Optimizing mobile dentistry
A University of Missouri engineer recently helped develop a model to aid a Montana non-profit interested in establishing a potential mobile dentistry program.
Ron McGarvey, assistant professor of Industrial and Manufacturing Systems Engineering, worked alongside Andreas Thorsen of Montana State University on the project. The corresponding paper, “Efficient frontiers in a frontier state: Viability of mobile dentistry services in rural areas,” recently was published in the European Journal of Operational Research.
They looked at a five-county area in rural Montana that serves as a potential coverage area for Community Health Partners (CHP), a community health center that serves low-income and underserved patients. Thorsen gathered preliminary information from CHP, and using that information and census data, he and McGarvey worked to build an optimization model that CHP could use to make decisions on the locations and frequency of care for the mobile dentistry service.
“They had an interest in fairness and access to service,” McGarvey said. “but they were unsure about the cost of all this. They would like everybody to have service, but there’s a challenge.
“If all they were concerned about was cost, you would just park the truck in the most attractive place and serve there every day of the week, but that’s not what they want to do. The model is focused on getting the most people at the least cost. What we had to do here is add constraints to trick the model, in a sense, into providing a proportional level of visits to different sites.”
The model also takes into account the possibility of a two-day, overnight stay, as well as allowing for results based on a three-month on, three-month off mode of service, which allows CHP to work around difficult winter weather in Montana should it choose.
With the model created, CHP stakeholders can use it to decide how many visits they make and locations they can service based on how much funding they receive. Depending on what the organization values most, it can use the model to find an optimal schedule.
“We can’t tell them which to pick, but we can say that based on the relative importance they place on the different metrics, the model can identify the best course of action to follow,” McGarvey said.
The project was a reunion of sorts for Thorsen and McGarvey. McGarvey mentored Thorsen when the latter was an Ph.D. student intern with McGarvey’s former employer, RAND Corporation. And it proved to be a great opportunity to impact lives for the better.
“Knowing that the results are going to help CHP make decisions that will help improve people’s lives is rewarding,” he explained.