Hospitals
One number carries most of the story: average revenue per occupied bed. It is not a price — it is the output of specialty mix, payer mix and case mix working together, which is why two hospitals with identical bed counts can earn three times differently.
ARPOB × occupancy × beds is the revenue engine. ALOS decides how fast beds turn. Everything else — capex per bed, doctor cost structure, accreditation — determines whether the capital ever earns out.
A two-tier structure, and a specialist layer above it.
The structure is two-tier. Multi-specialty tertiary care handles complex surgical procedures and critical care; single-specialty clinics and nursing homes handle primary and secondary care. Private hospitals account for roughly 58–60% of the market by value, expected to rise toward 73%, with large chains holding around 12% of that.
Single-specialty leaders have taken real share. Category leaders have captured 20%+ of the organised market in their niche — oncology, children's, eyecare, IVF, dialysis, dental and uro-nephrology each have a dominant operator. These are different businesses from a general tertiary hospital: narrower, more repeatable, and often higher-margin.
ARPOB spread across the listed set
- ₹60–70kThe large metro tertiary chains. Some hospitals reach ₹90k, growing 10–11% a year.
- ₹48kChildren's specialty, growing 7–8% a year.
- ₹25–30kThe value-tier chains — lower price point, different catchment, different model entirely.
Higher ARPOB represents genuine pricing power. But it is an outcome: change the specialty mix or the payer mix and ARPOB moves without any price list changing.
A fixed asset, filled at variable prices.
The cost stack
- Doctor cost22–24% of revenue. The largest single line, and the one with the most structural choice attached.
- Medical consumables14–15%.
- Other costs~7%.
- Marketing & business2–3% of the top line.
- Repairs & maintenance2–2.5%.
The doctor question is the structural one. Consultant cost — including super-specialists — is the main expense for any hospital. Is it a revenue-sharing arrangement or a guaranteed monthly payment? Many visiting consultants reduce fixed cost but dilute the hospital's brand, because the patient's loyalty follows the doctor rather than the institution. A senior departure in a high-value specialty can move a whole service line.
ALOS cuts both ways. Most revenue from a patient is earned in the early part of the stay, so hospitals push ALOS down to turn beds faster. But a surgical-heavy case mix naturally lengthens it. Read ALOS alongside case mix, never alone.
Switching costs are real but narrow. A patient mid-treatment in acute complex care does not transfer. An OPD or elective patient will. That asymmetry is why complex tertiary care commands durable pricing while elective volumes are contestable.
Mix, density, and clinical depth.
Mix engineering
Deliberately shifting specialty, case and payer mix upward lifts ARPOB without a price increase. Oncology and cardiac depth, plus a rising cash and international share, is the cleanest margin lever available.
Catchment dominance
Occupancy follows referral density in a defined catchment. Regional dominance — one chain owning the referral map of a city — is what sustains 75%+ occupancy while peers sit at 55–65%.
Clinical talent depth
A bench of senior consultants no competitor can rebuild in under years is the actual moat. It is also the key-person risk — the two are the same asset viewed from different sides.
What to answer before underwriting.
- →ARPOB bridge. How much of the move is specialty mix, case mix, payer mix, and how much is actual price? These are different qualities of growth.
- →Mature vs ramping occupancy. Split the estate. A blended occupancy number hides both a strong core and a capital-consuming tail.
- →Payer split. Out-of-pocket and international versus insured versus government schemes (CGHS, EHS, ECHS). Scheme beds carry state-set tariffs and can be a material share of capacity.
- →Doctor arrangements. Revenue-share or guaranteed monthly? How many visiting versus full-time consultants, and what does that do to fixed cost and brand?
- →Key-person exposure. Any senior departure in a high-value specialty, and what share of that service line's revenue followed them.
- →OPD to IPD conversion. OPD volume is the leading indicator of inpatient revenue. What is the conversion rate and is it trending?
- →Referral channels. Self-referral, physician referral, corporate or TPA routing — and how dependent the book is on any one.
- →Capex per bed and payback. Land, construction and equipment split; expected maturity period; and how it compares with peer projects.
- →Lease versus greenfield. The capital intensity and return profile differ sharply. Which model is the expansion using?
- →Price caps and DPCO. Exposure to government caps on elective procedures and to Drug Price Control Orders on the pharmacy line.
