Case Study

How MGA Converts Referrals in Minutes Instead of Hours

Ensuring patients receive high-quality homecare that meets their needs

About MGA

Ensuring patients receive high-quality homecare that meets their needs

MGA Homecare has been providing high-quality and personalized homecare with a wide range of healthcare personnel including Registered Nurses, Licensed Health Aides, and Occupational Therapists for over a decade. Headquartered in Arizona with healthcare staff serving across Texas, Colorado, North Carolina, Tennessee, and Washington, MGA is rapidly growing and expanding into new markets. With this growth came the challenge of processing the increasing volume of patient referrals and associated documentation needed to get MGA’s healthcare professionals into patient homes as quickly as possible.

“This is a game changer. It relieves our teams of the pressure of when we get several referrals back to back.”
—Nina Boulay, Senior Director of Intake

The Challenge

Back-to-back referrals from all over the place

Before working with Tennr, MGA employees could expect to spend hours manually entering patient referrals, which often arrived back-to-back from all over the place. In one afternoon, an MGA employee received seven referrals from hospitals looking for a variety of different homecare disciplines. Entering these referrals and then parsing through the available MGA healthcare professionals to assign to patients was proving to be a tedious and stressful task that required multiple employees to handle.

Aside from bogging employees down, the increased referral load strained MGA’s relationships with their network of hospitals; hospital referrals in particular were often unclear, confusing, and took extra time to sort through.

“We get referrals from all over the place, like hospitals… They drag things down, they're in cursive, and half the time we can't read it and they can't really figure out what it is that they're looking for because they're not clear.”

Not only did MGA need to find a way to more effectively process referrals and make sure they had the right documentation in place, they needed a tool that could automate entries within the first two hours of receiving the referral while still maintaining accuracy, reduce human error, and increase productivity across the board for its clerical staff.

Implementing Tennr

Introducing MGA’s new referral intake worker

The integration of Tennr into MGA's EMR system was smooth and adaptable to the intricacies of the referral intake team's current processes, enabling MGA to retain its processes without the need for any migrations. With Tennr’s help, employees were able to eliminate backlog referrals and have confidence that referrals were entered quickly and accurately.

“The data returned is accurate to a T. I don't worry about it. In fact, there's times where I’m like, ‘I can't find the type of referral this is,’ but clearly the system does. It can read the referral better than I can.”

- Nina Boulay, Senior Director of Intake