Before youbuild.

Every private hospital starts as a conviction: there is a need, we can meet it, and it will pay. The feasibility study is where that conviction meets the numbers, the rules and the people it depends on. It is also the last point at which changing the plan is cheap.

Once the building is designed, the equipment ordered and the first specialists hired, every change costs money and time. Before that point, a change is a few days of work on a model. That asymmetry is the whole case for doing the study properly.

Yet many hospital studies are written to confirm a decision that has already been taken. They start from a building, assume the beds will fill, and present a spreadsheet that looks solid until the first assumption moves. This article sets out what a study should answer instead, using the Romanian market as the setting.

A feasibility study is not there to prove the hospital will work. It is there to show under which conditions it will.

Read the market, not the averages

At first sight, Romania does not need more hospital beds. It has one of the highest bed rates in the European Union, and well above the average of OECD countries. At the same time, patients pay a large share of their health costs directly, and only a small share of the population is covered by private health insurance through their employer.

Read together, these figures say something important for an investor. The demand for private care in Romania is not about the number of beds. It is about access, waiting times, comfort and confidence in specific specialties, and people are already paying for those out of their own pockets.

That shifts the first question of the study. It is not whether the region needs a hospital. It is which services, for which patients, paid by whom: by patients directly, by private insurers and employers, or through a contract with the national health insurance system. Each answer leads to a different hospital.

Six questions the study must answer

A complete study answers six questions. They are connected: a change in one moves the others. A study that answers only the last one, the money, is a budget, not a feasibility study.

Questions 1 and 2

Demand and services

Demand analysis should start from patients, not from the building. Who lives in the catchment area, how old are they, what do they suffer from, where are they treated today, and why would they come to a new hospital instead? Existing providers, public and private, matter as much as the population: a specialty that is already well served nearby is a harder market than one where patients travel or wait.

From there, the study defines the medical service catalogue: which specialties, which procedures and in what volumes. This is the single most important decision in the whole plan, because everything else follows from it. The building, the equipment, the team and the revenue are all consequences of the service mix.

The doctors who will work in the hospital are the best source of input for this catalogue, but their input needs structure. Each specialist tends to plan for their own department. The study's job is to bring those plans together into one catalogue, check it against market references and the demand analysis, and make the trade-offs visible.

Questions 3 and 4

Capacity and people

Capacity follows from the services. For each specialty, the expected number of patients and the average length of stay give the number of beds needed, with a margin for peaks. The same logic applies to operating theatres, imaging rooms and day-care places. Doing this one specialty at a time, rather than for the hospital as a whole, shows where the real constraints are.

People are often the hardest constraint of all. A bed is only usable if there are doctors, nurses and support staff to run it, around the clock. The staffing plan has to meet the national staffing norms for each type of service, and it has to be realistic about the local labour market. In many Romanian regions, the question is not how many specialists the hospital needs, but whether it can recruit them at all.

Personnel is usually the largest operating cost of a hospital. That is why the staffing plan should feed directly into the financial model, rather than being estimated as a percentage of revenue.

Question 5

The money

The financial model brings the first four answers together. On one side, the investment: the building or its conversion, medical equipment, IT systems and the cost of getting ready to open. On the other, the running costs and the revenue, specialty by specialty.

A model is only as good as its assumptions, and the most useful thing a study can do is write them down. How many patients per day in year one? At what average price? With what length of stay? Paid by whom? When every assumption is visible, a board, an investor or a bank can question it, and the model becomes a tool for discussion rather than a page of conclusions.

We recommend building on deliberately cautious assumptions. If the hospital works on cautious numbers, anything better is upside. If it only works on optimistic ones, that is worth knowing before the first contract is signed.

Regulation belongs in this part of the study, not in a separate chapter. Whether the hospital will seek a contract with the national health insurance system, and so the accreditation that requires, changes who pays for which services, and therefore the revenue model itself. We describe the approvals involved in our guide to opening a private clinic in Romania.

Question 6

The ramp-up decides the financing

The question most often missed is time. A new hospital does not open full. Doctors build their patient lists gradually, referrals take time to form and reputation takes longer. A widely used World Bank guide to private healthcare facilities suggests that a new hospital typically needs around five years to become fully established.

The exhibit shows why this matters. In the optimistic case, this illustrative hospital covers its running costs in year two. In the base case, in year three. In the cautious case, only in year five. The building, the equipment and the team are the same in all three. What changes is how long the hospital needs funding before it pays for itself.

That difference is the funding gap, and it is where many hospital projects get into trouble. A plan financed for the base case has no room if reality follows the cautious line. The study should size the gap for each scenario, so the financing can be designed to survive the slower one.

Know which number to watch

A hospital model may have hundreds of inputs, but only a few of them drive most of the result. A good study tests each important assumption in turn and shows how much the result moves. The answer is often surprising.

In this illustration, occupancy and the average revenue per patient together move the result far more than all the cost lines except staff. That tells leadership where to focus: on the specialties, referral routes and pricing that fill beds, and on the staffing model that serves them. Energy and consumables still matter, but they will not decide whether the hospital succeeds.

In our own work on a new hospital, modelling capacity one specialty at a time made it clear which number would really drive the result. That one number then became the focus of leadership's attention, long before the doors opened.

What a good study gives you

At the end of the work, the investor should hold more than a report. A good feasibility study delivers five things.

1. 01

   A clear answer

   Go, go under conditions, or do not go. A study that cannot reach a conclusion has not finished its job.

2. 02

   Written assumptions

   Every important number, with where it came from and how confident it is, so anyone can challenge it.

3. 03

   A working model

   A model the team can use and update as the project moves, not a static document that is out of date in a month.

4. 04

   Scenarios and a funding gap

   What happens if the ramp-up is slower, and how much funding the slower case needs.

5. 05

   The conditions behind the answer

   The approvals, recruitment and partnerships the plan depends on, with the risks attached to each.

A closing thought

The best moment to discover that a hospital will not work is before it is built. The second best is never. A rigorous feasibility study is the cheapest insurance an investor can buy, and the projects that take it seriously are rarely the ones that need rescuing later.