Problem Definition
ClinicLine runs 12 walk-in urgent-care clinics across two fast-growing metro areas in the U.S. Southeast. Each clinic is open 8am to 8pm, seven days a week, and treats non-life-threatening problems such as infections, sprains, minor cuts and fevers. Each clinic has on-site X-ray and basic lab testing. Care is delivered mainly by nurse practitioners and physician assistants ("providers"), supported by medical assistants and front-desk staff.
Urgent care is now a large part of U.S. healthcare. The Urgent Care Association (UCA) counts about 15,300 urgent-care centers, which together see more than 185 million patient visits a year, and reports that the average center sees about 34 patients a day. The UCA puts the average urgent-care visit at about 56 minutes, compared with about 150 minutes for an emergency department visit.
ClinicLine is busier than average, with about 44 patients arriving per clinic per day. But its average "door-to-door" time (from walking in to walking out) has risen to 95 minutes, about 9% of arriving patients leave before being seen ("walkouts"), and its average online review rating has fallen from 4.4 to 3.7 stars in a year. The Chief Operating Officer has asked your team: Why are ClinicLine's patients waiting so long, and how can the network bring visit times close to the national average without a large increase in staffing costs?
Additional InformationAsk for dataInterviewer’s data
If asked, please share that:
- ClinicLine's net revenue is about $150 per completed visit (after insurer discounts); variable cost (supplies, tests) is about $25 per visit
- Network revenue is about $26 million a year
- Each clinic is staffed with 18 provider-hours per day; a provider can see about 2.5 patients per hour on average, including charting
- ClinicLine does not offer online check-in or pre-registration; all patients register at the front desk on arrival
- Providers are paid by the hour; the median U.S. nurse practitioner earns about $132,000 a year (about $64 per hour), and ClinicLine's fully loaded cost (with benefits) is about $83 per hour
- Local emergency departments are the main alternative for walkout patients
Question 1Structuring
How would you structure your analysis of why ClinicLine's patients wait so long?
Hint · Structuring
Build 3–4 branches that are specific to this client and question, not a generic framework. Check they don't overlap and together cover the problem.
Try it first, then checkCheck my answerModel answer
1. Demand
- a) Total patient arrivals per day and per clinic
- b) Arrival pattern by hour and day of week
- c) Mix of cases (simple vs. needing X-ray or lab tests)
2. Capacity
- a) Provider hours per day and patients per provider-hour
- b) Provider schedule by hour (when providers are actually on the floor)
- c) Support staff and exam rooms (can they keep providers busy?)
3. Process (patient journey)
- a) Registration and insurance check
- b) Waiting room time
- c) Triage and vital signs
- d) Waiting in the exam room
- e) Provider exam, X-ray or lab tests
- f) Discharge and payment
4. Tools and information
- a) Online check-in and wait-time display
- b) Pre-registration
What the interviewer is looking forInterviewer’s viewInterviewer’s view
A good candidate separates demand (how many patients arrive, and when) from capacity (how many patients the clinic can treat, and when) and from the process each patient goes through. A strong candidate explicitly considers timing: a clinic can have enough capacity over a full day but still build queues at peak hours. An excellent candidate breaks the patient journey into steps (registration, waiting, triage, provider exam, tests, discharge) and says they want to see where the minutes go.
Push back if the candidate goes straight to "hire more providers": "Before we spend money, how would we know whether we are short of staff or just have staff at the wrong times?"
So What? cascade:
- Level 1: long waits come from demand being higher than capacity
- Level 2: in walk-in care, demand is uneven across the day, so the question is whether capacity matches demand hour by hour, not just in total
- Level 3: if total capacity is enough but peaks are uncovered, the fix is rescheduling and smoothing demand, which costs far less than hiring
Question 2Numeracy
Exhibit 1 shows a typical weekday at a ClinicLine clinic. Does ClinicLine have too few providers, or are they working at the wrong times?
Hint · Numeracy
Write the formula before you plug in numbers, keep units and zeros explicit, and sanity-check the order of magnitude at the end.
