Our work for emergency medical services
We work with emergency medical services to predict how demand rates are likely to change and help providers to plan for the future. This involves using the wealth of data collected by ambulance services and delivering evidence-based solutions that enable the most effective use of resources.
Supporting future planning using simulation
When it comes to future planning, emergency medical services need to consider a wide range of competing demands and options for change. ORH supports this by building a simulation model of the service to predict the impacts of potential changes. Some of the questions we help services to address include:
- What is the optimal vehicle and staff mix to meet standards?
- Where are the optimal response locations for vehicles?
- What are the impacts of different dispatch protocols?
This video introduces our approach for emergency medical services, taking a data-led methodology to understand operational complexities. ORH’s experienced consultants ensure that the evidence-based outcomes are easily understood and support consultation with other stakeholders.
Areas of focus for emergency medical services
Emergency medical services around the world share a need to provide an appropriate response to incidents in a timely manner, often in the context of significant constraints on finance and resources. ORH works closely with clients to develop optimal strategies for meeting these challenges.
Our extensive experience in this sector allows us to evaluate performance through benchmarking and consider opportunities for change. For example, we have evaluated hub-and-spoke models in many organisations as well as different skill mixes and accompanying operating models.
When the Ambulance Response Programme (ARP) was implemented in England, ambulance services needed to understand the implications of new national response standards on performance and resourcing. We helped clients adapt to these new standards by considering the re-rostering of resources, new response locations and changes to operational tiering.
We have worked with a wide range of emergency medical services around the world, large and small, urban and rural. Some of the questions we have addressed include:
- How does the planned change of services at a hospital affect ambulance operations?
- In a rural area, what is the optimal balance between on-call and on-duty staff?
- In areas where population is expected to increase dramatically, how can the service collaborate with other providers to improve response times in the future?
In addition to consultancy work, some of our clients are keen to have access to the models that ORH typically use in-house to assess potential changes to deployments or response parameters.
We therefore provide a version of our ambulance simulation model (AmbSim) that we have set up with appropriate inputs for that service. The model enables users to evaluate the potential impacts of changes to:
- Demand by incident type and local area
- Time at scene and time at hospital
- Conveyance rates by category
- Start and finish times for shifts
Prior to handing over the model, ORH trains users at the ambulance service in how to use the software. In addition to technical instructions, we provide a series of service planning examples so that staff can apply this knowledge to answer real-world questions using the model.
Our case studies
10-year master plan for stations and vehicles
Developing a 10-year master plan for stations and vehicle deployments
Identifying options for paramedic and fire services
Future scenario planning for paramedic and fire services
Meeting national targets for ambulance response
Determine underlying capacity required to meet national ambulance targets
Ensuring equity of service in urban and rural areas
Improving the equity of response across urban and rural areas
Effective resource deployment in metopolitan areas
Deploying resources efficiently in a metropolitan ambulance service
Evaluating call handling, dispatch and triage
Comprehensive evaluation of call handling, dispatch and clinical triage
Resourcing requirements for future scenarios
Supporting the implementation of ARP through in-depth analysis and modelling