Insurance Spread Analysis — Alleviate Pain and Spine
Snapshot date 2026-05-05 · Generated 2026-05-05 13:56
626
Active patients (completed or scheduled)
490
Future-scheduled visits
12
Patients with real payer switch
1. Insurance Change
The practice has been Medicare-dominant since opening. Commercial share is gradually growing as the practice matures. Hover any line to see month-by-month detail.
2. Same data, 100% stacked view
Same monthly mix, presented as 100% stacked columns. Cleaner edges than a stacked area; easier to read absolute month-to-month proportions.
3. Volume growth
The practice scaled from 59 completed visits in July 2025 to 405 in April 2026 — a ~7× increase. The dotted line shows the monthly total.
4. Year-over-year shift
One slide, one number per payer: 2025 share → 2026 share. Commercial up +8.2pp, Medicare down -7.9pp, VA up +4.0pp.
5. Self-Pay reality check
Self-Pay registrations averaged ~15% of new patients in 2025. Self-Pay billed visits averaged only ~6%. The shaded gap represents patients who registered as Self-Pay (placeholder prior to appointment) but were billed under their actual insurance once the visit occurred.
6. Patient retention
Only ~23% of patients who registered as Self-Pay are active vs. ~80% for insured cohorts.
7. Payer flow (Sankey)
Flow of patients from registration → first visit → last visit, colored by payer at registration. Most flows are stable (same bucket throughout); divergent ribbons are the 12 patients with real switching.
8. Provider-level mix
Each row is a provider; bars sum to 100% of that provider's completed visits. Useful for spotting providers with atypical payer mixes (e.g., a heavily commercial vs. heavily Medicare panel).
9. Days to first visit
How fast does the average patient go from registration to their first completed visit, by payer bucket? Shorter pipeline = faster cash collection. Wide tails on Self-Pay reflect the registration-to-billing lag while eligibility is verified.
10. Visit-type by payer
What does each payer's visit mix look like?
11. Registration → activation funnel (counts)
For each registration cohort, what happened? Three states: completed at least one visit (green) vs. only has a future-scheduled visit (amber, pending) vs. no encounter at all (gray, lost). The amber slice matters — those patients are still in the pipeline, not lost.
12. Registration → activation rate (%)
Same data, normalized as 100% stacked bars so its easier to read the activation rate per cohort regardless of cohort size.
13. NEW patient return rate
Of patients whose first completed visit was a NEW (initial consult), how many came back? Solid green line: any subsequent visit (completed or scheduled). Dashed dark-blue: returned AND already completed a follow-up. Caveat: most-recent cohorts have had less time to return — interpret right edge with care.
14. Visit-type trends (overlay)
Monthly completed-visit count for NEW, F/U, INJ, and Tele. Tele is mutually exclusive — Tele New + Tele F/U live in the Tele line, not in NEW or F/U. Hover any line to see exact counts.
15. Visit-type trends (small multiples)
Same data as #13 but each visit type gets its own panel so you can read the shape of each trend without overlap. Useful for spotting an INJ slowdown that a busy NEW line might mask.
16. Insurance carrier reference table
Every primary insurance value appearing in either file, with encounters, registrations, unique-patient counts, and the assigned bucket. Click any column header to sort. Use the filter box to search by carrier or bucket.
17. Visit-type counts by provider
Each row is a provider; bars show their completed-visit panel split by NEW · F/U · INJ · Tele (Nurse visits excluded). Total visits annotated to the right of each bar. Useful for comparing absolute provider productivity.