Healthcare provider cases (hospitals, health systems, physician groups) are not pharma launch cases and not life-sciences pipeline cases. The decision is almost always about throughput, payer mix, and capacity, not selling more units.
Last full pass: 24 August 2026.
A healthcare case interview in 2026 is a provider-economics problem wearing a clinical costume. McKinsey, BCG, Bain, and the Big Four health practices use it because a hospital P&L looks simple until you notice that revenue is a rate per discharge set by Medicare DRGs and commercial contracts, while cost is driven by length of stay and staffing per occupied bed. Clarify the objective in one sentence: are we raising operating margin, cutting wait times, or deciding whether to add capacity? Then name the unit of volume. If you say “beds” when the interviewer is paying you on discharges, you will optimize the wrong thing.
This page is the provider track. Drug manufacturers belong on the pharma case interview guide. Mixed biotech, medtech, and diagnostics prompts belong on life sciences consulting cases.
What the interviewer wants you to decide
Typical objectives, none of which is “maximize revenue”:
- Capacity: add beds, ORs, or clinic slots, or squeeze more discharges from the beds you already staff.
- Service-line mix: grow orthopedics vs cut unprofitable medical admissions.
- Payer mix: commercial vs Medicare vs Medicaid vs self-pay. The same DRG can be a contribution machine or a loss.
- Site of care: inpatient vs outpatient vs ambulatory surgery center (ASC).
Ask four clarifying questions before you draw a tree: (1) staffed beds vs licensed beds, (2) which payer the exhibit is blended across, (3) average length of stay (ALOS) vs occupancy, (4) whether quality or CMS star ratings constrain the “just discharge faster” idea.
Exhibits you should expect
| Exhibit | What it is actually for |
|---|---|
| Occupancy by unit (med/surg, ICU, OB) | Occupancy is not demand. A 92% ICU with a 4% med/surg unit is a bottleneck, not a full hospital. |
| ALOS vs expected ALOS by DRG | Throughput lever. Cutting ALOS raises discharges at the same bed count. |
| Payer mix and rate card | Commercial might pay 1.6–2.0× Medicare on the same DRG. Blended average hides the mix shift. |
| Case-mix index / DRG weights | A “volume up, margin down” story is often a shift into lower-weight DRGs. |
| Staffing per occupied bed (HPPD) | Nursing is the flexible cost. Empty beds still need a night-shift floor. |
| Readmission or CMS penalty line | The constraint on aggressive ALOS cuts. |
Units and regulations that trip people
Beds vs discharges. Occupancy × beds × 365 gives patient-days. Discharges = patient-days / ALOS. Adding beds increases patient-days only if you can staff and fill them. Cutting ALOS increases discharges with no capex.
DRG vs per diem vs capitation. Medicare inpatient is typically a bundled DRG payment per stay, not per day. A longer stay at the same DRG is extra cost with no extra revenue. Commercial may still have per-diem outliers. If the client is a Medicaid managed-care plan rather than a hospital, you are suddenly in financial services economics (medical loss ratio), not provider throughput.
EMTALA and call coverage. You cannot “stop taking the unprofitable ED.” You can change downstream admission criteria and transfer protocols, with legal and reputational limits.
Practice a provider-economics case
Run a scored case and force the occupancy vs discharge distinction before you talk about adding a wing.
Worked mini-case: the 40-bed wing vs four-tenths of a day
Prompt. Riverview Health is a 280-staffed-bed community hospital. Occupancy is 72%, ALOS is 5.2 days. Blended net payment is $12,400 per discharge; variable cost is $11,100 per discharge (interview-style figures, stated as case inputs, not a market study). The CEO wants a $8.0m, 40-bed wing that would need $1.1m extra annual nursing. A length-of-stay program would cut ALOS to 4.8 days for $0.4m and no capex. Quality leadership says readmissions cannot rise. What do you recommend for next year’s operating margin?
Structure. (1) Current discharge factory, (2) ALOS lever holding beds and occupancy constant, (3) bed-add lever holding ALOS constant, (4) cash and staff, (5) quality constraint.
Math. Patient-days today = 280 × 0.72 × 365 = 73,584. Discharges = 73,584 / 5.2 ≈ 14,151. Contribution per discharge = $1,300.
ALOS to 4.8 days, same beds and occupancy: discharges = 73,584 / 4.8 = 15,330, or +1,179 stays. Extra contribution ≈ 1,179 × $1,300 = $1.53m, minus $0.4m program cost → ~$1.13m operating-profit lift, no $8m check.
Forty new beds at 72% occupancy and 5.2 ALOS: extra patient-days = 40 × 0.72 × 365 = 10,512; extra discharges ≈ 2,022; extra contribution ≈ $2.63m, minus $1.1m nursing → $1.53m year-1 P&L, but only after $8.0m of capital and only if those beds actually fill. At 72% occupancy the hospital is not short of rooms; it may be short of turns.
Recommendation. Do not pour concrete. Run the ALOS program, track 30-day readmissions weekly, and treat the wing as a year-2 option if occupancy on med/surg actually binds after throughput improves. Risk: ALOS cuts that dump patients into SNFs the hospital owns can look like a win on the inpatient P&L and a loss on the system. Next step: ALOS and contribution by DRG and by payer, not a blended average.
What a generic profitability tree misses here
Revenue − cost with “price × volume” treats the hospital like a retailer. It misses:
- Volume is discharges, not beds and not patient-days. Occupancy can rise while discharges fall if ALOS inflates.
- Price is not a sticker. It is a DRG weight × a base rate × a payer contract. Mix kills you silently.
- Variable cost is per day as much as per stay. Under DRG, extra days destroy margin.
- Fixed cost is staffing a unit, not a theoretical bed. A mothballed wing still needs a charge nurse if you open it.
- Quality metrics are binding constraints, not CSR. CMS penalties and commercial steerage reverse a “throughput win.”
The candidates who fail this case add capacity because occupancy is “only 72%” without asking whether the 72% is an ICU bottleneck plus empty med/surg, or a true demand gap.
See where you stand on a healthcare case
Practice the discharge math and the payer-mix so-what under time pressure.
Related guides
- Pharma case interview (manufacturer, patent cliff, net price)
- Life sciences consulting case interview (mixed pipeline and devices)
- Profitability framework
CoachNed is independent and unaffiliated with McKinsey, BCG, Bain, or other firms named for interview-style practice. Cases on CoachNed are AI-simulated.