Exhibit 1Typical Clinic Day, Arrivals and Provider Schedule
| Time block | Hours in block | Patient arrivals | Providers on duty (current schedule) |
|---|---|---|---|
| 8am-10am | 2 | 9 | 1 |
| 10am-12pm | 2 | 6 | 2 |
| 12pm-2pm | 2 | 6 | 2 |
| 2pm-5pm | 3 | 7 | 2 until 4pm, then 1 |
| 5pm-8pm | 3 | 16 | 1 |
| Total | 12 | 44 | 18 provider-hours |
Current schedule: Provider 1 works 8am-8pm (12 hours); Provider 2 works 10am-4pm (6 hours).
Source: ClinicLine case file
Additional InformationAsk for dataInterviewer’s data
- Share Exhibit 1
- If asked: weekends follow a similar pattern with slightly fewer patients
- If asked: assume each provider sees 2.5 patients per hour
Try it first, then checkCheck my answerModel answer
Step 1: Capacity vs. demand by block (current schedule)
| Time block | Provider-hours | Capacity (x 2.5) | Arrivals | Gap |
|---|---|---|---|---|
| 8am-10am | 1 x 2 = 2 | 5 | 9 | -4 |
| 10am-12pm | 2 x 2 = 4 | 10 | 6 | +4 |
| 12pm-2pm | 2 x 2 = 4 | 10 | 6 | +4 |
| 2pm-5pm | 2 x 2 + 1 x 1 = 5 | 12.5 | 7 | +5.5 |
| 5pm-8pm | 1 x 3 = 3 | 7.5 | 16 | -8.5 |
| Total | 18 | 45 | 44 | +1 |
Step 2: Interpret
- Over the whole day, capacity (45) is slightly above demand (44), so the clinic is not short of providers
- Spare capacity of 13.5 patients (4 + 4 + 5.5) sits between 10am and 5pm, when fewer patients arrive
- In the evening, 16 patients arrive but only 7.5 can be seen, a gap of 8.5 patients. The queue builds all evening, which is when most walkouts happen
Step 3: A better schedule with the same 18 provider-hours
- Provider A: 8am-2pm (6 hours)
- Provider B: 2pm-8pm (6 hours)
- Provider C: 8am-11am (3 hours, morning peak)
- Provider D: 5pm-8pm (3 hours, evening peak)
| Time block | Providers | Capacity | Arrivals | Gap |
|---|---|---|---|---|
| 8am-10am | 2 | 2 x 2 x 2.5 = 10 | 9 | +1 |
| 10am-12pm | 2 until 11am, then 1 | (2 + 1) x 2.5 = 7.5 | 6 | +1.5 |
| 12pm-2pm | 1 | 2 x 2.5 = 5 | 6 | -1 |
| 2pm-5pm | 1 | 3 x 2.5 = 7.5 | 7 | +0.5 |
| 5pm-8pm | 2 | 2 x 3 x 2.5 = 15 | 16 | -1 |
| Total | 45 | 44 |
The largest gap falls from 8.5 patients to 1 patient, at no additional cost. Part-time 3-hour shifts can be filled with per-diem (on-call) providers, which is common in urgent care.
What the interviewer is looking forInterviewer’s viewInterviewer’s view
The candidate should calculate capacity per block (providers x hours x 2.5) and compare it with arrivals. The key insight is that total daily capacity (45 patients) is above total demand (44 patients), but capacity is in the wrong place: there is a large shortfall in the morning and evening and spare capacity in the middle of the day.
If the candidate only compares daily totals, prompt: "Is there enough capacity at 6pm?"
A strong candidate will propose a new schedule with the same 18 provider-hours.
So What? cascade:
- Level 1: ClinicLine has enough provider-hours in total: it needs about 44 / 2.5 = 17.6 hours and has 18
- Level 2: capacity is placed in the middle of the day, while demand peaks in the morning and after work
- Level 3: reshaping the schedule fixes most of the problem at no extra cost
Question 3Judgement & Insights
The COO also commissioned a time study of the patient journey (Exhibit 2) and a breakdown of waiting times by arrival time (Exhibit 3). What else do these tell you?
Hint · Judgement & Insights
Read the exhibit title, axes and units first. Lead with the ‘so what’, then back it with one or two numbers.
