Five Myths About Healthcare RCM and Medical Coding in India
SRF Capital Studio Research DeskFunding Intelligence, SRF Capital StudioMost of what founders, investors and hospital managers believe about medical coding and RCM in India is a decade out of date. Here are five beliefs that cost real money.
Summary
- Revenue cycle management is far wider than billing, and the coding and documentation work at its centre decides how much of a hospital's revenue is actually paid.
- AI is taking routine coding hours, not the judgement-heavy work; offshore quality problems are mostly trust problems; and US complexity favours specialists.
- The costliest myth is the newest: that Indian hospitals can adopt the US coding playbook, when their losses come from documentation, pre-authorisation and TPA deductions.
Medical coding in India employs a very large workforce, most of it serving US hospitals, and almost nobody outside the industry understands what that workforce does. The misunderstanding is expensive. It leads founders to under-price their firms, investors to discount them, and Indian hospitals to buy the wrong fixes.
Five beliefs do most of the damage. For the full picture of how the revenue cycle works, start with our sector report on revenue cycle management.
Myth 1: RCM is medical billing with a longer name
Billing is one task: assembling a claim and sending it. Revenue cycle management is everything that decides whether that claim is paid in full. That includes checking cover before treatment, recording every charge, making sure the doctor's notes support the diagnosis, choosing the right codes, and fighting the payer when it refuses.
The difference shows up in money. Take a patient admitted with pneumonia whose notes also show signs of sepsis. If the doctor documents only pneumonia, the case is coded and paid as a respiratory infection. If a documentation specialist spots the gap and queries the doctor, and the doctor confirms sepsis, the case moves to a diagnosis group that pays substantially more. Nothing about the treatment changed. The hospital was simply paid for what it did.
That work, clinical documentation improvement, needs nursing or clinical training, knowledge of coding guidelines and the confidence to question a doctor. A firm that calls itself a "medical billing company" signals to buyers that it does none of it, and prices itself accordingly.
Calling yourself a billing company tells the buyer you do the cheapest part of the job.
Myth 2: AI will end medical coding jobs in India within a few years
People have predicted this for close to a decade. What has happened instead is more specific, and more useful to understand.
Software that reads clinical notes and suggests codes now handles a large share of simple outpatient work well: a single diagnosis, a routine procedure, a clean note. Clients know this, and they are asking vendors to pass the savings through. Routine coding billed per chart will get cheaper, and firms dependent on it will shrink.
The work that holds up is different in kind. Inpatient cases with several interacting conditions, oncology and cardiology coding, documentation queries, and appeals that depend on a particular payer's habits all need someone to reason about clinical facts and ambiguous rules. Coding guidance itself changes every quarter through the American Hospital Association's Coding Clinic, and applying it to edge cases is interpretive work.
- What AI takes: high-volume, low-complexity outpatient coding; first-pass claim checks; sorting denials by type.
- What AI speeds up: documentation reviews, denial prediction, drafting appeal letters for a human to finish.
- What still needs people: complex inpatient coding, physician queries, payer-specific appeal strategy, coding audits.
The right response is to automate the first list deliberately, move trained people into the third, and price the third on outcomes. A firm that does this ends up with fewer coders and better margins. A firm that resists ends up with the same number of coders and falling prices.
Myth 3: offshore means lower quality
This was a fair worry twenty years ago. Today the quality gap, where it exists, is usually a gap in proof rather than in performance.
A US hospital finance head hiring an Indian vendor is handing her most sensitive financial process to people she will rarely meet. What she needs is evidence she can check without flying to Chennai: live dashboards of accuracy and turnaround, independent audits of coding samples, a named client lead in her time zone, and security certifications her compliance team recognises. HITRUST CSF certification is among those US health systems most commonly ask for.
None of these makes a coder more accurate. All of them make accuracy visible. Firms that invest in them win contracts that equally capable competitors lose, and the lesson for a founder is to budget for proof as seriously as for delivery.
Myth 4: the US system is too complex to run from India
The US payer system is complicated: commercial insurers, Medicare, Medicaid, Medicare Advantage, each with its own rules, varying by state and contract, and changing every year. Kodiak Solutions found 11.81% of US hospital claims were initially denied in 2024, and only 2.8% were finally lost. Most of the difference was recovered by people who understood the rules.
That complexity is an argument for specialist outsourcing, not against it. A US hospital's in-house team has to know a little about every payer and every specialty. An Indian firm that concentrates on one payer segment, one specialty or one function can know far more about it than any single hospital could afford to.
Where Indian firms do fall short, it is usually because they run the work generically, rotating staff across clients and payers without building depth. The fix is organisational, not geographic.
The scale is already there to do this. The largest Indian operators employ tens of thousands of coders and analysts across several countries, as our piece on healthcare BPO in India shows. What separates them from smaller firms is less headcount than the discipline of assigning people to the same payers and specialties for years, so that knowledge builds up rather than walking out with each rotation.
Myth 5: Indian hospitals can copy the US coding playbook
This is the newest myth, and the one we see costing domestic healthtech founders the most time.
Indian hospitals are often paid through package rates, under government schemes and many insurer tie-ups,, with itemised billing for the rest. Coding accuracy matters, but the money is usually lost elsewhere: treatment given before pre-authorisation, documents missing at discharge, room-rent and consumable deductions by TPAs, and claims that miss the insurer's clock. IRDAI's May 2024 rules give insurers one hour to decide a cashless request and three hours for final discharge authorisation, which makes speed of documentation a revenue issue.
A domestic RCM product built around coding productivity will struggle. One built around pre-authorisation, discharge documentation and deduction tracking by payer will find buyers, because it attacks the losses Indian hospital finance teams actually see. Our guide to denial management sets out how those losses map to each stage.
What to do with this
- If you run a medical coding firm in India: stop describing yourself by your cheapest service. Report revenue by service line, move trained staff toward documentation and complex coding, and invest in the proof US buyers need.
- If you are investing: ask what share of revenue comes from routine coding priced per chart, and how that share has moved over three years. That one number tells you more about AI exposure than any product demo.
- If you are building for Indian hospitals: measure deductions and delays by payer before you design anything. The KPIs we recommend tracking are a starting point.
Medical coding in India is not a clerical job waiting to be automated. It is the front line of a revenue process, and the firms that treat it that way will price, sell and grow differently from those that do not.
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SRF Capital Studio Research Desk
Funding Intelligence, SRF Capital Studio
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