Practice Analytics Questions

Categorized as Operations

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. 

  1. How many patients were booked?
  2. What’s the age group, ethnicity and gender distribution?
  3. What’s the insurance payer distribution?
  4. What’s the visit type distribution?
  5. 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)
  6. How many patients confirmed – broken down by confirmation method (sms, call)?
  7. How many patients showed up?
  8. How many patients showed up that had confirmed their appt?
  9. How many patients showed up that had not confirmed their appt?
  10. How many patients that agents confirmed showed up?
  11. How many patients that confirmed via SMS showed up?
  12. How many patients that confirmed via SMS were called by agents?
  13. How many attempts before a patient actually confirms the appt?
  14. How many channels used to reach patients before the patient confirms the appt?
  15. How many patients that we left VM for actually show up?
  16. If a patient doesn’t answer the phone, do they confirm appt via text?
  17. How many patients booked from PCP referrals?
  18. How many patients booked from optometrist referrals?
  19. How many patients booked without a referral?
  20. How many patients were Medicare/Medicaid?
  21. How many patients were no show?
  22. How many no show patients were repeat no shows?
  23. What time of day do patients typically no show?
  24. What day of week do patients typically no show?
  25. What months of year do patients typically no show?
  26. How many patients rescheduled?
  27. How many reschedule patients were repeat reschedules?
  28. For reschedules – what times of appt do patients reschedule more?
  29. For reschedules – what days of week do patients reschedule more?
  30. For reschedules – what months do patients reschedule more?
  31. For reschedules – what’s the age group, ethnicity and gender distribution?
  32. How many patients cancelled?
  33. How many cancelled patients were repeat cancellations?
  34. For cancellations – what times of day do patients cancel more?
  35. For cancellations – what days of week do patients cancel more?
  36. For cancellations – what months do patients cancel more?
  37. For cancellations – what are the top reasons?
  38. For cancellations – what’s the age group, ethnicity and gender distribution?
  39. New visits vs follow ups
  40. How many patients were billed vs booked?
  41. How many billed patients actually leave a review?
  42. How many billed patients actually refer us new patients?
  43. Noshow trends
  44. Cancellation trends
  45. Visit type vs billed revenues/ type and overall billing distribution
  46. Visit types vs number of visit types
  47. How many appointment slots

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