What Your Revenue Cycle Team Does 100 Times a Day That Should’ve Been Automated Yesterday

Let’s face it: most RCM teams are quietly drowning in a sea of repetitive work. Eligibility checks. Fax follow-ups. Manual data entry. Status calls. Copy-paste chaos.

The scary part? A huge chunk of it is invisible overhead. It’s not tracked. It’s not optimized. It’s just... expected.

At Nanonets, we work with RCM leaders across specialties — from orthopedics to behavioral health. And here’s what we’ve learned:

Your team is doing the same 5-10 tasks hundreds of times a week. Each one is a perfect candidate for automation.

This article breaks down the top repeat offenders in revenue cycle workflows — and how AI agents can take them off your team’s plate, fast.

1. Insurance Eligibility Checks

Manual workflow:

• Login to payer portal
• Enter patient DOB, name, insurance ID
• Download PDF or screenshot
• Copy data into EHR or spreadsheet

Average time: ~4 minutes per patient Volume: 100s of checks per day at mid-sized practices

The problem:

• Slow and error-prone
• Limited batch processing
• High risk of missed coverage flags

How to automate: Nanonets AI agents integrate with clearinghouses or payer APIs to:

• Auto-extract coverage details
• Populate EHR fields
• Flag inactive plans or out-of-network benefits

"We went from 6 FTEs doing eligibility to 1 AI agent running 24/7."
— Director of Rev Cycle, Behavioral Health Group (8 states)

2. Chasing Down Prior Authorization Status

Manual workflow:

• Log into payer portal (or worse, call)
• Search auth request by member ID
• Manually document status updates

Average time: 5–10 minutes Volume: 20–30 per day per staffer

The problem:

• Wasted time on hold or navigating portals
• No audit trail of follow-up efforts
• Re-submissions often delayed

How to automate: Nanonets AI agents:

• Log into portals securely
• Scrape auth status
• Update EHR and billing queue
• Trigger alerts for denied or delayed auths

3. Referral Intake & Data Entry

Manual workflow:

• Receive fax/email
• Download attached referral
• Open PDF and enter data into EHR manually

Average time: 7–10 minutes Volume: 30–50 per day in busy practices

The problem:

• Delays in scheduling
• Typos and missed fields
• No pipeline visibility

How to automate:

• OCR-powered AI reads incoming faxes/emails
• Extracts patient demographics, referring provider, reason for visit
• Creates referral records in EHR automatically

"Our average time from referral to first contact dropped by 48 hours."
— VP Ops, Multispecialty Clinic (Texas)

4. Faxing and Uploading Medical Records

Manual workflow:

• Receive request (e.g., for prior auth)
• Print or download relevant records
• Fax/upload to payer
• Wait and re-check for confirmation

Average time: 10–15 minutes

The problem:

• Fax machines fail
• Upload portals have file type restrictions
• No audit trail or confirmation

How to automate:

• AI pulls relevant documents from EHR
• Matches to payer criteria
• Uploads automatically to the correct portal (or sends secure email/fax)

5. Rechecking Claim Statuses

Manual workflow:

• Access clearinghouse or payer portal
• Search for claim by DOS/member ID
• Download status reports
• Update spreadsheet or practice management system

Average time: 3–5 minutes per claim Volume: 100s per week

The problem:

• Claims slip through the cracks
• Denials often caught too late

How to automate:

• Agent checks status in real-time
• Flags denials or underpayments
• Generates appeals automatically (in certain cases)

6. Appointment Scheduling Follow-ups

Manual workflow:

• Call patient
• Leave voicemail
• Repeat

Average attempts: 3 per patient Contact rate: ~30–40%

The problem:

• Time sink for front-desk teams
• High no-show risk when scheduling is delayed

How to automate:

• AI voice agent calls patients with available time slots
• Confirms DOB and reason
• Books appointment via scheduling API

The Hidden Cost of Manual Work

Every task above seems small. But across hundreds of patients a week, the numbers add up fast:

• Time wasted: 40–60 hours/week per team
• Revenue leakage: Delayed scheduling, missed auths, unverified insurance = $100k+/year lost
• Burnout risk: Staff turnover is 30%+ in many RCM teams

Why Now Is the Time to Automate

AI has finally reached the point where:

• It’s accurate enough to handle messy faxes
• It’s secure enough for HIPAA workflows
• It’s cheap enough to run 24/7

At Nanonets, we don’t just do OCR. We deploy specialized AI agents for:

• Patient intake
• Insurance eligibility
• Prior auth tracking
• Fax triage
• Appointment scheduling

All integrated with your EHRs (like athena, Nextech, eClinicalWorks) and clearinghouses.

TL;DR

If your team is still manually:

• Checking eligibility
• Re-keying referrals
• Chasing down auths
• Faxing records

...you’re doing work a machine should do.

Let your team focus on exceptions. Let the AI handle the rest.

Want to see what this looks like in your workflows?
[Book a demo with Nanonets RCM – No sales fluff, just real automation.]

Sources:

• MGMA Stat poll: "What slows your revenue cycle down the most?" (2023)
• HFMA: "Staffing shortages and manual processes remain top RCM challenges"
• Nanonets internal benchmark data (2024)