Performance Home Medical runs a high-volume intake and customer service operation as a respiratory and sleep medical equipment supplier. Their Director of Intake, Ben Hauge, manages a mix of remote and on-site teams responsible for processing hundreds of incoming orders daily.
The Challenge
Before Tennr, checking for accuracy and ensuring teams were operating error-free was a slow, manual, and reactive process. They relied on internal audits, denials, and one-off reviews to catch mistakes and keep up the quality in their processes. This meant delays, training & onboarding bottlenecks, and extra staff hours to keep quality high.
Life with Tennr
Tennr’s Autopilot feature, with built-in quality control, changed that.
Performance Home Medical compared August through October 2025 to the same period in 2024 and saw an 18% increase in orders output, all while operating with 29% fewer staff members dedicated to that process than the prior year. That’s a 65% productivity increase per team member. All with the help of fully automated data entry fields.
The efficiency gains also strengthened their ability to stay responsive to referring providers, keep documentation complete, and move patients through the pipeline without delays.
“Even on a busy day, my process is current. I’m within an hour all day, every day,” said Ben Hauge, Director of Intake.
How they did it:
Cutting Workload Without Cutting Quality
When working with inbound documents and automating data entry, teams need a way to make sure that the information going into their systems is correct every time. And whether that’s an automated system doing that or a human reviewer, you want to make sure you’re getting it right every time.
Performance Home Medical needed a way to ensure they could speed through the process while maintaining the highest quality. There was no method for monitoring how teams were performing when it came to getting the right information, how data was flowing, and how often costly errors were going undetected.
Within months of using Tennr's Autopilot and Quality Control suite, Performance Home Medical was able to monitor the performance of Tennr’s ML models and the performance of their team members working with Tennr. They measured a 29% reduction in each team member’s time spent on intake, as well as an increase in data entry accuracy.
“With the amount of automation we’ve been able to flip on, the team can maintain their same KPIs, the same expectations, the same output — but from fewer people dedicated full time,” Ben shared.
With autopilot, Tennr reads their inbound documents and updates patient information in their systems, eliminating 12 data entry points in Performance Home Medical’s process. Every time an employee doesn’t need to manually review and enter that patient data, hours are saved weekly.
Their document classification queue, which feeds every downstream operation with over 17,000 inbound faxes per month, now stays current within one hour, even on days where the team processes more than 860 incoming documents.
Staff Ramp Time Cut in Half
Beyond efficiency and accuracy gains, Quality Control has also cut Performance Home Medical’s new staff hiring and training time in half.
Traditionally, Performance Home Medical spent up to 6 weeks onboarding new intake operators. With Tennr guiding new hires through workflows step-by-step, presenting the exact documentation they need to learn, and providing the guardrails to keep them on track, the onboarding time dropped over 50% to under three weeks.
“You don’t have to understand all the ins and outs to be productive. With Tennr, we’ve had people productive on their own in days,” Ben said.
Quality Control: A Clear Path to Safe Automation
Before Tennr, automation driven by a platform felt “risky”. Ben described the early automation platforms as seeming like a black box.
Autopilot in Tennr comes standard with built-in quality control tools, which give him transparent accuracy metrics, field-by-field confidence in data entry, and the ability to selectively put parts of his process on Autopilot with a click. He evaluates risk by looking at accuracy and frequency and checks whether downstream steps would be vulnerable to compounding errors.
“I like the control. I like being able to make the decision to put something on autopilot or not… we don’t need to call you as the vendor to talk about it. I can just look at what’s being accomplished, where we need reviewers, and make the decision.”