MediRoutes has launched Predictive ETAs for non-emergency medical transportation providers. The feature is available in the latest version of its dispatch software.
The tool uses machine learning and GPS trip history to estimate how long a route is likely to take, giving dispatchers a more detailed basis for scheduling than standard map-based travel times. It combines historical trip data with live traffic conditions and updates estimates as a journey progresses.
The estimates are based on GPS readings collected from provider vehicles about every five seconds. The model also accounts for variables including previous travel on the same route, time of day, and day of the week.
The approach is designed to reflect how non-emergency medical transportation journeys differ from standard driving routes. In addition to time on the road, these trips can include loading and unloading, wheelchair or stretcher securement, and waiting at facility entrances.
According to MediRoutes, it has supported more than 100 million NEMT trips since 2008, and the model becomes more accurate as more data is added.
The launch comes as transport brokers apply greater scrutiny to GPS reporting and operators face growing pressure to back on-time performance records with documented trip data. Against that backdrop, MediRoutes is positioning historical GPS information as both an operational record and a source for route planning.
Dispatchers can use the estimates when building routes and deciding whether to accept broker trips. A more precise view of expected travel times could influence whether a provider decides an additional job will fit within an existing schedule.
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