Healthcare and pharma
Cases on medicines, hospitals, and health insurers: pricing a drug under health technology assessment, sizing hospital capacity with Little's Law, and payer and provider economics.
Key takeaways
- In healthcare, the buyer is often not the patient, so follow the money: who pays, what they judge value on, and what limits capacity.
- First establish who pays and how, then size the value or capacity question with the right healthcare measure (cost per QALY, occupied beds, cost per member), and check patient outcomes alongside money.
- Healthcare cases are common, and firms with large life-sciences and healthcare practices may expect you to handle basic terms such as payers, providers, and QALYs.
- The strong answer follows the payer's decision rule. The weak one prices as if the patient were the buyer.
What this case type is and when it shows up
Healthcare cases cover drug and device makers, hospitals and clinics (providers), and the organizations that pay for care (payers: government health systems, social insurance, and private insurers). Typical questions: how to price or launch a new drug, how to fix hospital capacity or waiting times, or how an insurer can control costs. Many firms have large healthcare practices, and these cases often use their own vocabulary, which you should define as you go.
Key idea
In healthcare, the buyer is often not the patient, so follow the money: who pays, what they judge value on, and what limits capacity.
The underlying theory, in plain language
Three groups matter. Payers decide what is covered and at what price. Providers deliver care and are paid per service, per case (a fixed price per procedure or package), or per person. Makers of drugs and devices must convince payers that their product is worth its price.
Many health systems judge new medicines through health technology assessment (HTA): does the extra health benefit justify the extra cost? Benefit is often measured in quality-adjusted life years (QALYs); one QALY is one year of life in full health. The cost per QALY gained (the incremental cost-effectiveness ratio) is the extra cost divided by the extra QALYs. England's HTA body, NICE, used a threshold of roughly GBP 20,000 to 30,000 per QALY for more than two decades, and from April 2026 uses GBP 25,000 to 35,000. Thresholds change, so check the current figure.
Hospital capacity follows Little's Law: the average number of occupied beds equals admissions per day times the average length of stay. Hospitals usually aim for average bed occupancy of about 85 percent or less, because higher occupancy leaves no room for peaks and leads to long waits in emergency departments.
Payer economics: an insurer's cost is members x share using a service x cost per use. Programs that prevent expensive care, such as diabetes management, can save money if they cost less than the care they avoid.
What the prompts sound like, from simple to hard
- Simple: why are emergency waits so long at a hospital in Dubai.
- Medium: at what price should a new drug launch in England.
- Hard: should a private hospital group in India add beds or shorten stays, given how insurers pay.
Finding and narrowing the real problem
Key idea
First establish who pays and how, then size the value or capacity question with the right healthcare measure (cost per QALY, occupied beds, cost per member), and check patient outcomes alongside money.
- Healthcare question
- Payer: who pays and on what basis
- Coverage and price decisions
- Cost per member
- Key: Product maker: value versus price
- Extra benefit (QALYs)
- Extra cost and cost offsets
- Cost per QALY versus threshold
- Provider: capacity and cost
- Admissions x length of stay
- Occupancy versus target
- Payment model (per day, per case)
- Patient outcomes and access
Pick the branch the question sits in, and follow the money.
Frameworks for this type, each as a thinking tool with its limit
- Payer, provider, product maker: Identify who pays, who delivers, and whose decision the case is about. Limit: Systems differ by country; ask how payment works.
- Cost per QALY: Extra cost divided by extra QALYs, compared with a threshold. Limit: QALYs do not capture every benefit, and thresholds vary.
- Little's Law for beds: Occupied beds = admissions per day x average length of stay. Limit: Averages hide daily and seasonal peaks.
Methods for solving this type
- Ask who pays and how
- Choose the right measure (cost per QALY, occupied beds, cost per member)
- Size the question with that measure
- Compare options, including doing nothing
- Check patient outcomes and access
The math patterns it relies on
- Cost per QALY = (new cost minus old cost minus cost offsets) / extra QALYs
- Maximum price = threshold x QALYs + old cost + offsets
- Occupied beds = admissions per day x length of stay
- Insurer cost = members x share using x cost per use
Worked cases
Worked case
Launching a new drug in England
The prompt
A drug maker plans to launch a new drug in England at GBP 28,000 per course. Trials show it adds 0.5 QALYs per patient compared with the current treatment. About 8,000 patients a year are eligible, and about half would get it once approved. The exhibit summarizes the costs. Will it be approved at this price, and what should the company do?
