 high acuity patient transports within Southeastern British Columbia were reviewed in order to capture information about ‘observed’ transport times, locations, and other transport characteristics. A geographic network analysis of each route identified within the study dataset was conducted in order to estimate ‘expected’ transport times. These expected transport times, in addition to GoogleMap time estimates, were compared to observed transport times to determine areas of possible concern within the transport network. A multiple regression analysis was conducted to identify predictors of transport times.
Observed transport times in the study dataset were generally found to be within a statistically acceptable range of expected transport time estimates. The only transports with significantly longer than expected journey times were due to ‘meets’ in transport. Additional factors such as patients’ clinical categories, mode of transport, and max elevation en-route were predictive of transport times within the study context. (Less) - Popular Abstract
- When someone becomes very ill in a small town it can be difficult for them to stay in their community and get all of the medical attention they need. In some cases, this person must be taken to a larger center in order to get specialized treatment for their condition.
If a sick person needs to go to a larger hospital (e.g., one that can provide specialized care), how do they get there? Often an ambulance will drive them—but in the Southeastern corner of British Columbia, the distance between any given community and a larger hospital can be very long, up to 300km. Aside from long distances, poor weather conditions, construction, or traffic congestion can all make it hard to drive between communities in quickly; unfortunately, when a... (More) - When someone becomes very ill in a small town it can be difficult for them to stay in their community and get all of the medical attention they need. In some cases, this person must be taken to a larger center in order to get specialized treatment for their condition.
If a sick person needs to go to a larger hospital (e.g., one that can provide specialized care), how do they get there? Often an ambulance will drive them—but in the Southeastern corner of British Columbia, the distance between any given community and a larger hospital can be very long, up to 300km. Aside from long distances, poor weather conditions, construction, or traffic congestion can all make it hard to drive between communities in quickly; unfortunately, when a patient is very sick, time matters!
This project looked at the different driving routes ambulances have taken to bring sick patients to regional hospitals. This was done with three questions in mind: 1) Are any of these routes unexpectedly slow or fast (if so, which ones)?; 2) Do longer driving distances make it more difficult to predict transport times due to greater variability in drive times; 3) What factors might help to predict drive times between communities?
By looking at the paper documentation from ambulances and hospitals in the region, ambulance drive times were calculated. These times were compared to drive time estimates from GoogleMaps as well as from the results of a geographic analysis of road networks. When actual ambulance drive times were compared to the time estimates, it was found that ambulance drive times where within an acceptable range across the board. The only exception to this was when two ambulances needed to meet at a mid-way point in the trip in order to bring the patient all the way to their final destination. These ‘meets’ increased transport times by an average of 42 minutes. Other factors like clinical category of the patient (e.g., type of illness), the maximum elevation of the route, and the mode of transport were also found to influence transport times. (Less)
Please use this url to cite or link to this publication:
http://lup.lub.lu.se/student-papers/record/8881848
- author
- Buhler, Holly LU
- supervisor
- organization
- alternative title
- Medical transport in Southeastern British Columbia
- course
- GISM01 20161
- year
- 2016
- type
- H2 - Master's Degree (Two Years)
- subject
- keywords
- high acuity, medical transport, patient transport, inter-facility transport, network analysis, geography, GIS, road network, rural health, emergency medical services
- publication/series
- Master Thesis in Geographical Information Science
- report number
- 52
- language
- English
- additional info
- Co-Supervisor: Brian Klinkenberg, University of British Columbia
- id
- 8881848
- date added to LUP
- 2016-06-16 11:03:46
- date last changed
- 2018-01-01 04:09:14
@misc{8881848,
abstract = {{Very sick patients who need specialized health services often require transport from their community to a regional facility that is appropriately resourced to provide definitive care for their condition. This is particularly important for people living in rural and remote areas but can be challenging due to long distances, mountainous terrain and inclement weather.
The purpose of this research was to improve health service delivery to rural communities within the study area by identifying whether or not there were inter-facility medical transport routes within the study area with highly variable or unexpectedly long journey times. Select transport characteristics were examined to further inform decision making related to acute inter-facility transport within the study area.
The medical records of 418 high acuity patient transports within Southeastern British Columbia were reviewed in order to capture information about ‘observed’ transport times, locations, and other transport characteristics. A geographic network analysis of each route identified within the study dataset was conducted in order to estimate ‘expected’ transport times. These expected transport times, in addition to GoogleMap time estimates, were compared to observed transport times to determine areas of possible concern within the transport network. A multiple regression analysis was conducted to identify predictors of transport times.
Observed transport times in the study dataset were generally found to be within a statistically acceptable range of expected transport time estimates. The only transports with significantly longer than expected journey times were due to ‘meets’ in transport. Additional factors such as patients’ clinical categories, mode of transport, and max elevation en-route were predictive of transport times within the study context.}},
author = {{Buhler, Holly}},
language = {{eng}},
note = {{Student Paper}},
series = {{Master Thesis in Geographical Information Science}},
title = {{Evaluation of inter-facility medical transport journey times in Southeastern British Columbia}},
year = {{2016}},
}