Exhibit 2Average Patient Journey at ClinicLine (minutes)
| Step | Minutes | Type |
|---|---|---|
| Registration at front desk | 12 | Administration |
| Waiting room | 36 | Waiting |
| Triage and vital signs | 7 | Care |
| Waiting in exam room for provider | 15 | Waiting |
| Provider exam and treatment | 14 | Care |
| X-ray or lab tests (averaged across all patients) | 6 | Care |
| Discharge and payment | 5 | Administration |
| Total door-to-door | 95 |
Source: ClinicLine case file
Exhibit 3Waiting-Room Time and Walkouts by Arrival Time
| Arrival time | Patient arrivals | Avg. waiting-room time (minutes) | Share of daily walkouts |
|---|---|---|---|
| 8am-10am | 9 | 43 | 25% |
| 10am-12pm | 6 | 12 | 5% |
| 12pm-2pm | 6 | 12 | 5% |
| 2pm-5pm | 7 | 10 | 0% |
| 5pm-8pm | 16 | 62 | 65% |
Source: ClinicLine case file
Additional InformationAsk for dataInterviewer’s data
- Share Exhibits 2 and 3
- If asked: the time study tracked 600 patients across 4 clinics over two weeks
- If asked: registration includes filling in a paper form and scanning an insurance card
Try it first, then checkCheck my answerModel answer
1. Where the 95 minutes go
| Type | Steps | Minutes | Share |
|---|---|---|---|
| Care | Triage 7 + exam 14 + tests 6 | 27 | 28% |
| Waiting | Waiting room 36 + exam room 15 | 51 | 54% |
| Administration | Registration 12 + discharge 5 | 17 | 18% |
| Total | 95 | 100% |
2. Waiting depends on when patients arrive
- Check the average waiting-room time, weighted by arrivals: (9 x 43 + 6 x 12 + 6 x 12 + 7 x 10 + 16 x 62) / 44 = (387 + 72 + 72 + 70 + 992) / 44 = 1,593 / 44 = about 36 minutes, consistent with Exhibit 2
- Patients arriving between 5pm and 8pm wait 62 minutes in the waiting room alone, and that period accounts for 65% of walkouts
- Mid-day patients wait only 10-12 minutes: the clinic performs well when capacity matches demand
3. Administration is a second, cheaper lever
- 12 minutes for registration is long for a returning patient; online pre-registration could cut it to about 4 minutes, saving about 8 minutes per visit
- Online check-in ("save my spot") lets patients wait at home and see live wait times, which moves some evening demand to quieter hours
4. Implication
The problem is timing, not total staffing. After rescheduling providers, cutting waiting-room time at peaks and shortening registration, a realistic target is a door-to-door time of about 60 minutes, close to the national average of about 56 minutes.
What the interviewer is looking forInterviewer’s viewInterviewer’s view
The candidate should group the journey into care, waiting and administration. The key finding is that patients spend only about 27 minutes (less than a third of the visit) receiving care, while waiting takes more than half. Exhibit 3 confirms Question 2: waits and walkouts are concentrated in the morning and evening peaks. A strong candidate also spots the 12-minute registration step: this can be shortened with online check-in and pre-registration, which also lets patients wait at home.
So What? cascade:
- Level 1: 51 of 95 minutes (54%) is waiting
- Level 2: 90% of walkouts happen in the two peak periods, the same periods where Question 2 showed the capacity gap
- Level 3: fixing the schedule reduces waiting; online check-in cuts registration time and spreads demand, since patients can see the wait and choose a quieter time
Question 4Synthesis
The COO has two proposals on the table: (1) the rescheduling and online check-in plan, or (2) adding a fifth provider shift of 4 hours every evening at every clinic. What do you recommend?
Hint · Synthesis
Answer first: the recommendation, two or three reasons with numbers, then risks and next steps.
