Saving Lives by Better Ambulance Deployment

Tom Carchrae is the senior engineer working on Actenum's core platform work. He has been leading the development of a new way of applying Actenum's decision and optimization technologies that I find fascinating. It was inspired by the many newspaper stories about ambulances that have taken too long to arrive at the scene of emergency incidents, sometimes with tragic results. The problem is illustrated in a 2005 article in the Philadelphia City Paper: ‘Do you know how many times a week people say to me, “Hey, what the hell, I called you 20 minutes ago?” asked paramedic Lou Rosmini. “But they don't know I just had to drive 50 blocks to get to them.”’

Part of the challenge sits at the emergency control center, where dispatchers distribute Emergency Medical Services (EMS) ambulances according to unit capacities, meal periods, anticipation of future incidents, and ambulances coming off ER deliveries. Many control centers attempt to deal with the challenge by using predefined deployment plans that will tell the dispatchers in which sequence they should deploy the ambulances to various staging points within a geographic area. These plans include how many ambulances are required for coverage of the area, and where they should be deployed at various times of the day and week.

Building better operational strategies

Actenum has developed a set of technologies and tools that take the guesswork out of developing operational strategies. These tools make it easy to perform predictive analysis (better known as “what-if” analysis) to evaluate different strategies through a detailed simulation that gives you a quantifiable measure of impact. For example, the question “what is the impact on response time of adding an extra unit?” is no longer answered with a vague “better” but rather by a more tangible “improved by 30 seconds”. A more difficult question is “what do I need to do to reach an 8:59 response time?” There are many options to improve response time, such as adding more units, staging locations, altering staging location priorities, staffing schedules, meal policies, types of units, and so on. Actenum's solution searches through the many possible choices to find the best strategy to meet the required targets.

The tool combines call data, road networks, automatic vehicle locator (AVL) data, and deployment policy information, and can operate in two different modes. The first mode runs scenarios over and over while exploring different ways of running your service, while the second determines the best configuration for the ambulance service and proposes recommendations for service improvement.

Dynamic deployment decisions

Setting up the operational strategies and deployment plans is important. However, these plans are often static, and this has obvious drawbacks. For example, they do not take the real traffic or demand load at any given point into account. Experienced dispatchers learn how to make better decisions than the deployment plans would suggest. They try to anticipate incidents and make their decisions based on an understanding of the current situation, which includes consideration of the time of day, weather and traffic conditions, past call history, and population density.

This is, however, not easy, and complexity puts a heavy burden on the dispatchers. Their decisions are neither consistent, nor always very good. They can, therefore, greatly benefit from technologies and tools that support gathering and extracting information, enhance situational awareness, reason with that information, and propose decisions—especially concerning how ambulances should be dynamically deployed to minimize response time.

Actenum therefore applied its dynamic and reactive optimization technology to these challenges. The technology has been incorporated into a software application that allows an operator to quickly make plans, easily visualize the planning results, and continue making changes up to the last minute. It is expected to significantly reduce the cognitive load on dispatchers, thereby allowing them to do a better job. Better response times should result, since units are redeployed sooner and more efficiently, and also the paramedic work environment should be improved, because the system considers factors such as meal periods and workload.

Note: This software is a result of the work of a consortium consisting of Actenum Corporation, CAE Inc., Precarn Incorporated, Simon Fraser University, McGill University, and Ottawa Paramedic Services.