B

My Full Prescription List Organizer

2.75

Derivation Chain

Step 1 Aging population & Health management demand
→
Step 2 Increase in complex multi-prescriptions for 50s with chronic conditions
→
Step 3 Inability to consolidate prescriptions across multiple hospitals
→
Step 4 Blind spot for drug duplication & interaction risks

Problem

Adults in their 50s-60s receive prescriptions from 2-3 different hospitals (internal medicine, orthopedics, dermatology, etc.), totaling 6-10 different medications, but there is no user-friendly service to view all prescriptions in one place. While Korea's HIRA (Health Insurance Review & Assessment Service) offers a 'My Medications' service, it requires a public certificate login and has a poor UI, resulting in extremely low actual usage. As a result, when doctors ask 'What medications are you taking from other hospitals?', patients rely on memory, and drug interaction risks are overlooked.

Solution

Users photograph their medication packets or enter drug names to organize a complete medication list, with automatic flagging of duplicate ingredients and interaction risks. Generates a 'My Medication Card' to show during hospital visits. Instant interaction warnings when adding new medications against existing ones.

Target: Ages 50-65, regularly visiting 2+ hospitals, with 1+ chronic conditions (hypertension, diabetes, hyperlipidemia, etc.), who want systematic medication management
Revenue Model: Basic list management and interaction lookup free. Family sharing feature (children managing parents' medications) at 2,000 KRW (~$1.50)/month. Pharmacy partnership advertising.
Ecosystem Role: Infrastructure
MVP Estimate: 2_weeks

NUMR-V Scores

N Novelty
2.0/5
U Urgency
3.0/5
M Market
3.0/5
R Realizability
3.0/5
V Validation
3.0/5
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.
SaaS N=.15 U=.20 M=.15 R=.30 V=.20 Senior N=.25 U=.25 M=.05 R=.30 V=.15

Feasibility (62%)

Tech Complexity
24.0/40
Data Availability
18.3/25
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 (51/100)

Competition
8.0/20
Market Demand
6.2/20
Timing
14.0/20
Revenue Signals
7.5/15
Pick-Axe Fit
10.5/15
Solo Buildability
5.0/10
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 [medium] Backend [medium] AI/ML [medium]
Dashboard