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We took the standard R-Keeper report package and they tailored it to us on top of that. It all just works.
Solutions
Business analytics for medical practices and clinics
A clinic's revenue is driven by occupancy: how many appointments fit into a working day, and how many actually happen. These reports show that by clinician, by room and by service.
Accounting vs analytics
Accounting
A clinic's revenue is driven by occupancy: how many appointments fit into a working day, and how many actually happen. The booking system has the diary and the accounts have the revenue; only joined together do they show what an empty slot costs.
Appointment schedulesService pricesMaterial costsInsurer payments = a single number?
Business analytics
Power BI analytics works that out automatically. The management reports show occupancy by clinician and by room, and the did-not-attend rate by day of the week and by clinician, so reminders are aimed where they are needed most.
Rivilė / FinvaldaPractice management system
Joined up overnight Room occupancy, week by week The figures worth watching
Clinician and room occupancy
How much of the working day is actually filled with appointments. It is the clinic's main revenue driver, and the one easiest to improve without spending anything.
Profitability by service
Revenue from a procedure less materials and clinician time. Some popular services earn considerably less than they appear to once materials are counted.
Did-not-attend rate
Every no-show is an empty slot in the diary. Broken down by clinician and day of the week, it shows where a reminder system would pay.
Revenue mix
Private payments, insurers and state-reimbursed services kept apart — they carry quite different margins and payment terms.
Patient return rate
How many patients come back, and how soon. For a clinic that matters more than the flow of new patients.
Average appointment value
Together with the number of appointments, it explains any change in revenue — more patients came, or they received more treatment.
How it looks in the report
How to read the report
01
Room occupancy
Clinician and room occupancy are shown with breaks and empty slots separated out. The difference between clinicians often runs to tens of percentage points — and it can be filled without spending anything.
02
No-shows and returns
The did-not-attend rate is given by clinician and day of the week, against the average. Next to it is the patient return rate at 1, 3, 6 and 12 months — a figure that matters more to a clinic than the flow of new patients.
03
Services and revenue
Profitability by service separates popularity from earnings: a frequently performed procedure can earn the least once materials are counted. The revenue mix keeps private payments, insurers and reimbursed services apart — they carry different margins and different payment terms.
Where the data comes from
- the practice management system (appointments, services, clinicians)
- the reception or booking system
- the accounting system
- insurer and reimbursement statements
Read access The connection is read-only — the reports read your data, change nothing, and never write back to your systems.
What people usually notice first
- 1 The usual finding is a difference in occupancy between clinicians and rooms that the diary does not show: one clinician is overloaded while the room next door stands empty for hours a day.
- 2 The second is that no-shows cluster on particular days or at particular hours. Reminders almost always solve it, and the effect on revenue shows within a month.
Analitika360 client stories
Data that helps you decide
See how companies like yours put Analitika360 reports to work in Power BI.
Where to start
Most people start with a ready-built report set, which connects to your accounting system within a few days, and add the industry-specific reports as a second stage. Describe your situation and we will tell you what would work best in your case.