Visit volume is the heartbeat of an urgent care center, but the number that matters isn't total visits — it's whether those visits line up with the hours you're paying providers to be there. This dashboard puts daily volume, visits per center-day, and visits per provider-hour side by side with the times patients actually walk in, so staffing follows demand instead of last month's hunch.
What this dashboard answers
The overview answers the questions an operations lead asks every week: how many visits did each center see, how busy was an average open day, and how many patients did each clinical labor hour produce? Walk-in share and online check-in share show how patients are reaching you, and the peak-hour view exposes the late-morning and evening surges where the waiting room fills up. Together they tell you whether a slow shift is overstaffed or a busy one is underwater.
The metrics that matter
Visits per provider-hour is the throughput metric urgent care lives on — a healthy center usually runs in the low-single-digits of patients per provider-hour, and a number that sags points to overstaffing or a slow daypart. Visits per center-day normalizes volume so a four-day-week site and a seven-day site compare fairly. The arrival-hour heatmap by day of week is where the real scheduling decisions come from: it shows the exact windows where demand outruns staffing, and the slow mornings where a provider could start later.
Why the data is trapped
Visit counts live in Experity, eClinicalWorks, or athenahealth, but arrival channel and the timestamp detail you need to build an hour-by-day heatmap often sit in Solv or your check-in tool, not the PM report. The standard EMR reports give you a daily total, not visits-per-provider-hour by daypart — so operators export both and stitch them together in a spreadsheet that's stale the moment it's built. Roll several centers up and the manual work multiplies.
How to read it
Start with visits per provider-hour by center: the outliers tell you who is overstaffed and who is slammed. Then read the arrival heatmap against your actual schedule — the surge windows should have the most provider hours, and the cool corners (slow weekday mornings) are where to trim. Watch online check-in share over time as a leading indicator of how patients prefer to arrive.
The sample on this page uses entirely synthetic visit data — anonymized centers, no real patients or PHI.
Metrics it tracks
| Metric | What it means |
|---|---|
| Total Visits | Count of patient visits across all centers in the period — one row per visit. |
| Visits per Center-Day | Total visits ÷ the number of center-days the door was open — average daily volume per site. |
| Visits per Provider-Hour | Total visits ÷ provider hours staffed — throughput intensity per clinical labor hour. |
| Walk-in Share | Share of visits that arrived as unscheduled walk-ins rather than a reservation. |
| Online Check-in Share | Share of visits that used a digital reservation or check-in (Solv and the like). |
| Peak-Hour Visit Share | Share of visits arriving in the late-morning and evening surge windows. |
Used by: Regional operations directors and center managers matching provider hours to demand
Frequently asked questions
What is a good visits-per-provider-hour for an urgent care center?
Most urgent care operators target roughly two-and-a-half to four patients per provider-hour, depending on acuity, ancillary mix, and support staffing. Below that range usually signals overstaffing or a slow daypart; well above it can mean wait times and door-to-door times are about to suffer.
Why match staffing to arrival times instead of total volume?
Urgent care demand is spiky — it concentrates in late-morning and evening surges and on weekends. A center can hit its daily total while being badly overstaffed at 8am and underwater at 6pm. The arrival-hour-by-day heatmap shows exactly where provider hours should move.
Can I build this on my Experity or Solv data?
Yes. Export visit and arrival data from Experity, eClinicalWorks, or athenahealth, optionally with check-in detail from Solv, and use this as a template. We model it into a Power BI report; the sample here uses synthetic data so you can see the finished layout first.
Build this report on your own data
Clone this Urgent care template — describe it and we’ll generate sample data so you can try it free, or upload your own export. You get a fully modeled, branded Power BI project that opens in Power BI Desktop.
Use this as a template →