B

Parent's Care Grade Pre-Diagnosis

4.25

Derivation Chain

Step 1 Employment changes/economic insecurity in the AI era
→
Step 2 Increasing caregiving burden for the 50s sandwich generation
→
Step 3 Difficulty in determining the timing and preparation for elderly parents' long-term care grade application

Problem

A 52-year-old office worker with parents in their 80s misses out on benefits for months to years because they cannot determine the right time to apply for long-term care grade. The assessment criteria (52 items) are public, but difficult for the general public to understand, and there is no way to estimate in advance what grade their mother might receive. If the application is rejected, they must wait 6 months to reapply, so the loss from applying unprepared is significant. Currently, the only way is to informally ask a care worker or social worker.

Solution

On the web, (1) input the parent's daily living abilities through a simplified 15-question survey based on the 52 assessment items, (2) it presents the expected care grade and score range, (3) guides on items that must be included in the doctor's opinion to increase the likelihood of grade approval, and (4) compares available home-based and facility services and out-of-pocket costs by grade.

Target: Aged 48-58, supporting parents aged 75 or older, dual-income couples, office workers who sense their parents' health decline but are unfamiliar with the long-term care system.
Revenue Model: Simple grade diagnosis is free. Detailed diagnosis report (including doctor's opinion guide): 5,000 KRW (~$3.75) per transaction. When linked to nursing facility comparison and recommendation, a facility-side commission is charged.
Ecosystem Role: Education
MVP Estimate: 2_weeks

NUMR-V Scores

N Novelty
4.0/5
U Urgency
4.0/5
M Market
3.0/5
R Realizability
5.0/5
V Validation
4.0/5
NUMR-V Scoring System
N Novelty1-5How uncommon the service is in market context.
U Urgency1-5How urgently users need this problem solved now.
M Market1-5Market size and growth potential from proxy indicators.
R Realizability1-5Buildability for a small team with realistic constraints.
V Validation1-5Validation signal quality from competition and demand data.
Each dimension is scored 1-5 and weighted into grade S/A/B/C/D.
N=.15 U=.20 M=.15 R=.30 V=.20

Feasibility (73%)

Tech Complexity
32.0/40
Data Availability
20.8/25
MVP Timeline
20.0/20
API Bonus
0.0/15
Feasibility Breakdown
Tech Complexity/ 40Difficulty of core implementation stack.
Data Availability/ 25Practical availability and cost of required data.
MVP Timeline/ 20Expected time to ship a usable MVP.
API Bonus/ 15Bonus for viable public API leverage.
Total 100 points; below 50% is filtered out.

Market Validation (60/100)

Competition
8.0/20
Market Demand
6.2/20
Timing
16.0/20
Revenue Signals
10.5/15
Pick-Axe Fit
12.0/15
Solo Buildability
7.0/10
Validation Breakdown
Competition/ 20Signal quality from competitor landscape.
Market Demand/ 20Demand proxies from search and mention patterns.
Timing/ 20Fit with current shifts in tech, behavior, and regulation.
Revenue Signals/ 15Reference evidence for monetization viability.
Pick-Axe Fit/ 15How well the concept serves participants in a trend.
Solo Buildability/ 10Practicality for lean-team implementation.
Total 100 points; below 50 is filtered out.

Technical Requirements

Frontend [low] Backend [medium]
Dashboard