Interviewer-led: the interviewer shows the cost table and asks for the cost per QALY.
Clarifying questions, with the interviewer's answers
- Which treatment does the new drug replace?Answer: The current standard treatment, costing GBP 5,000 per course.
- What threshold should I use?Answer: Assume GBP 35,000 per QALY, the upper end of the current range.
- Does the drug save other costs?Answer: Yes, fewer hospital days, worth about GBP 3,000 per patient.
A hypothesis to say out loud: The proposed price is 5.6 times the current treatment. My hypothesis is that the cost per QALY is above the threshold at that price and that a modest discount is needed to get approval.
The structure
- Cost per QALY versus the threshold
- Extra cost after offsets
- Key: Cost per QALY
- Maximum price at the threshold
- Revenue at that price
The exhibit
| Item | Current treatment | New drug |
|---|---|---|
| Price per course (GBP) | 5,000 | 28,000 |
| Hospital costs avoided (GBP) | 0 | 3,000 |
| QALYs gained versus current treatment | 0 | 0.5 |
Working it through
1. Extra cost per patient
New drug price minus current treatment minus hospital costs avoided.
Extra cost (GBP):28,000 - 5,000 - 3,000 = 20,0002. Cost per QALY
Extra cost divided by 0.5 extra QALYs: above the GBP 35,000 upper threshold.
Cost per QALY (GBP):(28,000 - 5,000 - 3,000) ÷ 0.5 = 40,0003. Maximum price at the threshold
Threshold times QALYs gained, plus the costs the drug replaces or avoids.
Maximum price (GBP):35,000 × 0.5 + 5,000 + 3,000 = 25,5004. Discount needed
From GBP 28,000 to GBP 25,500.
Discount (%):(28,000 - 25,500) ÷ 28,000 × 100 = 8.935. Patients treated
Half of 8,000 eligible patients.
Patients a year:8,000 × 0.5 = 4,0006. Revenue at the maximum price
4,000 patients at GBP 25,500.
Revenue (GBP a year):4,000 × 25,500 = 102,000,000
What the exhibit shows
The new drug gives real benefit and saves some hospital cost, but at GBP 28,000 its cost per QALY is above the current threshold range.
The recommendation
At GBP 28,000 the drug is unlikely to be approved, but a discount of about 9 percent, to about GBP 25,500, brings it within the GBP 35,000-per-QALY upper threshold. First, the cost per QALY at the list price is about GBP 40,000, above the current GBP 25,000 to 35,000 range. Second, at GBP 25,500 it sits at the upper threshold and could reach about 4,000 patients a year, about GBP 102 million of revenue, against nothing if rejected. Third, the hospital days it saves are a strong part of the value story and should be evidenced well. Offer the discount through a confidential agreement if the company wants to protect its list price in other countries.
Risks: The assessment may judge the QALY gain or hospital savings as lower than the trials suggest; A lower price in England may be used as a reference by other countries.
Next steps: Strengthen evidence on hospital days avoided; Prepare a pricing agreement with a discount of about 9 percent.
A strong candidate
Included cost offsets, calculated cost per QALY, found the maximum price at the threshold, and compared approval at a discount with rejection.
A weak candidate
Argued the price was fair because the drug is innovative, without calculating cost per QALY.
Worked case
Beds or shorter stays at an Indian private hospital
The prompt
A private hospital in Bengaluru has 320 beds and its emergency department is often full, with patients waiting for beds. Should it add beds?
Candidate-led: you drive; the interviewer answers what you ask.
Clarifying questions, with the interviewer's answers
- How many admissions a day, and how long do patients stay?Answer: About 60 admissions a day, with an average stay of 5 days.
- How is the hospital paid?Answer: Most admissions are paid a fixed package price per procedure by insurers, not per day.
- What does a bed cost to add, and what does a bed-day cost to run?Answer: About INR 12 million (1.2 crore) per new bed; about INR 8,000 per bed-day in variable costs.