Additional InformationAsk for dataInterviewer’s data
- Online check-in and pre-registration software costs about $30,000 per clinic per year
- Both proposals are expected to reduce walkouts from about 4 per clinic per day to about 1
- The COO asks for the financial case as well as the patient case
Try it first, then checkCheck my answerModel answer
1. Value of fewer walkouts (same for both proposals)
- Walkouts avoided: 4 - 1 = 3 patients per clinic per day
- Revenue: 3 x $150 x 365 days x 12 clinics = about $1.97M per year
- Contribution after variable costs: 3 x ($150 - $25) x 365 x 12 = about $1.64M per year
2. Cost of each proposal
- Proposal 1: rescheduling costs nothing extra (same 18 provider-hours); software costs $30,000 x 12 = $0.36M per year
- Proposal 2: 4 hours x $83 x 365 days x 12 clinics = about $1.45M per year
3. Net benefit
| Proposal 1: Reschedule + online check-in | Proposal 2: Extra evening shift | |
|---|---|---|
| Contribution from fewer walkouts | $1.64M | $1.64M |
| Added cost | -$0.36M | -$1.45M |
| Net annual benefit | ~$1.28M | ~$0.19M |
4. Recommendation to the COO
ClinicLine should reschedule its providers to match patient arrivals and introduce online check-in and pre-registration across all 12 clinics.
- The problem is timing, not headcount. Each clinic has enough provider-hours (18) for its 44 daily patients, but too few in the morning and evening peaks, where 90% of walkouts happen
- Rescheduling is free and closes the evening gap from 8.5 patients to about 1
- Online check-in cuts registration time by about 8 minutes and spreads demand across the day
- Financially, the plan adds about $1.3M a year in net contribution, compared with about $0.2M for the extra-shift proposal
- Target: door-to-door time of about 60 minutes (national average about 56), walkouts below 3%, and a recovery in online ratings within 6 months
Risks and next steps:
- Providers may resist split or short shifts: pilot the new schedule in 3 clinics and use per-diem providers for the 3-hour peak shifts
- The evening remains tight (capacity 15 vs. 16 arrivals): if walkouts stay high in a clinic after 3 months, add a shorter evening shift there only, rather than across all 12 clinics
- Track door-to-door time, walkouts by hour and review ratings weekly for each clinic
What the interviewer is looking forInterviewer’s viewInterviewer’s view
The candidate should calculate the revenue recovered from fewer walkouts and compare the cost of each proposal. A good candidate finds that both proposals recover the same revenue. A strong candidate shows that proposal 1 costs a fraction of proposal 2. An excellent candidate recommends proposal 1, keeps proposal 2 as a fallback for clinics where the evening gap remains, and sets targets (door-to-door time, walkout rate, rating) to track.
Data Sources
Company figures for ClinicLine are fictional. Market facts below come from public sources and are rounded for interview math.
- About 15,300 (15,274) urgent-care centers in the U.S.; more than 185 million patients treated a year in urgent care -> Urgent Care Association, "Urgent Care Data", accessed 2026, https://urgentcareassociation.org/about/urgent-care-data
- Average of about 34 (33.96) patients per day per urgent-care center in 2025, up from 33.13 in 2023 -> Urgent Care Association, "Urgent Care Data", accessed 2026, https://urgentcareassociation.org/about/urgent-care-data
- Average urgent-care visit time of about 56 minutes, against about 150 minutes for an emergency department visit -> Urgent Care Association, "Urgent Care Data", accessed 2026, https://urgentcareassociation.org/about/urgent-care-data
- Median annual wage for U.S. nurse practitioners of about $132,000 ($132,300, May 2025), about $64 per hour on a 2,080-hour year -> U.S. Bureau of Labor Statistics, "Occupational Outlook Handbook: Nurse Anesthetists, Nurse Midwives, and Nurse Practitioners", 2026, https://www.bls.gov/ooh/healthcare/nurse-anesthetists-nurse-midwives-and-nurse-practitioners.htm
- Urgent-care visits generally cost far less than emergency room visits for the same non-emergency care (illustrative in-network example: $300 provider fee at urgent care vs. $1,000 at the ER); used as the basis for ClinicLine's $150 net revenue per visit after insurer discounts -> FAIR Health Consumer, "Emergency Care and Urgent Care", accessed 2026, https://www.fairhealthconsumer.org/insurance-basics/healthcare/emergency-care-and-urgent-care
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