📊 Practice Health Overview
📅 Active Care Plans
47
38 on-track | 9 at-risk
▼ 3 lapsed this week
💰 Monthly Collected Revenue
$38,240
Insurance: $22,100 | Cash: $16,140
▲ 6.4% vs last month
⚠️ No-Show Rate (7-Day)
18.3%
Industry avg: 12% | Cost: ~$2,100
▲ Up from 14% last week
📉 Patient Visit Decay Curve — Live Risk Scoring
Active Patient Risk Board
On-Track
Slipping
Lapsing
Decay score = days since last visit ÷ prescribed visit frequency × plan compliance rate. Updated every 6 hours.
Marcus T.
Day 4
On Schedule
Sandra K.
Day 6
On Schedule
Jerome W.
Day 11
Send Reminder
Patricia M.
Day 13
Send Reminder
Darnell C.
Day 19
Call Now
Brenda F.
Day 31
Lapsed
📌 SE_Watch Insight: Week 4 is your highest-risk dropout gate. Patients who skip their Week-4 visit have a 74% probability of not completing their care plan. Automated reactivation sequence fires at Day 10 of missed visits.
Dropout Risk by Visit
% of patients who lapse at each visit milestone
● Visit 4: 44% of lapsed patients — critical gate
● Visit 8: 36% of remaining — second choke point
● Visit 16: 30% of long-term patients — maintenance gate
📋 Care Plan Compliance Engine
Active Care Plans — Compliance & Revenue at Risk
Total plan value: $48,200
PatientPlan TypeCompliance%At Risk
Marcus T.
Auto injury rehab · 24 visits · $3,200
88%
$384
Sandra K.
Chronic care · 36 visits · $4,800
79%
$1,008
Jerome W.
Neck/shoulder · 20 visits · $2,600
55%
$1,170
Darnell C.
Lumbar rehab · 30 visits · $3,900
33%
$2,613
Brenda F.
Whiplash recovery · 18 visits · $2,340
17%
$1,942
⚠️ $7,117 in committed plan revenue is currently at risk due to compliance gaps. Signal Engine's automated care plan check-in sequences reduce dropout by 38% on average.
💳 Payer Mix Optimization + No-Show Pattern Analysis
Insurance vs Cash-Pay Mix
Cash-Pay
38%
Avg LTV: $2,840 · Margin: 78%
Insurance
45%
Avg LTV: $2,020 · Margin: 52%
Medicare
17%
Avg LTV: $1,480 · Margin: 38%
💡 Opportunity: Shifting 10% of new intakes from insurance to cash-pay membership generates an est. +$8,200/yr in retained margin with zero billing lag.
No-Show Heatmap — By Day × Time Block
Darker cell = higher no-show rate. Click any cell to trigger automated reminder sequence.
Mon
Tue
Wed
Thu
Fri
Sat
8–10am
8%
6%
7%
6%
12%
19%
11am–1pm
15%
9%
17%
7%
24%
28%
2–4pm
9%
6%
13%
8%
11%
16%
4–6pm
22%
14%
19%
11%
31%
—
🔴 Friday afternoon + Saturday AM = highest no-show risk. SE sends dual-channel reminders 48hr + 2hr before these slots.
🔄 Reactivation Window Intelligence
Lapsed Patient Reactivation Probability Engine
23 lapsed patients · Est. recoverable value: $41,8000–30 Days
74%
Auto text sequence
31–60 Days
61%
Personalized outreach
61–90 Days
42%
Offer + follow-up
91–180 Days
18%
Re-exam offer
180+ Days
7%
Loss — new intake req
PatientLast VisitLapsedProbEst. Value
Tanya R.
May 14, 2025
29 days
71%
$2,100
Send Reactivation
Kevin S.
May 8, 2025
35 days
63%
$1,840
Send Reactivation
Denise A.
Apr 22, 2025
49 days
48%
$2,400
Send Reactivation
Robert M.
Apr 1, 2025
70 days
39%
$1,560
Send Reactivation
Latoya B.
Feb 14, 2025
115 days
16%
$980
Low Priority
🔬 SE_Watch — Behavioral Signal Monitoring
Practice-Level Risk Signals — Updated Every 6 Hours
Contact Response Gap Detected
7 patients have not responded to last reminder. Average gap: 4.2 days. Signals cancellation intent or disengagement from care plan.
Risk: HIGH
Insurance Billing Lag Alert
3 claims pending over 35 days with no adjudication. Average write-off risk at 45-day threshold: $3,200. Escalation recommended.
Risk: HIGH
Pre-Book Rate Below Threshold
Only 54% of patients pre-booked next appointment at checkout. Practices with 80%+ pre-book rate reduce no-shows by 29%. Currently leaving 12 open slots unscheduled.
Risk: MED
Adjunct Service Attach Rate Low
Massage therapy, decompression, and rehab services at 18% attach rate vs 31% benchmark. Estimated lost margin per month: $1,840.
