15–20%
Initial PA denial rate for elective surgery
Prior authorization · Elective surgery · India
AI for Prior Authorization
Built for hospital revenue-cycle teams, TPAs, and surgical planners — to drive more PA acceptances, fewer denials, and faster elective surgery clearances.
The pain is measurable, recurring, and tied directly to hospital revenue
₹2 Cr
Annual revenue leakage per ₹100 Cr hospital
6%
Last-minute OT cancellations from PA delays
₹1.5–2.5K
Administrative cost per denial appeal
Highest-impact specialties
OrthopedicsOphthalmologyGeneral surgeryNeurologyOncologyChronic careOrthopedicsOphthalmologyGeneral surgeryNeurologyOncologyChronic care
What is NeMo?
Prior authorization, automated end to end
NeMo automates prior authorizations for elective surgery. Our AI agent, Stitch, covers the insurance workflow from clinical records to insurer-ready submission - helping hospitals get more PA acceptances.
Instead of doctors, billing teams, and TPAs manually assembling fragmented reports, NeMo structures patient information into clear clinical reasoning aligned with insurer requirements.
The core insight: hospitals do not just have a medical problem - they have a workflow problem. Most denials are documentation and underwriting-translation failures, not purely clinical ones.
End-to-end workflow
From fragmented records to insurer-ready prior auth
Hospital records
Notes, imaging, labs, prescriptions — scattered across systems
Stitch analyses
Clinical basis, conservative treatment history, policy alignment
Insurer-ready package
Medical necessity, attachments, room-rent & coding checks
PA submitted
Fewer denials, faster clearances, less admin rework
Knee replacement · Case #PA-2841Ready to submit
12 evidence points mapped · 2 gaps resolved · Denial risk low
The problem
Elective surgery sits in a gray zone insurers exploit
A treatment may be medically valid and still get delayed because evidence is missing, notes are poorly structured, or insurer criteria are never explicitly addressed.
Insurer bias toward rejection
Elective procedures face greater scrutiny — classified as avoidable, cosmetic, or non-essential. Life-saving emergencies get approved; knee replacements and cataracts wait.
Missing medical necessity proof
Surgeons know the patient needs surgery. Insurers need structured evidence: failed conservative treatment, imaging, mobility impairment, and policy-compliant estimates.
Fragmented manual workflows
Teams collect scans from multiple systems, fill insurer-specific forms, match ICD codes, and chase clarifications — failure points at every step.
No universal insurer logic
Every TPA uses different forms, attachment rules, room-rent caps, and PED thresholds. Hospital desks operate on memory and spreadsheets, not systems.
Procedures under heightened scrutiny
Total knee & hip replacementSpinal fusionCataract & LASIKCholecystectomy & hernia repairCosmetic & reconstructive surgery
The data
Measurable pain across revenue cycles
Denial rate
15–20%
Overall PA denial rate for planned or elective surgeries on initial submission across India.
Source: Indian Journal of Medical Sciences
Revenue leakage
2%
Of gross annual patient revenue lost combatting denied PA elective cases — ₹2 Crores per ₹100 Crores for a mid-sized private hospital.
Source: PubMed
OT cancellations
6%
Last-minute elective surgery cancellations on procedure day from unresolved financial clearances — perishable OT revenue lost entirely.
Source: Industry estimates
Appeal overhead
₹1.5–2.5K
Operational cost per claim to investigate rejection, retrieve scans, update notes, and resubmit — draining billing team bandwidth.
Source: Operational benchmarks
Most common denial reasons
- 1Waiting period exclusions
- 2Missing clinical documentation
- 3Lack of medical necessity
- 4Policy limits & room rent caps
- 5Undisclosed pre-existing diseases
How NeMo solves it
An intelligence layer between hospital records and insurer requirements
NeMo treats prior authorization as an underwriting optimization problem — not administrative paperwork.
- 01
Extract clinical evidence
Pull patient information from physician notes, radiology, prescriptions, labs, and discharge summaries — automatically.
- 02
Break down the case
Decompose treatment into sub-questions insurers ask, then search hospital records for answers to each.
- 03
Map insurer logic
Align documentation with policy requirements, waiting periods, room-rent caps, and medical necessity frameworks.
- 04
Flag before submission
Detect missing evidence, weak justification, and denial risk before the PA ever leaves your desk.
- 05
Generate insurer-ready docs
Structure clinical reasoning into submissions TPAs can evaluate consistently — not just completed forms.
- 06
Support appeals
When denied, map rejection reasoning to missing evidence and draft structured appeals for your team to review.
Meet Stitch
Your AI agent for the insurance workflow
Stitch covers prior authorization end to end — from unstructured clinical data to structured, insurer-ready documentation that revenue-cycle teams can submit with confidence.
In a knee replacement case, Stitch does not stop at the diagnosis. It analyses duration of pain, failed physiotherapy, medication history, mobility deterioration, imaging findings, and prior interventions — then translates that into underwriting language.
Denial risk
15–20%
Initial PA denial rate for elective surgery submissions across India.
Revenue impact
₹2 Cr
Annual leakage per ₹100 Cr hospital revenue from denied elective PAs.
Stitch output
PA ready
Medical necessity packaged · 3 gaps flagged · Appeal draft on standby.
stitch.run()
- 1Ingest records from EMR, PDFs, and imaging
- 2Identify clinical basis for treatment
- 3Score denial probability pre-submission
- 4Package insurer-specific submission
- 5Monitor TPA responses and clarifications
- 6Generate appeal drafts on rejection
Example output
Medical necessity package ready · 3 gaps flagged · Denial risk: medium
The technology
Built for underwriting translation, not form-filling
NeMo combines clinical AI with policy interpretation to understand why a claim may be denied — and what evidence is missing — before submission and after rejection.
- Clinical document intelligence
- Multimodal medical data extraction
- Policy interpretation systems
- Denial-risk prediction models
- Workflow orchestration
- Insurer-specific submission optimization
Why this problem exists
Insurance minimizes risk
PA exists as a filtering layer before expensive treatments. Elective surgery gives insurers time to investigate — unlike emergencies with legal and reputational risk.
Workflows stay manual
Forms, codes, attachments, and clarifications create failure points: missing scans, vague notes, wrong packages, absent conservative-treatment history.
Hospitals optimize for throughput
Clinical teams deliver care; insurers need structured proof. The translation layer between medicine and underwriting is weak.
Get started
Stop losing revenue to preventable denials
NeMo is built for Indian hospitals navigating elective surgery prior authorization. Book a demo to see Stitch on your workflow.
Data projections based on Indian Journal of Medical Sciences, PubMed, and operational benchmarks. IRDAI exact figures unavailable due to proprietary hospital data.