Checkup History TrendBook

3.65

Derivation Chain

Step 1 Post-health checkup follow-up management

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Step 2 Year-over-year checkup metric trend visualization

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Step 3 Trend-based guidance on follow-up test necessity

Problem

Office workers in their 50s get annual national health checkups, but results only show that year's numbers without visualizing 3–5 year trends. Even when fasting blood sugar rises steadily from 95→100→108, each result is marked 'normal,' so they fail to recognize they're entering pre-diabetes. The National Health Insurance Service app lets users view past results, but it's just a list of PDFs with no trend graphs or risk-change alerts.

Solution

Users upload Health Checkup result PDFs or manually enter values on a web interface, and the system visualizes year-over-year trends for 12 key metrics including blood sugar, blood pressure, cholesterol, and liver function. Items that are 'within normal range but trending worse' are flagged with orange warnings, along with evidence-based guidance on which follow-up tests to consider.

Target: Ages 45–60, employees or regional health insurance subscribers who get annual checkups but can't properly interpret their results, at-risk for pre-chronic conditions

Revenue Model: 3-year trend analysis: Free. 5+ year long-term trends + risk score + follow-up test recommendation Report: 3,000 won (~$2.25) Per Transaction. Family member integrated trend management: 4,900 won (~$3.70)/month.

Ecosystem Role: Consumer

MVP Estimate: 2_weeks

NUMR-V Scores

N Novelty

3.0/5

U Urgency

3.0/5

M Market

4.0/5

R Realizability

5.0/5

V Validation

3.0/5

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 (71%)

Tech Complexity

29.3/40

Data Availability

21.7/25

MVP Timeline

20.0/20

API Bonus

0.0/15

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 (50/100)

Competition

8.0/20

Market Demand

6.2/20

Timing

14.0/20

Revenue Signals

7.5/15

Pick-Axe Fit

7.5/15

Solo Buildability

7.0/10

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 [medium] Backend [medium] Data Pipeline [low]

Dashboard