- Auxee AI for Healthcare
- Posts
- Four Pre-Denial Gaps Costing You Revenue
Four Pre-Denial Gaps Costing You Revenue
Where practices lose money before a claim is filed, and what top performers measure weekly to stop it.
Hi and happy Tuesday,
Reviews across DSOs, specialty groups, and independent practices reveal four recurring pre-submission issues: missed benefit capture, early verification, missing or mismatched authorization proofs, and manual workflows that drain staff time.
Systematically resolving these gaps improves first-pass yield, raises collections, and frees staff for patient care.
1. Benefit capture misses
Teams assume standard benefits and skip plan-specific allowances (e.g., do not record full portal benefits, alternate benefits, or frequency resets).
Quick audit:
Audit the last 60 days of not covered determinations for perio and major services
Re-verify in the portal and record alternate benefits, frequency limits, and reset dates in the chart
Attach a portal screenshot to the encounter and select the paid code on the claim
Metric to own: Benefit capture before visit. Target above 95%.
Care is approved, but the proof is not attached, codes do not match the approval, or dates fall outside the window.
Checklist to standardize:
Approval PDF attached to the chart
Authorization number in claim notes
Approved codes mirrored on the claim
Dates inside the authorization window
The silent up-code opportunity:
Procedure Type | Without Pre-Auth Documentation | With Pre-Auth Attached | Revenue Gap |
Periodontal scaling D4341 (per quadrant) | $180 | $245 | $65 |
Implant placement D6010 | $1,200 | $1,650 | $450 |
Orthodontic treatment | $3,800 | $4,500 | $700 |
Metric to own: Percent of high-value claims with proof attached. Target 100 percent.
3. Scheduling and verification timing
Verification is done early. The waiting period expires later. Treatment occurs before expiry. The claim is ineligible.
Operating rule
For major services, schedule at least seven days after the waiting period expiry. If earlier care is clinically necessary, collect payment in advance and queue the claim for the eligibility date.
Metric to own: Waiting-period scheduling compliance. Target 100%.
4. Labor inefficiency that suppresses throughput
Manual verification, benefit checks, and pre-auth tracking consume hours that could be used for billable care.
How to model it
Measure minutes per verification by case type
Convert time saved into additional cases per month using your average case value
Track denial rate and days to submission before and after
Staff time recovery matrix:
Task | Manual time | Automated time | Hours saved per month | Revenue opportunity per month |
Insurance verification | 45 min × 80 cases | 10 min × 80 cases | 46.7 | $11,680 |
Benefit eligibility checks | 20 min × 400 patients | 3 min × 400 patients | 113.3 | $28,325 |
Pre-authorization tracking | 30 min × 40 cases | 5 min × 40 cases | 16.7 | $4,175 |
TOTAL | 176.7 | $44,180 |
Metrics to own: Average verification time under 15 minutes for complex cases. Days to submission under 45 days.
Exemplifying a successful case study

Key takeaway
Prevent losses before submission. Capture benefits at scheduling, attach proof on every high-value claim, enforce a seven-day eligibility buffer, and track four weekly metrics. Do these consistently and denial rates fall, collections rise, and staff time converts into billable care.
See how much you could recover in 30 days
Book a 20-minute demo and we’ll model your pre-denial revenue gap using your own metrics.
Next week, I will cover the 8 AI building blocks every practice needs to future-proof revenue.
See you next Tuesday,
Dino Gane-Palmer
![]() Dino Gane-Palmer | About the Author Dino Gane-Palmer is the founder of Auxee and CEO of PreScouter, an Inc. 5000–recognized innovation consultancy that helps Fortune 500 companies and global organizations capitalize on new markets and emerging technologies. He launched PreScouter while earning his MBA at Kellogg and later founded Auxee to help teams use AI to tackle complex, research-heavy workflows. His work has supported decisions at some of the world’s leading healthcare, manufacturing, and consumer brands. Dino is also the author of the best-selling book Do More With Less: The AI Playbook, a practical guide to applying AI where it matters most. |
