How Electromed Used AI to Unite Order Intake and Sales Teams

Client Profile

  • Client Name: Electromed, Inc.
  • Industry: Durable Medical Equipment (DME) and Home Medical Equipment (HME)
  • Location: United States
  • Client Background: Electromed is a leading provider of airway clearance therapy devices. Its products require prior authorization and insurance approval, making medical documentation review a critical part of the referral workflow. A team of 20+ Patient Account Liaisons (PALs) was responsible for manually reviewing high volumes of medical records to ensure compliance with payer criteria.

Introduction

To secure insurance approvals for its medical devices, Electromed relied on intensive manual documentation review. PALs spent hours reading through lengthy medical records, searching for key insurance criteria. As AI solutions gained traction across healthcare operations, Electromed’s leadership saw an opportunity to automate this process and improve operational efficiency.

Challenge

Problem Statement

Prior to adopting Notable Systems, Electromed’s documentation review process was fully manual, labor-intensive, and prone to delays. PALs had to comb through every page of a referral packet to locate specific payer-required information.

This manual process created significant bottlenecks, requiring 20+ staff with no real-time visibility into documentation status. This created a disconnect between intake teams and sales teams, where sales representatives would visit client locations to request documentation that had already been provided or miss documents that were still needed, potentially damaging relationships with referral sources.

  • Volume Bottlenecks: Manual review limited how many referrals could be processed daily
  • High Resource Burden: 20+ staff were required to handle document intake and review
  • Accuracy Issues: Human error occasionally led to missed criteria or unnecessary documentation requests
  • Internal Friction: Sales teams were frustrated when documents were incorrectly flagged as incomplete, damaging trust with referral sources
  • Redundant Workflows: Staff had to highlight, extract, and re-enter information manually in multiple systems

"So it was just the documentation review... we have this team of 20 users that are scouring through all these medical records to find key words. It was just a painful process and it's something that we had always done, but it definitely slowed everything down in the referral process."

Our Solution

Notable Systems entered the picture after Electromed leadership when they began shopping for AI vendors. discovered the vendor at a trade show while researching AI-driven operations tools. The leadership team saw clear potential in using automation to streamline their documentation review workflows.

Objectives:

  • Reduce manual review time
  • Expand referral volume capacity
  • Improve accuracy and consistency in criteria identification
  • Align sales and reimbursement teams
  • Create a scalable review process for future growth

Rather than a disruptive overhaul, Electromed chose a thoughtful, phased approach. After evaluating three AI vendors, they selected Notable Systems and began implementation in three strategic phases.

Phase 1: Discovery and vendor evaluation with core leadership team

Phase 2: Initial rollout as assistive cover sheet tool 

Phase 3: Advanced Salesforce CRM integration 

The initial implementation featured regular meetings with a dedicated customer success manager and close collaboration with the IT team for document access and testing. At first, Electromed implemented Notable as a cover sheet resource tool to assist their team to create a feedback loop for customized and improved order accuracy.

A larger breakthrough in AI implementation came with Phase 3, when Electromed launched their Salesforce CRM integration. This advanced integration allowed Notable's structured outputs (JSON files) to automatically create and route referral opportunities based on extracted data, transforming their entire intake workflow from manual to automated.

“We've been able to take Notable to the next level. It's giving us a lot more efficiency. Before, we [used Order Intake] as a guide. It was nice to have, but now it's driving processes and automations."

Results

Electromed has already seen strong operational gains:

Operational Improvements:

  • Increased Throughput: Teams can process significantly more referrals
  • Time Savings: Staff can go straight to the relevant content (e.g., “page 6”)
  • Higher Accuracy: AI identifies and highlights critical criteria, reducing oversight
  • Workflow Automation: Salesforce now auto-generates and routes referral opportunities using extracted data (e.g., clinic, zip code)
  • Team alignment: Real-time documentation status eliminates duplicate requests and missed documents

Process Improvements:

  • Faster Reviews: Cover sheet summaries offer key data at a glance
  • Reduced Rework: Fewer unnecessary documentation requests
  • Improved Collaboration: Greater trust between reimbursement and sales teams

The success stemmed from several key factors. The phased rollout approach worked particularly well, and effective change management came through training, support, and feedback loops proved essential for overcoming the staff’s initial skepticism of AI, while Notable's technical support became a standout contributor to successful adoption.

Challenges Faced and Overcome:

  • Trust and Adoption: Early skepticism was addressed by letting staff compare AI-generated results with manual outcomes, which steadily increased confidence
  • Integration Complexity: Salesforce integration required coordination across teams, but paid off in long-term gains

“I think there was an extra level of confidence between our reimbursement staff and our sales team. Before, especially if we had a newer internal staff reviewing documents, they would maybe put a request in for additional medical records when really we had what we needed. I think that additional level of confidence in recognizing that we have what we need or that we don't... I've seen an improvement."

Key Takeaways:

  • Phased Rollout Worked: Starting with assistive features helped teams build confidence before deeper automation
  • Integration Amplifies Value: The full potential of automation was unlocked after tying the system into Salesforce
    Change Management Matters: Training, support, and feedback loops were key to overcoming skepticism
  • People + Product Success: Notable’s technical support was a standout contributor to successful adoption

Overall Impact:
Electromed successfully transitioned from a manual documentation review process to an AI-enhanced workflow. The shift enabled faster, more accurate, and more scalable operations, especially after Salesforce integration.

This improved visibility has dramatically strengthened relationships with referral sources, as sales teams can now visit clients with complete knowledge of documentation status. The reduced rework and fewer unnecessary documentation requests have rebuilt trust between reimbursement and sales teams, creating the internal alignment needed to keep reimbursements flowing.

"Not only the solution, but I just want to call out the team themselves," says Stephanie LaBelle, Senior Business Relations Manager. "Everyone we worked with at Notable, especially during this whole implementation with Salesforce has been amazing. They're so knowledgeable and go over and beyond to make sure things are working and resolving issues quickly." 

She also noted the speed of implementation: "The timeline of implementation was really fast... It was so quick and they were responsive."

Key Success Drivers:

  • Thoughtful, phased implementation
  • Strong vendor partnership
  • Effective change management
  • Strategic system integration
‍This case study demonstrates Notable Systems' ability to transform manual documentation processes in the DME/HME industry, delivering measurable improvements in operational efficiency and work volume capacity. For DME/HME organizations facing similar documentation review challenges, this implementation provides a proven roadmap for AI-powered process transformation.