ModelChoice decision tree · Healthcare
Hospital Equipment Decision
Buy premium or standard imaging equipment, lease it, or share it with a partner hospital?
From the model’s decision tree
Best first decision: Buy Premium Equipment
The expected value of each first option when every later decision is also made well (the tree rolled back).
| First decision | Expected value | |
|---|---|---|
| Buy Premium Equipment | $44,810,000 | ✔ best |
| Buy Standard Equipment | $42,080,000 | |
| Lease Equipment | $42,642,500 | |
| Share with Partner Hospital | $26,060,000 |
| Measure | Value |
|---|---|
| Expected value of the best strategy | $44,810,000 |
| Best outcome on the best strategy | $47,750,000 |
| Worst outcome on the best strategy | $38,600,000 |
S-curve (cumulative probability) of Buy Premium Equipment from the saved simulation.
The decision
A hospital needs to acquire specialized medical imaging equipment for its radiology department. The equipment will serve a growing patient population over the next decade. Management must weigh capital cost, maintenance, reliability, and patient throughput. The options are:
- Buy Premium Equipment — highest capability, best reliability, highest cost
- Buy Standard Equipment — proven technology, lower cost, more breakdown risk
- Lease Equipment — no capital outlay, includes maintenance, upgrade options
- Share with Partner Hospital — split costs but accept scheduling constraints
How the inputs are linked
Patient Volume, Revenue per Procedure, and Maintenance Costs are defined once and referenced by multiple branches. Changing clinical volumes instantly updates all paths.
The inputs that drive several branches at once:
- Revenue per Procedure × Patient Volume — drives revenue across all four paths
- Maintenance Costs — applied in premium, standard, and shared paths
- Patient Volume — throughput multiplier used in every revenue calculation
- Useful Life — time horizon for all revenue and cost projections
- Downtime Cost per Day — penalty applied in breakdown scenarios across paths
- Standard Price — used in buy standard and as fallback in failed sharing
The decision tree
The tree has 2 decisions, 4 chance events and 13 outcomes. The best path is open: at every decision the best choice is marked, and the expected value beside each branch counts every cash flow from the start. Open any other branch to see what follows it.
DecisionChance event+$ cash flow on the branch
Buy Premium Equipment −$2,500,000expected $44,810,000 ✔ best
Chance: Premium Equipment Reliability- 60% High Reliability +$50,250,000payoff $47,750,000
- 30% Normal Reliability +$43,500,000payoff $41,000,000
- 10% Frequent Breakdowns +$41,100,000payoff $38,600,000
Buy Standard Equipment −$1,200,000expected $42,080,000
Chance: Standard Equipment Reliability- 40% High Reliability +$44,000,000payoff $42,800,000
- 40% Normal Reliability +$44,000,000payoff $42,800,000
- 20% Frequent Breakdowns +$40,400,000payoff $39,200,000
Lease Equipmentexpected $42,642,500
Chance: Lease Equipment Performance- 35% Upgrade Available +$47,750,000payoff $47,750,000
- 50% Standard Performance +$41,000,000payoff $41,000,000
- 15% Vendor Issues +$36,200,000payoff $36,200,000
Share with Partner Hospital −$1,250,000expected $26,060,000
Chance: Sharing Arrangement Outcome- 30% Smooth Coordination +$30,750,000payoff $29,500,000
- 45% Scheduling Conflicts +$21,300,000payoff $20,050,000
25% Partnership Breakdownexpected $32,750,000
Decision: Partnership Failed- Buy Own Standard Equipment +$34,000,000payoff $32,750,000 ✔ best
- Continue Sharing (Reduced) +$15,000,000payoff $13,750,000
Change the numbers. Open the workbook with ModelChoice, change a probability or a cost in the tree, and the best decision updates at once.
Key assumptions
| Assumption | Value | Notes |
|---|---|---|
| Equipment Purchase Price (Premium) | $2,500,000 | High-end equipment with latest features |
| Equipment Purchase Price (Standard) | $1,200,000 | Reliable mid-range equipment |
| Annual Maintenance Cost (Premium) | $150,000 | Preventive maintenance contract |
| Annual Maintenance Cost (Standard) | $100,000 | Basic maintenance contract |
| Patient Volume per Year | 3,000 | Expected annual procedures |
| Revenue per Procedure | $1,500 | Average reimbursement per procedure |
| Lease Annual Cost | $400,000 | Annual equipment lease payment |
| Useful Life (Years) | 10 | Equipment operational lifetime |
| Premium Efficiency Bonus | 15.0% | Extra throughput from premium equipment |
| Shared Equipment Cost Share | 50.0% | Our share of shared equipment costs |
| Shared Utilization Factor | 70.0% | Available capacity when sharing equipment |
| Downtime Cost per Day | $8,000 | Lost revenue during equipment downtime |
The figures are illustrative: the companies and numbers are invented for teaching.
Try it in ModelChoice
- Increase Patient Volume. Watch all revenue terminals scale up together
- Raise Revenue per Procedure. See how reimbursement rates shift the decision
- Increase Downtime Cost. Reliability becomes more valuable
- Run Sensitivity Analysis. Find which clinical parameter matters most
Find similar models
- Product
- Type
- Application
- Uses
Further reading
Download the workbook and open it with ModelChoice. The free trial opens every example.
Related example models
- ModelChoice★★★★★Fleet ElectrificationConvert a 100-vehicle diesel fleet to electric all at once, in phases, in part, or not at all?Two decisions and four chance events, driven by linked inputs. Best first decision: Hybrid Fleet (30% EV), expected value $1.1m.
- ModelChoice★★★★★Software Platform Build vs BuyBuild a software platform, buy a licence, buy and customise one, or use open source?Two decisions and four chance events, driven by linked inputs. Best first decision: Buy Commercial License, expected value $9.4m.
- ModelChoice★★★★★Data Center BuildBuild a Tier IV or a Tier III data centre, lease colocation space, or move to the cloud?One decision and four chance events, driven by linked inputs. Best first decision: Colocation Partnership, expected cost $14.1m.
An illustrative example: the figures are invented for teaching. Last updated 9 October 2026.