S

Post-Checkup 90-Day Follow-Up Coach

4.25

Derivation Chain

Step 1 Longitudinal interpretation of health checkup results
→
Step 2 Identifying abnormal items through trend analysis
→
Step 3 Not knowing which department to visit or when after discovering abnormal findings

Competitor references

No usable source links are available for this idea. Its signal notes and scores need independent verification.

Problem

45% of people in their 50s who receive abnormal findings on health checkups never follow up with detailed examinations (NHIS 2024 statistics). Even after getting a result like 'Findings: Abnormal liver function,' they don't know which department to visit (gastroenterology? hepatobiliary surgery?), how much the detailed exam costs, whether national health insurance covers it, or by when they should go. As a result, they miss early detection opportunities and discover worsened conditions at the next year's checkup.

Solution

(1) Enter abnormal checkup findings to get a breakdown of required follow-up exams by item, which department to visit, estimated cost (with national insurance coverage), and recommended deadline, (2) auto-generate a 90-day follow-up calendar (schedule exam → review results → lifestyle adjustment), and (3) send email/push reminder notifications for follow-up actions — all as a web service.

Target: Ages 45-60, with 1+ abnormal findings on health checkup, currently delaying follow-up exams
Revenue Model: Basic guidance and calendar free. Personalized health management plan (3-month) at $7.50 (~9,900 KRW). Referral booking to specialized checkup clinics.
Ecosystem Role: Regulation
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 (82%)

Tech Complexity
40.0/40
Data Availability
22.5/25
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 (58/100)

Competition
8.0/20
Market Demand
6.2/20
Timing
16.0/20
Revenue Signals
9.0/15
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 [low]
Dashboard