- →Base effects. Was a strong prior year inflated by acute or viral infection load? What underpins confidence that occupancy holds?
- →Ancillary lines. Pharmacy, diagnostics, wellness and tele-diagnostics — revenue share and margin on each.
What to monitor, quarter by quarter.
| KPI | Calculation / source | Benchmark or read-through |
|---|---|---|
| ARPOB | Revenue ÷ occupied bed days | ₹25–30k value tier, ₹60–70k metro tertiary, ₹90k at the top |
| Occupancy rate | Beds occupied ÷ beds available | 55–65% at ramping/specialty, ~77% at a dominant metro chain |
| Operational beds | Beds live vs licensed | Licensed capacity overstates earning capacity — use operational |
| ALOS | Total bed days ÷ discharges | Lower turns beds faster, but rises with surgical mix — read together |
| Occupied bed days by specialty | OBD split | Where the beds actually go; the driver behind ARPOB |
| Payer mix | Cash / insurance / government / international | Cash and international absorb full list price and lift blended ARPOB |
| Case mix | ICU and surgical share of cases | Higher-intensity cases carry higher charges and longer stays |
| IPD vs OPD volumes | Footfall, YoY | OPD is the leading indicator of inpatient revenue |
| OPD to IPD conversion | Admissions ÷ OPD visits | The efficiency of the funnel from footfall to revenue |
| New patient volume | First-time registrations | Distinguishes genuine catchment growth from repeat load |
| ARPP | Revenue ÷ patients | Complements ARPOB where day-care and OPD are material |
| Doctor cost ratio | Consultant cost ÷ revenue | 22–24% is the working band; structure matters as much as level |
| Consumables ratio | Consumables ÷ revenue | 14–15% typical; a spike signals case-mix change or leakage |
| EBITDA per bed | Segment EBITDA ÷ operational beds | Normalises across differently-sized estates |
| Capex per bed | Project cost ÷ beds added | Compare against peer greenfield projects; drives the payback |
| ROCE by unit | Unit EBIT ÷ capital employed | Mature units should carry the estate; identify which actually do |
How the thesis breaks.
- !Regulatory price caps. Government caps on elective procedures and DPCO on drugs compress the highest-margin lines with no operational remedy.
- !Government-scheme dependence. A large share of beds billed at state-set tariffs earns far less per bed, and rate revisions are political and infrequent.
- !Key clinician departure. A senior specialist leaving can take a service line's volume with them — the moat and the risk are the same person.
- !The greenfield drag. A 7–8 year payback and 3–5 years to accreditation means aggressive expansion suppresses consolidated returns for a long time.
- !Flattering base years. Occupancy inflated by an acute infection season sets an unrepeatable comparison.
- !Perverse doctor incentives. Performance-linked pay tied to the business a doctor generates — including pushing tests — is a clinical governance and reputational exposure.
- !Occupancy without ARPOB. Filling beds with low-tariff cases grows volume and flatters occupancy while doing nothing for returns.
The figures, and where they stand.
| Metric | Value | Note | Basis |
|---|---|---|---|
| ARPOB — metro tertiary | ₹60–70k | Top hospitals reach ₹90k; growing 10–11% p.a. | FY23 |
| ARPOB — value tier | ₹25–30k | Different catchment and model | FY23 |
| ARPOB — children's specialty | ~₹48k | Growing 7–8% p.a. | FY23 |
| Occupancy range | 55–77% | Specialty/ramping at the low end, dominant metro at the high | Research note |
| Doctor cost | 22–24% | Of revenue — the largest single cost line | Research note |
| Medical consumables | 14–15% | Other costs ~7% | Research note |
| Marketing / R&M | 2–3% / 2–2.5% | Of the top line | Research note |
| Greenfield payback | 7–8 years | Multi-specialty above 200 beds | Est. |
| Land requirement | 4–5 acres | For a 400-bed facility | Research note |
| NABH accreditation | 3–5 years | Mandatory for scheme empanelment and insurance recognition | Regulatory |
| Private hospital share | 58–60% → ~73% | Of market by value; large chains ~12% | To FY25E |
| Single-specialty leaders | 20%+ share | Dialysis ~43%, dental ~47%, oncology ~48%, IVF ~35%, children's ~26%, eyecare ~20% | Research note |