Patient life cycle – past and present, over any period of time (filter). Want to be able to see trends, be able to see the bell curve to understand max, min, median, outliers etc.
- How many patients were booked?
- What’s the age group, ethnicity and gender distribution?
- What’s the insurance payer distribution?
- What’s the visit type distribution?
- What’s the appointment source distribution (referrals faxed/sent, website appt requests, call in for appt, walk in for appt, referring provider office called to make appt, ZocDoc, postcards mailed to them etc)
- How many patients confirmed – broken down by confirmation method (sms, call)?
- How many patients showed up?
- How many patients showed up that had confirmed their appt?
- How many patients showed up that had not confirmed their appt?
- How many patients that agents confirmed showed up?
- How many patients that confirmed via SMS showed up?
- How many patients that confirmed via SMS were called by agents?
- How many attempts before a patient actually confirms the appt?
- How many channels used to reach patients before the patient confirms the appt?
- How many patients that we left VM for actually show up?
- If a patient doesn’t answer the phone, do they confirm appt via text?
- How many patients booked from PCP referrals?
- How many patients booked from optometrist referrals?
- How many patients booked without a referral?
- How many patients were Medicare/Medicaid?
- How many patients were no show?
- How many no show patients were repeat no shows?
- What time of day do patients typically no show?
- What day of week do patients typically no show?
- What months of year do patients typically no show?
- How many patients rescheduled?
- How many reschedule patients were repeat reschedules?
- For reschedules – what times of appt do patients reschedule more?
- For reschedules – what days of week do patients reschedule more?
- For reschedules – what months do patients reschedule more?
- For reschedules – what’s the age group, ethnicity and gender distribution?
- How many patients cancelled?
- How many cancelled patients were repeat cancellations?
- For cancellations – what times of day do patients cancel more?
- For cancellations – what days of week do patients cancel more?
- For cancellations – what months do patients cancel more?
- For cancellations – what are the top reasons?
- For cancellations – what’s the age group, ethnicity and gender distribution?
- New visits vs follow ups
- How many patients were billed vs booked?
- How many billed patients actually leave a review?
- How many billed patients actually refer us new patients?
- Noshow trends
- Cancellation trends
- Visit type vs billed revenues/ type and overall billing distribution
- Visit types vs number of visit types
- How many appointment slots