Healthcare call centers are the unsung heroes of patient access. They connect patients to providers, schedule appointments, answer questions, and serve as the first touchpoint for many seeking care. But behind the scenes, the work is far from simple. Representatives often juggle multiple systems, sift through spreadsheets, and reference static documents while trying to match patients with the right provider or location.
The process can be overwhelming. Representatives may need to determine if a provider accepts a particular insurance plan, is taking new patients, or practices close to the patient’s home. They might also need to find someone who speaks a specific language or meets unique care needs, like treating workers’ compensation cases or seeing newborns. All of this happens while the clock is ticking, and the patient is waiting on the other end of the line.
For patients, this can result in long hold times and, at worst, frustration or delayed access to care. For call center teams, it creates inefficiencies, increases the likelihood of errors, and adds to an already high-pressure environment.
It’s a puzzle—one that organizations have been trying to solve for years.
On the surface, matching patients with providers seems straightforward: gather patient preferences, cross-reference them with provider availability, and schedule the appointment. But in reality, it’s anything but simple.
Healthcare organizations often store provider and location information across a patchwork of systems—EHRs, scheduling software, spreadsheets, and even PDFs or printouts. This fragmentation forces call center representatives to toggle between platforms, manually cross-check information, and make judgment calls based on incomplete or outdated data.
The result?
The inefficiencies are substantial: according to industry data, healthcare call centers spend an average of 8 to 10 minutes per call navigating systems and sourcing data for scheduling purposes. Furthermore, 30% of scheduling errors are attributed to incomplete or outdated provider information, which can lead to unnecessary reschedules and no-shows.
This is where intelligent assistants, like an Ana assistant for provider and location matching, come into play. By streamlining access to up-to-date provider information and automating the matching process, these solutions transform how call centers operate.
Here’s how it works:
The impact of intelligent provider and location matching isn’t just about saving time (though that’s a big part of it). It’s about creating a better experience for everyone involved:
For Patients:
For Call Center Representatives:
For Organizations:
The complexity of healthcare isn’t going away anytime soon. Provider networks are growing, patient needs are becoming more diverse, and the demand for faster, more personalized service is only increasing. Intelligent assistants, like Ana for provider and location matching, offer a scalable solution to these challenges.
They don’t just make life easier for call centers—they create a ripple effect of benefits that extend to patients, providers, and the organization as a whole.
Imagine a healthcare call center where representatives no longer need to toggle between systems, manually cross-check information, or make decisions based on incomplete data. Instead, they’re equipped with a tool that consolidates everything they need into one place and delivers answers in seconds.
The result? A patient access experience that’s simple, fast, and accurate—exactly what patients expect and deserve.
The puzzle of provider and location matching may have been complex in the past, but with the right tools, it doesn’t have to be. It’s time to streamline the process, empower your teams, and make scheduling as seamless as it should be.
