Footfall near hospitals and clinics: reading a place that never closes

Footfall around a hospital looks unlike footfall anywhere else: it stays high through the night, peaks at shift changes and visiting hours rather than lunch, and barely drops at the weekend. That pattern is the useful part. It tells a pharmacy, a cafe, a car park operator or a transport planner when the people around the hospital are there and for how long. What footfall cannot tell you is how many patients the hospital sees: it measures people-hours of presence, and a nurse on a twelve-hour shift counts for more of it than a patient in for a blood test.

This is for businesses that serve the people around healthcare sites (pharmacies, food and coffee, florists, medical supply shops, parking and taxi services) and for health planners comparing clinics. It covers how to measure, how to read a healthcare pattern, a worked example in Mexico City, and an AI employee that keeps the picture current.

Who makes up the footfall around a hospital

• Staff. Often the largest group. Long shifts mean each person adds many people-hours. Shift changes, typically early morning and evening, show up as peaks.
• Inpatients. People staying in the hospital are present all day and night. They raise the late-night figure but rarely buy anything outside.
• Outpatients and their companions. Mostly weekday daytime. They wait, eat and fill prescriptions: the customers for a nearby pharmacy or cafe.
• Visitors. Concentrated in visiting hours, often in the afternoon and early evening, and at weekends.

A clinic without beds is different again: its footfall follows its opening hours, close to an office pattern, with little at night.

How to read the figures

The late-night share

Mobility Footfall splits the day into morning (6:00 to 12:00), midday (12:00 to 16:00), evening (16:00 to 21:00) and late night (21:00 to 6:00). Around most shops the late-night share is small. Around a large hospital it stays high, because staff and inpatients are there. A high late-night share is a sign that a business open at night has customers, but only those who leave the building.

The busiest hour

Around a hospital it often falls at a shift change or in visiting hours, not at lunch. For a cafe, that is when to have staff at the counter; for a car park, when spaces run out.

Weekday against weekend

The block can measure weekdays only or weekends only. Clinics and outpatient departments drop sharply at the weekend; emergency hospitals much less. Comparing the two tells you how much of a site's activity is planned appointments.

A worked example in Mexico City

The figures below are made up. A pharmacy group wants to open next to a large public hospital and is weighing two units: one by the main entrance, one by the outpatient building on the other side of the site, 400 m away. It measures footfall within 150 m of each, over the last 30 days, weekdays and weekends separately.

Invented figures, for illustration only.

The main entrance is busier and steadier, but its 07:00 peak and high late-night share suggest much of it is staff arriving and inpatient wards. The outpatient side is quieter overall and almost empty at weekends, yet its peak at 10:00 on weekdays is exactly when people leave appointments with prescriptions. The group picks the outpatient unit for a daytime pharmacy and checks with the hospital whether prescriptions are filled on site, which footfall cannot show.

Before deciding, it also counts the pharmacies already within 300 m of each unit with Nearby places, since a quiet unit with no rival can beat a busy one with three.

Mistakes to avoid

• Reading footfall as patient numbers. It mixes staff, patients and visitors weighted by how long each stays. A hospital's own activity figures are the source for patient numbers.
• Using a wide radius on a big campus. A 500 m circle around a hospital can include a metro station, a university or housing. Measure close to the door you care about, and measure several doors separately.
• Comparing a hospital with a clinic directly. One runs around the clock and the other keeps office hours. Compare like with like, or compare the parts of the day.
• Expecting the night shift to shop. A high late-night share is mostly people inside the building. Night trade depends on whether they can and do step out.

Doing it with an AI employee

Health sites are many and spread out. An AI employee can find them, measure them and tell you where the opportunity is each month.

1. Schedule, every month, and an Area of interest on the city.
2. Nearby places for hospitals and medical clinics in the area. Each comes with its position, rating and brand.
3. Mobility Footfall on each one, Around each place set to 150 or 200 m, Time window Last 30 days, with Footfall and Busy hours chosen under Return. Each site gets footfall_daily, its busiest hour and how the day splits.
4. A second Nearby places, Each incoming place with counts, for pharmacies (or cafes) within 300 m, so each site gets nearby_count.
5. Filter to keep sites with no more than one rival nearby, and Sort and limit by footfall_daily, highest first.
6. Email and Show on a map.

What lands in the inbox each month is a list of hospitals and clinics with how busy the area around each one is, when it peaks, how much happens at night and how many rivals are already there, with a map to plan visits from. A place with no footfall data yet says so and is left with empty figures rather than a guess.