Healthcare FDD demands reimbursement analysis, claims data, staffing normalisation and regulatory exposure. A practitioner's guide to the angles that generic playbooks miss.
Two care-home groups can post identical EBITDA growth of 8% year on year, and one of them can be a fundamentally worse business than the other. In healthcare, the number on the page tells you almost nothing until you know what drove it — a fee uplift the payer can reverse next April, a spike in agency nursing that masks a recruitment crisis, or a single framework contract quietly renegotiated downwards. The mechanics of financial due diligence do not change when you walk into a healthcare deal. What changes is where the risk lives, and if you dig in the usual industrials or software places you will walk straight past it.
This is why healthcare is one of the sectors where sector fluency, not just technical competence, separates a strong analyst from an average one. Let me walk through the angles that actually matter.
In most sectors, a customer receives a service and pays for it at an agreed price. In large parts of healthcare — clinics, care homes, diagnostics labs, dental groups, community services — the person receiving the care is not the person paying for it. A public payer (the NHS, a national insurance fund, a regional health authority) or a private insurer reimburses the provider, often at a rate the provider does not fully control.
That single fact reshapes your entire approach to revenue quality. A reimbursement rate change, a shift in coding methodology, or a renegotiated payer tariff can move revenue overnight with zero change in the volume of care actually delivered. Historical growth driven by a temporarily favourable tariff is not the same quality as growth driven by genuine volume expansion — yet both land identically in the P&L.
A 3% tariff uplift and a 3% increase in patient episodes look the same in the revenue line and completely different in an investment committee. Your job is to tell them apart before the buyer signs.
So the first question in any healthcare quality of earnings exercise is never "did revenue grow?" It is "was the growth rate or volume?" You decompose the top line into price (tariff) and quantity (episodes, bed-days, tests, procedures) and you ask which is durable.
Suppose a diagnostics provider grew imaging revenue from £20.0m to £23.1m — a headline 15.5% increase that management is presenting as a growth story. You pull the operational data and rebuild it.
| Driver | FY24 | FY25 | Change | Quality read |
|---|---|---|---|---|
| Scans performed (000s) | 200 | 210 | +5.0% | Durable — real volume |
| Average reimbursement (£/scan) | 100 | 110 | +10.0% | Fragile — payer-set tariff |
| Imaging revenue (£m) | 20.0 | 23.1 | +15.5% | Mostly price |
Of the £3.1m uplift, roughly £2.1m comes from a tariff increase the provider did not earn through effort and the payer can revise. Only about £1.0m is genuine volume. If that tariff reverts in the next funding round — a live risk in publicly funded healthcare — a buyer who paid a multiple on the full £23.1m has overpaid materially. The normalised, defensible run-rate here is closer to a low-single-digit growth business than a mid-teens one. That distinction, surfaced clearly, is worth more than any amount of polish elsewhere in the report.
This is the same discipline behind every EBITDA adjustment: strip out what is not repeatable and show the buyer the true underlying engine.
Healthcare providers usually deliver the service months before they get paid. A claim is submitted, the payer adjudicates it, some portion is queried, some is denied, and cash eventually settles — or does not. This produces receivables and accrued-income balances that behave nothing like a standard trade debtor book, and it feeds directly into your net working capital analysis.
The trap is analysing the AR ageing as if every invoice will pay in full. In healthcare, a slice of billed revenue is denied or clawed back by the payer after the fact — sometimes a year later, following a coding audit. A provider running a high gross-billing model with a chronic denial rate is booking revenue it will never collect.
| Metric | What a generic AR review sees | What healthcare FDD must check |
|---|---|---|
| Debtor days | Simple DSO calculation | Split by payer; adjudication lag differs hugely |
| Bad debt provision | Ageing-based percentage | Actual historical denial and clawback rates by claim type |
| Accrued income | A balance to confirm | Whether the underlying claims will survive payer audit |
| Revenue cut-off | Invoice date | Service date vs. claim-approval date |
You cannot answer these from the sales ledger. You need the claims data — denial rates, resubmission success, average days-to-adjudication by payer. A history of claims being reversed is a genuine revenue quality red flag, and it is one of the clearest examples in the sector of a finding that belongs in your red flags summary. Any working-capital adjustment or normalised debtor-days assumption you feed into the working capital target mechanism has to reflect real collection behaviour, not gross billings.
