5.3 Understanding patient travel

Geographic accessibility is a key component of access to health services and is therefore of great interest to health system planners. Because geographical accessibility is inherently spatial, planners and researchers have often turned to GIS to try and model spatial patterns of access across different regions. A common aim of all such models is to predict the costs involved for different patients in travelling between their origin (normally their home) and their health service destination (such as a clinic or hospital). These travel costs might be measured in terms of distance, time or financial expense.

Before we can try and predict the cost of a patient’s journey we must first understand how that journey might be made. In particular, we need to know the type of transportation the patient is likely to use. Three of the most common modes of transport are considered in this object: walking, travel by private car, and travel by scheduled public transport. The relative importance of each of these will vary within countries and between different regions of the world. A greater proportion of patients may walk to health services in developing countries, for example, than in developed countries. In large cities with efficient public transport systems, more people may use a train or bus to reach health services than in rural or suburban areas where the car may predominate. It is essential to realise however that, within any population, different modes of transport will be used by different individuals, making the characterisation of patient travel a complex task.

The factors affecting the cost of different transport options must be evaluated if they are to be incorporated in a GIS model. The box below considers what factors might effect the travel time of journeys made on foot.

 
Travel times by private car will be determined by a very different set of criteria than journeys made on foot. Car journeys take place over a road network so it is important to first identify the shortest, or fastest, route between patients’ origin and destination (Haynes et al. 2006). The drive-time will be effected by factors such as the speed limits of different sections of road and infrastructure such as traffic lights and roundabouts. The amount of traffic on the road at a given time will also be important and this adds a temporal dimension to the issue, with traffic varying with the time of day, day of the week, and time of the year.

Modelling travel times for journeys made using scheduled public transport requires that a further set of factors be considered. Such journeys may involve multiple legs by bus, train, tram, ferry or other means. Each leg will have a journey time associated with it, as well as a waiting time while individuals await arrival of the transport or queue for a ticket. Journeys by public transport often involve distances that are walked on foot at the beginning and end, or in between different legs of the journey. Further complexities are added by issues of service unreliability or unavailability due to overcrowding.

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