Risk: MED
Outcome Reporting Compliance
Patients who receive outcome progress updates at Visit 4 retain 2.4x longer. Currently 71% of patients receive Visit-4 outcome check — above 65% benchmark.
Signal: GOOD
Google Review Request Timing
Review requests sent at Visit 6 convert 3.1x higher than post-discharge. 0 of 8 eligible Visit-6 patients received review prompts this week.
Opportunity
💸 Revenue Leakage Engine — Chiropractic-Specific
$71,400
Estimated Annual Revenue Leakage Identified
No Visit-Frequency Re-Engagement System
Without decay-triggered outreach, practices lose an avg 22% of active care plan value to early dropout. At your volume, this equals $29K/yr in incomplete plan revenue.
$29,000
Cash-Pay Adjunct Under-Utilization
Decompression, massage, dry needling offered at 18% attach vs 34% average for practices your size. High-margin services not systematically recommended at checkout.
$22,100
Insurance Billing Timing Gaps
Claims submitted avg 4.1 days post-visit vs best practice 24-hour submission. Late submission increases denial rate by 18%. Estimated write-offs: $12,400/yr.
$12,400
No Lapsed-Patient Reactivation Workflow
23 lapsed patients with recoverable value above $1K each. At 42% success rate for 60-day window, est. $7,900 recoverable with systematic outreach.
$7,900
👩⚕️ Provider Utilization Intelligence
Provider Performance — Revenue per Hour + Utilization Rate
Practice target: 78% utilization · $180/hr
ProviderTypeUtilization%Rev/HourMonthly Rev
Dr. Wilson
DC · Primary
84%
$214/hr
$18,200
Dr. Chen
DC · Associate
71%
$188/hr
$12,400
Maria L.
Massage Therapist
48%
$92/hr
$4,140
James K.
Rehab Specialist
38%
$78/hr
$3,500 Under-Utilized
💡 Maria and James combined represent $8,200/mo in unfilled capacity. SE_Watch recommendation: bundle massage + adjustment packages to cross-promote both providers at checkout.
🛠️ Chiropractic Intelligence Toolkit
Visit Decay Forecaster
Models each patient's probability of dropout at Visit 4, 8, and 16 based on appointment gap history, complaint severity, and payer type. Triggers automated outreach at Day 7, 10, and 14 post-missed visit.
⚡ Live Scoring
Payer Mix Revenue Optimizer
Models your current insurance vs cash-pay vs Medicare split, calculates true margin per payer type including billing overhead, and identifies the optimal intake mix for your overhead structure.
📊 Revenue Modeling
Reactivation Window Scorer
Assigns each lapsed patient a probability-of-return score based on days since last visit, complaint type, plan completion %, and response history. Generates personalized outreach copy for each segment.
📩 Auto-Sequences
No-Show Pattern Analyzer
Identifies your highest no-show risk slots by day, time block, provider, and appointment type. Auto-triggers dual-channel (SMS + email) reminders 48hr and 2hr before high-risk slots.
🔔 Automated Reminders
Care Plan Compliance Engine
Tracks every active care plan's visit compliance in real-time. Surfaces revenue at risk from incomplete plans, flags patients showing non-compliance patterns before the plan fully lapses.
⚠️ Risk Detection
Outcome-Based Retention Trigger
Patients who receive outcome progress reports at Visit 4 retain 2.4x longer. This tool auto-generates personalized progress summaries at the V4 checkpoint and prompts in-office outcome discussions.
🧠 Retention Science
Why this cannot be replicated with ChatGPT
Generic AI can tell you what visit decay curves are. Signal Engine models yours — tracking every patient's decay stage in real time, scoring their reactivation probability based on actual behavioral signals from your practice, and firing outreach at the mathematically optimal moment. This is proprietary intelligence infrastructure, not a template.
✦
Chiropractic-Specific Dropout Model
Trained on the statistical reality that 62% of chiropractic patient churn concentrates at Visit 4, 8, and 16 — not a generic retention model, but a decay curve built specifically for this billing cadence and care plan structure.
✦
Live Reactivation Probability Engine
Each lapsed patient gets a probability-of-return score that degrades by the day. The 90-day window model (74% vs 7% return rate) isn't available anywhere else — it's a behavioral intelligence layer built into your patient list.
✦
No-Show Heatmap with Auto-Response
The no-show heatmap isn't static reporting — it identifies your specific high-risk slots and fires automated dual-channel reminders pre-emptively. No EHR has this built in. No generic CRM knows your clinic's pattern.
✦
Payer Mix Margin Modeling
The optimizer models actual margin — not just revenue — accounting for billing overhead, denial rate by payer, and collection lag. It produces a practice-specific optimal intake mix recommendation, not an industry average.
Start recovering lapsed revenue this week
Connect your practice data and Signal Engine will identify every at-risk patient, lapsed plan, and billing gap within 24 hours.