HealthShare NSW, which operates a Patient Transport Service, asked operational researchers to explore resourcing options for reducing the use of alternative service providers to significantly reduce costs.
HealthShare NSW’s planning process for its patient transport service (PTS) aims to strike a balance between the timeliness of service and the efficient utilisation of resources. It is particularly challenging to maintain this balance over a range of geographies which vary from sparsely populated, large rural areas to densely populated urban areas. In an area spanning 20,732km2 there are 12 hospitals and four bases from which the service operates.
In 2016/2017 the service undertook 200 patient transports per week with 492 vehicle hours. When the PTS system was unable facilitate all journeys, some were passed to alternative providers at great additional cost.
There are a number of other factors which needed to be considered: patients have a range of mobilities and clinical needs, so an appropriate vehicle with trained crew members must be selected to transport them. Some patients, such as children, may require to be transported with an escort, and other patients may be infectious and therefore must travel alone.
The OR team used sophisticated analysis and modelling techniques to deliver robust solutions that are evidence-based, objective and quantified. It began with studies of the resources required to undertake efficient patient transport, along with a detailed analysis of the historical journey profile, the timeliness of patient transfers against key performance indicators (KPIs) and vehicle utilisation to build a detailed picture of how the service operates. The results were used to generate a patient transport simulation model, taking into account all factors including shift patterns, vehicle type and crew mix, and the distribution and volume of patient journeys.
While some journeys were booked ahead of time, between 40 and 70% of journeys were booked on the same day as travel, requiring the model to allow for adaptation in response to these requests.
A fast ‘greedy’ algorithm was used to rapidly generate vehicle routes, which were improved using a cost function to determine which is ‘better’ – this was not just financial but also considered patient care and timeliness. The results were greatly improved efficiency in the service, leading to fewer journeys sent out to alternative providers, in turn saving costs.
The model showed there were 60 journeys per week which were given to alternative services and, by adjusting the simulation, 80% of these 60 were accommodated within the core HealthShare capacity by adding 176 vehicle hours. This additional cost in hours was far less than the costs of using alternative providers. This has greatly reduced the costs of the service overall, and led to improved service for patients.
Full article available in Impact Magazine, Spring 2018: ‘Improving Patient Transport in New South Wales’ pp42-45