B
Long-Term Care Grade Change Response Coach
3.20
Derivation Chain
Step 1
Parent care administration & cost planning
→
Step 2
Long-term care grade application & assessment
→
Step 3
Responding to benefit and cost changes from grade upgrades/downgrades
Problem
When parents in their 80s have their long-term care grade upgraded from Grade 3 to Grade 2, or downgraded to Grade 4, the benefit limits, co-payments, and available services change significantly — but families don't find out until after the change. Only upon receiving the grade change notification do they discover that their existing care facility hours or home visit care time has been reduced, forcing a frantic search for alternatives. Missing the 60-day appeal deadline is also common.
Solution
Enter the current care grade and services in use (home care/day-night care/facility admission) on the web, and the system simulates in advance how benefit limits, co-payments, and available services would change if the grade moves up or down by one level. When a grade change notification arrives, it provides an appeal checklist with deadline reminders and recommends the optimal service combination for the new grade.
NUMR-V Scores
NUMR-V Scoring System
| N Novelty | 1-5 | How uncommon the service is in market context. |
| U Urgency | 1-5 | How urgently users need this problem solved now. |
| M Market | 1-5 | Market size and growth potential from proxy indicators. |
| R Realizability | 1-5 | Buildability for a small team with realistic constraints. |
| V Validation | 1-5 | Validation signal quality from competition and demand data. |
SaaS N=.15 U=.20 M=.15 R=.30 V=.20
Senior N=.25 U=.25 M=.05 R=.30 V=.15
Feasibility (73%)
Data Availability
18.8/25
Feasibility Breakdown
| Tech Complexity | / 40 | Difficulty of core implementation stack. |
| Data Availability | / 25 | Practical availability and cost of required data. |
| MVP Timeline | / 20 | Expected time to ship a usable MVP. |
| API Bonus | / 15 | Bonus for viable public API leverage. |
Market Validation (55/100)
Validation Breakdown
| Competition | / 20 | Signal quality from competitor landscape. |
| Market Demand | / 20 | Demand proxies from search and mention patterns. |
| Timing | / 20 | Fit with current shifts in tech, behavior, and regulation. |
| Revenue Signals | / 15 | Reference evidence for monetization viability. |
| Pick-Axe Fit | / 15 | How well the concept serves participants in a trend. |
| Solo Buildability | / 10 | Practicality for lean-team implementation. |
Technical Requirements
Frontend [low]
Backend [medium]
Data Pipeline [low]