Denial Management and the RCM Value Chain: Where Revenue Is Lost and Who Earns the Margin
SRF Capital Studio Research DeskFunding Intelligence, SRF Capital StudioMost claim denials are caused upstream and paid for downstream. How denial management actually works, how it differs for Indian hospitals, and why the most valuable position in the chain is the data it produces.
Summary
- Denials and deductions are rarely caused where they are noticed; most start at registration, pre-authorisation, documentation or coding, weeks before the payer says no.
- Good denial management works four loops, from prevention to root-cause fixing, and in India it has to deal with partial deductions by insurers and TPAs more than outright rejection.
- Across the value chain, margin sits with whoever owns judgement and data: documentation, complex coding, outcome-priced recovery and the payer analytics built from all of it.
A hospital finance team usually meets a denial at the end of the cycle, as a letter or portal message saying a claim will not be paid in full. The instinct is to treat it as a collections problem: appeal, chase, escalate.
That instinct is expensive. Almost every denial was caused earlier, by a missing approval, a wrong policy number, a discharge summary that did not support the bill, or a code that did not match the notes. Denial management that only appeals will keep appealing the same mistakes. This piece looks at denials through the whole value chain, which is also the clearest way to see who in the RCM industry earns the margin. For the stage definitions, see our revenue cycle management report.
Where denials come from
Kodiak Solutions, which benchmarks more than 2,100 US hospitals, put initial denials at 11.81% of claims in 2024, against about 10.2% in 2020. Its breakdown is instructive: denials tied to authorisation fell during 2024, as hospitals got better at securing approvals, while denials for medical necessity and for requests for more information rose. The fight is moving from paperwork to clinical justification.
Indian hospitals face a different mix. Outright rejection happens, but the bigger loss is partial payment. IRDAI data for 2023-24 showed insurers disallowed about ₹15,100 crore, 12.9% of the amount claimed, and repudiated another ₹10,937 crore. Disallowances arise from room-rent caps, items classed as non-payable, charges above agreed package rates, and documentation that does not support the line billed.
Where denials and deductions originate, US and India compared
| Stage where it starts | Typical US denial | Typical Indian deduction or rejection |
|---|---|---|
| Registration and eligibility | Patient not covered on date of service | Wrong policy or TPA details; sum insured exhausted |
| Pre-authorisation | No prior authorisation on file | Treatment or stay beyond the approved amount |
| Clinical documentation | Medical necessity not supported | Discharge summary or investigation reports missing |
| Coding and charge capture | Code does not match notes or payer policy | Items billed outside the package or classed non-payable |
| Submission | Late filing, format errors, duplicates | File sent after the insurer's clock or incomplete |
The table makes the core point. Denial management is not a back-office function at the end of the chain. It is the feedback system for every stage before it.
How denial management actually works
The operations that do this well run four loops, each feeding the next.
- Prevent. Check eligibility and approvals before treatment, and hold files that fail basic checks before they go out. In India this includes confirming room category and sub-limits at admission, when the patient can still choose.
- Sort. Every denial or deduction is tagged by payer, reason and stage of origin within days of arriving. Without this step there is no learning, only a queue.
- Recover. Correct and resubmit what can be corrected; appeal what was wrongly refused, with the clinical evidence the payer needs, inside the payer's deadline. Prioritise by value and by likelihood of success.
- Fix the cause. Once a month, take the three largest causes and change the process upstream: a registration field, a pre-authorisation checklist, a documentation template, a doctor briefing.
An appeal recovers one claim. A fixed cause recovers every claim that would have followed it.
In the US, most denials are recoverable with this work: Kodiak's data show only 2.8% of claims ending as final denials. In India the clock matters more than the appeal. IRDAI's May 2024 master circular requires insurers to decide cashless requests within one hour and final discharge authorisation within three, and puts the cost of delays beyond three hours on the insurer. Hospitals that can send a complete file inside those windows avoid a large share of disputes before they start. The National Health Claims Exchange, live since June 2024, will make the timing and the reasons for deductions far easier to measure.
For Indian hospitals, the arithmetic of deductions interacts with pricing and payer mix. Our piece on hospital payer mix and package rates shows how a procedure's realised price varies by payer, and why some deductions are really pricing problems.
Who earns the margin in the value chain
Seen as an industry, the revenue cycle is a chain of activities sold by different kinds of firms. Vendor presentations often put a precise margin on each. Those figures are rarely sourced, so the table below ranks the activities by what drives their economics instead.
Where pricing power sits across the RCM value chain
| Activity | What the buyer pays for | Pricing power | Main threat |
|---|---|---|---|
| Revenue cycle software platforms | The system every stage runs on | High; switching is very costly | Few; slow to change |
| Payer analytics | Prediction of how each payer will behave | High where data is proprietary | Access to data; client contract limits |
| Clinical documentation improvement | Revenue supported by better records | High; clinical skill is scarce | Talent supply |
| Denial recovery on outcome fees | Money recovered | Moderate to high | Payers automating their own reviews |
| Complex coding | Accuracy on hard cases | Moderate | AI on the easier share |
| Routine coding, billing, posting, eligibility | Volume processed | Low and falling | Automation and price competition |
The pattern is simple. Activities priced on volume are being automated and re-priced. Activities priced on judgement or outcome hold their value. And the most defensible position of all is the data layer that emerges from doing denial work at scale: knowing, payer by payer and procedure by procedure, what gets refused and what wins on appeal.
The data opportunity, and its limits
Indian RCM firms handle enormous claim volumes for US clients, which in principle makes them well placed to build payer analytics. In practice two things stand in the way.
First, contracts. Client service agreements typically limit how a vendor may use a client's claims data beyond delivering the service. Building an analytics product requires consent, de-identification and aggregation designed in from the start, and legal work most vendors have not done. Second, investment. A coding or follow-up business run for headcount margin is not naturally set up to fund a data team that will not earn revenue for years.
For domestic players the opportunity is earlier but cleaner. Indian hospitals, TPAs and insurers are standardising claims through the national exchange, and a vendor that helps hospitals track deductions by payer and reason builds the same kind of dataset, with the hospital's consent, as a by-product of the service.
What to do
- Hospital CFOs: tag every deduction and rejection by payer, reason and stage for one quarter. Then fix the top three causes before buying any tool. Put the results on the same page as the revenue cycle KPIs you already track.
- RCM founders: sell denial management with a root-cause report attached, and price at least part of it on money recovered. That is the step that moves you out of the volume-priced bottom of the table.
- Investors: ask a denial management vendor for recovery rate and time-to-recovery by payer, and for evidence that clients' initial denial or deduction rates fell over time. A vendor whose clients' denial rates never fall is being paid to keep appealing the same mistakes.
Denials will not go away; payers are automating their own reviews as fast as providers automate submissions. The advantage goes to the side that learns faster, and for hospitals and diagnostic chains, that learning starts with treating every denial as information about a stage upstream. Where this sits in the wider revenue system is covered in RevenueOS for hospitals and diagnostics.
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About the author
SRF Capital Studio Research Desk
Funding Intelligence, SRF Capital Studio
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