Revenue Cycle Operations,
Rethought
Reduce revenue leakage across the full revenue cycle — not just claims
Revenue is lost at every stage: claims delayed by manual data assembly, deductions that go unchallenged, packages priced below their true cost, payer guidelines absorbed too late. HealthFoundry's FinOps agents work across the full revenue cycle — surfacing leakage, quantifying its financial impact, and supporting your team to act on it — while keeping humans in control of every consequential decision.
Revenue leakage occurs across three domains.
We address all three.
Most RCM programmes focus on claims submission speed. The bigger opportunity is systematically closing every channel through which revenue leaks — claim denials and deductions, packages that cost more to deliver than they reimburse, and payer guideline changes that erode margins before anyone notices.
Claims Management
The eight-stage claims lifecycle — from eligibility verification through settlement reconciliation — with agents reducing manual assembly time, query backlogs, and rejection rates.
Package Profitability
Analysing actual billing against reimbursable amounts to identify where packages are delivered at a loss — and recommending package master optimisations that improve margins without compromising care quality.
Payer Intelligence
Continuous monitoring of payer portals, scheme bulletins, and insurer notices for guideline changes — so deductions from non-absorbed updates are caught before they hit your settlement.
The Claims Lifecycle: eight stages, bottlenecks at each one
Every stage from patient registration through settlement carries a distinct failure mode. HealthFoundry agents support your team at each stage, reducing manual data assembly and surfacing exceptions for human review.
Typical Stage Bottleneck & Failure Mode
Incomplete insurance identification at admission leads to downstream coverage mismatches and delayed authorization requests.
FinOps Agent Intervention
Agent cross-references patient demographic and payer portal databases instantaneously at intake to verify active policy eligibility and pre-auth limits.
Payer guidelines change.
Agents that stay current.
For government scheme payers and large insurers, package and guideline changes are frequent — and non-absorption is directly penalised through deductions. HealthFoundry's Payer Rule Intelligence capability continuously monitors payer publication channels for changes to package definitions, documentation requirements, and coding guidelines.
When a change is detected, the agent parses it, identifies the operational delta, and surfaces a structured update for the claims team to review. Unambiguous, low-impact updates can be applied to agent configuration after human confirmation. Ambiguous changes — where the interpretation is unclear — are presented with both interpretations and their expected financial impact, for the claims manager to confirm.
Required documentation changed: Operative notes must now include explicit histopathology confirmation prior to claim submission.
Payer guideline currency is a continuous operational responsibility — one that demands ongoing attention while maintaining human decision authority.
Not every package generates a margin.
Most hospitals don't know which ones don't.
The gap between what a procedure costs to deliver and what the payer reimburses is often invisible — until it accumulates into a structural profitability problem. Our Package Profitability capability makes that gap visible, attributable, and actionable.
01. Actual billing analysis
Agent reads actual billing data across procedures, service lines, and payer categories — building a granular picture of what was charged for each episode of care and how it was reimbursed.
02. Compare with reimbursable amount
Actual cost-to-deliver is compared against the reimbursable package rate for each payer. Packages where the delta is consistently negative are identified and ranked by financial impact.
03. Review the package master
The agent maps loss-generating packages against the package master — reviewing included components, consumable assumptions, and procedure bundling — to identify origin points.
| Procedure Package | Payer Category | Avg Delivery Cost | Reimbursed Rate | Margin Delta | Status / Action |
|---|---|---|---|---|---|
| Total Knee Replacement (TKR) | Commercial Insurance | ₹ 2,45,000 | ₹ 2,80,000 | + ₹ 35,000 (+14%) | Profitable |
| Coronary Angioplasty (Single Stent) | Government Scheme | ₹ 1,28,000 | ₹ 1,12,000 | - ₹ 16,000 (-12%) | Structural Loss |
| Laparoscopic Cholecystectomy | TPA Partner | ₹ 78,000 | ₹ 85,000 | + ₹ 7,000 (+9%) | Profitable |
| Oncology Chemotherapy Cycle 3 | Corporate Insurer | ₹ 95,000 | ₹ 88,000 | - ₹ 7,000 (-7%) | Structural Loss |
Two agents covering the revenue cycle
Every agent in the platform is semi-autonomous — it reads, analyses, surfaces, and recommends. Your team retains decision authority at every consequential step.
Works across claims management and package profitability — reviewing claims against payer rules before submission, identifying patterns in deductions and rejections, and analysing actual billing data against reimbursable amounts to surface packages that are structurally unprofitable.
- Pre-submission coding validation
- Denial prediction & appeal scoring
- Query response drafting
- Actual billing vs. reimbursable analysis
- Package master review
- Optimisation recommendations
Continuously monitors package-level profitability across service lines and payer categories. Reads actual billing data, compares it to reimbursable package rates, and identifies packages where the cost-to-deliver consistently exceeds reimbursement. Recommends package master changes for clinical and finance review.
- Package-level margin analysis
- Structural loss identification
- Bundling & component review
- Profitability optimisation
- Runtime package selection support
Indicative outcomes across claims,
package profitability, and payer intelligence
Indicative ranges based on the Design phase. Actual improvement is anchored in your Audit baseline.
No two payer relationships work the same way.
A government scheme oncology claim has fundamentally different documentation requirements, authorisation logic, and portal workflows than a commercial insurer elective surgery claim. Our methodology maps each significant payer type and claim category as a distinct workflow variant, each with its own logic and requirements.
This matters because automation targeted at the wrong variant produces the wrong result. Our Outcomes-Driven Optimization Blueprint for claims starts with your specific payer mix, procedure mix, and current KPI baseline — before we configure a single agent.