Portfolio census planning

Census growth simulator

Pick a facility and set the baseline numbers in the sidebar. The physics are simple: census always drifts toward monthly admits divided by the discharge rate.

Kipu, Salesforce and Patientize pulls, late July 2026

Plateau census

63

where growth stops at these rates

Census in 12 months

63

from 74 today

Net admits per month

-5.7

at today's census, full digital

Reaches target

Never

at these rates

Woburn, 24 month projection

stalls near 63
Every facility at its current baseline. Edit a baseline and this table updates.
Facility Census now Admits /mo Discharge rate Plateau In 12 mo Reaches target Verdict
How the model works, and what to keep in mind

Each month: new census = census + admits, minus discharges. Discharges = discharge rate x census. So census always drifts toward a plateau of admits divided by discharge rate, and growth requires admits to keep rising as census grows.

  • Every projection reads only from that facility's baseline: census now, referral admits, digital admits, discharge rate, and target.
  • Alumni, BD and other admits are grouped in a single figure because they are relationship capped and do not scale with ad spend. The shipped baseline holds them at their January to June average.
  • Other admits are the gap between Kipu admits and Salesforce attributed sources. Elevate's gap is about 14 per month and is worth reconciling before large spend decisions.
  • Digital admits are held flat at the sidebar value for the whole projection. Change that number to model a different run rate.
  • Elevate and Indiana each show one unusually heavy discharge month 60 to 90 days back. If that month is a data artifact, their true discharge rates sit at the low end of the noted Kipu range.
  • The model covers admissions only. Red Ribbon Indiana and Colorado also need capacity, staffing, and licensing headroom before their targets are physically possible.
  • The left sidebar holds the numbers behind each facility. Drag the sliders to model different rates live. Reset restores that facility's shipped July 2026 pull; clearing site data restores all of them.

Sources: Kipu census and discharge reports per facility, Salesforce admits by lead source, Patientize VOB performance.

Admits per month required to hold the target census once you get there, and the digital ad spend that implies. Yellow cells are editable. Census is from the Aug 2026 master overview; rates and CPA start from the scenario-range sheet.

Facility Census Target Alum+BD CPA base Realistic Optimistic
Rate% Admits Digital $/mo Rate% Admits Digital $/mo

What each scenario assumes

  • Realistic: each site’s current discharge rate and current cost per admit. No help, no extra penalty. Digital spend = (admits − Alumni − BD) × CPA.
  • Optimistic: rate eases ~8–15 pts (transfers stripped, retention/LOS improves); CPA −15% from conversion fixes and concentrating spend where it’s cheap. Digital spend = (admits − Alumni − BD) × CPA × 0.85.
  • Admits/mo = rate × target — the number needed to hold the target once there. Alumni & BD are held flat; digital covers the gap.
  • This sizes holding the target, not reaching it. Reaching it is the climb on the Growth projection view. Three mature sites peaked then unwound in 2026, so “can it be held at all” is still an open question above these numbers.
  • Targets: Woburn / Elevate / Mpower = 100; Red Ribbons = 50 near-term. Change any yellow cell and the range recalculates.

Sources: Scenario range sheet + Census growth MASTER overview (census as of Aug 2026). CPA from Patientize; rates from Kipu.