Healthcare margins are unusually sensitive to labour. Clinical and nursing shortages have driven real wage inflation in many markets, and providers plug rota gaps with agency and locum staff at premium rates — sometimes 1.5 to 2 times the cost of a permanent equivalent. That distorts the cost base and, crucially, the EBITDA a buyer is being asked to underwrite.
The analytical question is whether agency dependency is structural or temporary. A one-off spike covering a maternity leave or a seasonal surge might reasonably be normalised out. Chronic reliance on locums because the group cannot recruit permanent staff is not a one-off — it is the cost of running the business, and normalising it away flatters EBITDA dishonestly.
This is far closer to a judgement-heavy remuneration normalisation than to a mechanical cost-base tidy-up, and it has direct consequences for the sustainable margin you present.
Healthcare businesses operate inside dense regulatory regimes — facility registration, minimum staff-to-patient ratios, clinical governance standards, inspection ratings. A downgraded inspection can suspend admissions; a breach can trigger fines, mandated remediation spend, or licence loss. These are real financial exposures that a purely financial-statement-driven review will miss entirely.
Two things matter here. First, capex to maintain compliance is not discretionary. If a care home needs £1.2m of building works simply to keep its registration, that is effectively maintenance capex, not growth investment, and it must be treated as such in the cash-flow picture and any normalised free-cash-flow view. Second, an unresolved regulatory issue — an outstanding enforcement notice, a pending investigation — is a contingent liability that needs sizing.
You will not run the regulatory review yourself. But flagging the need for a parallel regulatory workstream, and pushing to have its findings reflected in your numbers, is frequently as valuable as anything in your own report. This dovetails with the broader financial due diligence process: the best analysts treat adjacent workstreams as data sources, not silos.
Many healthcare targets grow by rolling up sites — buying clinics, homes or practices and consolidating them. That makes reported growth almost meaningless until you separate organic (like-for-like) growth from acquired growth. A group that "grew" 20% because it bought four new sites is a very different proposition from one that grew 20% at existing sites.
Build a like-for-like bridge: strip out sites acquired or opened in the period, and show what the mature estate actually did. This matters for the buyer's whole thesis and it also affects how you think about the EV-to-equity bridge — deferred consideration and earn-outs from prior roll-up deals often sit as debt-like items that reduce equity value at completion. Where a target has been assembled through acquisitions, some of those sit outside the core net-debt-style working defined in the net debt analysis and need calling out explicitly.
Expect a healthcare-flavoured version of "what would you focus on?" Do not recite the generic framework. Show that you know where the sector's risk concentrates.
"In a healthcare deal my first instinct is that reported revenue growth can be misleading, because so much of the top line is reimbursement-driven rather than customer-paid. So I'd want to decompose growth into tariff versus volume — a fee uplift the payer can reverse next year is far lower quality than genuine episode growth, even though both look identical in the P&L. Second, I'd scrutinise receivables using claims data rather than a standard AR ageing, because denial and clawback rates mean a chunk of billed revenue may never collect, which flows straight into my working-capital view. Third, on the cost side, I'd interrogate agency and locum spend — if reliance is structural rather than a one-off, normalising it out overstates sustainable EBITDA. And I'd flag early whether a regulatory workstream is in scope, because compliance-driven capex isn't discretionary and an open enforcement issue is a contingent liability. The mechanics of the EBITDA and net debt bridges are the same as any deal; healthcare just tells me exactly where to dig hardest."
That answer works because it is concrete, sequenced, and shows you understand why the generic playbook needs adapting — which is precisely the interview signal senior reviewers look for.
The framework you learned on your first industrials job does not get thrown away in healthcare — you are still building an EBITDA bridge, still working a net-debt line, still landing a working-capital target. What sector fluency buys you is a map of where to spend your hours: reimbursement mechanics over generic revenue trends, claims data over simple AR ageing, structural agency cost over a tidy cost-base review, and compliance capex over a boilerplate fixed-asset note. Get those four right and you will have said something the deal team cannot get from the data room alone. That is the whole job — and in a sector where two identical EBITDA numbers can hide two completely different businesses, it is where the money is made or lost.
The Transaction Services Interview Programme (€119.99, one-time) includes a dedicated healthcare-sector module covering reimbursement analysis, claims-data receivables testing, and agency-cost normalisation, with worked models and interview drills. Enrol today.
Hundreds of candidates prepared their interviews with this programme. Those who landed the role have one thing in common: they worked the cases before walking into the room.