A hypothesis to say out loud: With package prices, shorter stays cost less without lowering revenue. My hypothesis is that shortening stays is cheaper and faster than building beds.
The structure
- Occupied beds = admissions x length of stay
- Occupancy today versus an 85 percent target
- Option A: add beds
- Key: Option B: shorten stays
Working it through
1. Occupied beds
Candidate: "By Little's Law, average occupied beds are admissions per day times length of stay."
Average occupied beds:60 × 5 = 3002. Occupancy today
Candidate: "That is about 94 percent of 320 beds, well above the 85 percent that leaves room for peaks. That explains the emergency waits."
Occupancy (%):60 × 5 ÷ 320 × 100 = 93.753. Beds needed at 85 percent
Candidate: "To bring occupancy to 85 percent with today's stays, the hospital needs:"
Beds needed:60 × 5 ÷ 0.85 = 3534. Cost of option A
About 33 more beds at INR 12 million each.
Cost of new beds (INR):(353 - 320) × 12,000,000 = 396,000,0005. Option B: shorter stays
Interviewer: "Faster discharge planning could cut the average stay to 4.5 days." Candidate: "Then occupancy becomes:"
Occupancy at 4.5 days (%):60 × 4.5 ÷ 320 × 100 = 84.386. Money effect of option B
Candidate: "With package prices, revenue per patient stays the same. Each patient stays half a day less, and each bed-day avoided saves INR 8,000 of variable cost: 60 x 365 x 0.5 x 8,000."
Yearly cost saved (INR):60 × 365 × 0.5 × 8,000 = 87,600,000
The recommendation
Shorten stays before adding beds. First, the problem is occupancy of about 94 percent, and cutting the average stay from 5 to 4.5 days brings it to about 84 percent, within the 85 percent target, with no construction. Second, because insurers pay a fixed package per procedure, shorter stays do not reduce revenue and save about INR 8.8 crore a year in running costs. Third, adding beds would cost about INR 40 crore and take years. Keep a bed expansion plan ready if admissions keep growing.
Risks: Discharging too early could raise readmissions and harm patients; Admissions may grow faster than expected.
Next steps: Introduce daily discharge planning and weekend discharges; Track length of stay, readmissions, and emergency waiting times weekly.
A strong candidate
Used Little's Law to find the occupancy problem, asked how the hospital is paid, and chose the faster, cheaper lever while watching patient safety.
A weak candidate
Recommended building beds because the hospital "is full," without checking length of stay or the payment model.
Prompt: "At what price should we launch this drug?"
Weaker answer
Prices off development cost or competitor drugs in other countries, ignoring how the payer decides.
Stronger answer
Asks what the drug replaces and how the payer judges value, calculates cost per QALY with cost offsets, and finds the maximum price at the threshold.
Why the stronger answer wins: The strong answer follows the payer's decision rule. The weak one prices as if the patient were the buyer.
Common mistakes, traps, and curveballs
- Assuming the patient is the buyer
- Forgetting cost offsets (hospital days avoided)
- Planning beds at 100 percent occupancy
- Ignoring how the payment model changes incentives
- Treating health outcomes as secondary
Healthcare cases are common, and firms with large life-sciences and healthcare practices may expect you to handle basic terms such as payers, providers, and QALYs. Define terms as you use them. Formats differ by office and change over time, so check the current process for your target office.
Practice
A treatment costs EUR 12,000 more than the current one and adds 0.4 QALYs. What is its cost per QALY, in EUR?
A hospital in Abu Dhabi admits 40 patients a day with an average stay of 6 days. How many beds are occupied on average?
A UAE insurer covers 200,000 members. 8 percent have diabetes, each costing AED 12,000 a year. A program cuts their costs by 10 percent. What is the yearly saving, in AED?
What does a cost per QALY of GBP 40,000 mean?
Admissions are 50 a day and the average stay is 4 days. How many beds does the hospital need for about 85 percent occupancy?
A hospital is paid per day of stay. How does that change the case for shorter stays?
Follow the money: find who pays and how they judge value, then use the right measure, such as cost per QALY or occupied beds, to size the answer.
Sources for this lesson (1)
- Recognized public explanations of case-interview concepts and frameworks
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